Unitary Foundation blog

Building a Bridge: A Look Back at the Inaugural unitaryDESIGN Event

Thu, 12 Mar 2026 00:00:00 GMT

At the heart of Unitary Foundation is a simple but important mission: to ensure that the quantum technology ecosystem benefits as many people as possible. For the ecosystem to be truly inclusive, it needs more than just functional code — it needs a bridge. It needs clear documentation, intuitive data visualization, and a language that invites everyone in, from veteran researchers to curious newcomers.

Our goal for unitaryDESIGN was just this. We set out to expand our vibrant, open-source community and emphasize design as a primary tool for science engagement. Over twelve high-voltage days this February, our community proved that when you pair technical expertise with creative storytelling, quantum tech can be approachable and exciting regardless of your disciplinary background.

Beyond Bug Bounties

The core of unitaryDESIGN rested on science communication - organizers and maintainers went into the event with the ethos that a project’s impact is only as strong as its accessibility. Throughout the event, participants worked to transform dense, technical READMEs and tutorials into clear, user-friendly guides that act as welcoming front doors for new contributors (here's a quick example).

Participants also helped maintainers build intuitive ways to see and understand the nuances of their work through video tutorials, branding updates, explanatory animations, data visualization, and educational challenges. Whether through reimagining a project’s "Why" or creating compelling visual narratives, these efforts ensured that the breakthroughs happening in the code are being seen — and understood — by a larger audience.

The Impact

383 participants from 51 countries registered for the event with 41 maintainers overseeing 15 projects.

In the end, participants earned $5935 by closing 46 of the 59 bounties (which were funded by Shift Grants and 2026 Unitary Foundation Members). Congratulations to everyone who participated and contributed!

The Projects

As always, our hackathons aren’t possible without hard working, dedicated maintainers who are willing to spend their free time reviewing PRs and mentoring participants. We are so grateful to all of the participating maintainers of unitaryDESIGN2026 - check out their projects below and consider contributing to their repos! You can also read about each project and which of their creative issues were closed here.

Participating Projects
Amazon Braket	MQT Core (Munich Quantum Toolkit)
Art with Quantum Dynamics (Moth Quantum)	Open Quantum Design
Deltakit (Riverlane)	PennyLane (Xanadu)
graphix	Piccolo.jl (Harmoniqs)
H-hat	QBraid-SDK; PyQASM (QBraid)
Metriq (UF)	Quantify (OrangeQS)
toqito	Quantum Open Source Foundation
zxlive

The Community Experience

While the code was built on GitHub, the pulse of the event was felt across our entire digital ecosystem. Maintainers served as sounding boards for one another and participants shared “getting started” resources on the UF Discord while conversations continued into the project repos and PR threads. We saw truly meaningful contributions emerge precisely where human connection was made - demonstrating that a collaborative spirit is key to success. This was an ecosystem without borders: hackers of all experience levels worked side-by-side and brought unique perspectives to the stack.

This creative energy shone across the cohort of participating projects. A fantastic example of this was seen at PennyLane, where the maintainer team leaned into the creative challenge, working closely with participants to produce puzzles, GIFs, and animations that demystify complex quantum concepts. You can see the results of that particular collaboration — including the winning designs and honorable mentions — over at the PennyLane blog.

Additional programming further bridged the gap between theory and practice. We were honored to host UF Advisor and microgrant alum Klem Jankiewicz, who led an informal "Ask Me Anything"-style group discussion about her journey as the Head of Design at Classiq. Her insights into what it truly means to be a designer in the quantum industry provided a potential roadmap for those looking to turn their creative skills into a career in deep tech.

Ultimately, the impact of unitaryDESIGN has already moved beyond the digital realm. The interdisciplinary energy of this event served as the direct inspiration for the NYC Quantum Design Hackathon, a first-of-its-kind gathering (developed by UF and our colleagues and former grantees at Harmoniqs) that proved just how hungry this community is for a design-led future. You can read the full recap of that sister event here.

Lessons Learned

unitaryDESIGN was an experiment in reimagining how open-source maintainers and contributors can collaborate. As with any inaugural event, we walked away with valuable insights on how to better support our community.

Firstly, while we saw a surge of interest from designers and artists at registration, they ultimately did not make it to our leaderboard this year. Part of this is the learning curve even for contributing on Github, and part of it is the fast-paced nature of the hackathon itself. In future iterations, we hope to offer more onboarding opprtunities (e.g. Zoom-based Github tutorials, connections to other educational opportunties ahead of the events, and regular office hours throught the event) as well as more face-to-face oppourtunies for all participants, like the Ask Me Anything session with Klem.

We also navigated the growing industry-wide challenge of automated content. While there were brilliant examples of participants using AI as a collaborative tool, we also saw instances where the human element was lost in favor of unvetted LLM outputs. Our aim is to cultivate an authentic and thoughtful ecosystem; as we move forward, we remain committed to finding new ways to ensure that the work we support reflects the genuine expertise and care of our community.

In both cases, we found a consistent truth: proximity matters. Whether through digital group discussions or in-person gatherings, the more we see one another as people, the more intentional and beautiful our collective work becomes.

Final thoughts: Making Quantum Technology Benefit Everyone

By treating design as a foundational tool for our community, we’ve seen that the quantum ecosystem can be as engaging as it is functional. This event demonstrated that there is a massive, untapped community of creatives ready to support the quantum stack — we just needed to build the right bridge to reach them.

We are incredibly proud of what our community achieved in such a short window. A huge thank you to our event sponsor, Shift Grants, as well as the Unitary Foundation Members for their vital support in bringing this inaugural edition to life. We’re already looking forward to seeing how these new connections continue to grow.

What’s Next?

Keep Designing: Our goal is continued momentum. If you found a repository that sparked your interest, don’t stop at the bounty - keep the conversation going with those maintainers. They are the heart of this industry and always welcome a helping (human) hand! And while you're at it, consider starring the repos that you're support. :)
Stay Tuned: Join our Discord, newsletter, and LinkedIn to be the first to find out about upcoming UF programming (spoiler alert: unitaryHACK is coming very soon!)

Metriq: A Collaborative Platform for Benchmarking Quantum Computers

Tue, 10 Mar 2026 00:00:00 GMT

Today we are releasing a major update to Metriq, our platform for open, community-driven quantum computer benchmarking.

This release introduces <a href="https://github.com/unitaryfoundation/metriq-gym" target="_blank" rel="noopener noreferrer">metriq-gym</a>, a new open-source toolkit for defining and running benchmarks across hardware providers, <a href="https://github.com/unitaryfoundation/metriq-data" target="_blank" rel="noopener noreferrer">metriq-data</a>, a public dataset of benchmark results, along with a new <a href="https://metriq.info/" target="_blank" rel="noopener noreferrer">Metriq website</a>, where results can be tracked and shared.

We invite the quantum community to suggest improvements, extend the benchmark suite, run experiments, and upload new results. As quantum computers evolve over time, the Metriq platform will evolve with them. Check out our <a href="https://arxiv.org/abs/2603.08680" target="_blank" rel="noopener noreferrer">new paper</a> describing the platform, and see you on GitHub!

Our goals for Metriq

How does a processing unit U perform on workload W – and how has that changed over time?

In classical computing, answering this question is possible through mature and (mostly) standardized benchmarking. Before buying a GPU, one can usually find side-by-side benchmarks for the games they want to play or the ML models they want to train; for CPUs, tools like Geekbench summarize performance across common everyday tasks (file compression, compiling C programs, rendering PDFs, and more). At the high end, LINPACK benchmarks have long been used to rank the world's most powerful supercomputers. And in the GenAI era, MLPerf brought benchmarking into the modern ML world by giving researchers, vendors, and practitioners a shared suite for training and inference.

In quantum computing, a crisp answer to the same question is still a work in progress. Benchmarking quantum computers today means navigating a fragmented landscape where reproducibility is the exception, not the norm. The challenges are both practical and structural:

Vendor-specific tools tied to a single hardware stack
Results scattered across papers and press releases
No standardized cross-platform datasets
Benchmarks rarely reproduced independently, with code often isolated in hard-to-find Python notebooks.

Still, there has been important progress. Early benchmarks such as Quantum Volume helped establish common ways of characterizing quantum processors, while later proposals like CLOPS and EPLG explored additional dimensions of performance, from execution speed to layered-gate fidelity. Community efforts such as the QED-C benchmarking initiative and benchmark suites like SupermarQ, QUARK, and BACQ have continued to expand the landscape.

Yet despite this progress, benchmarks are still difficult to run and compare across platforms, and results often remain scattered across papers and repositories.

Today we're launching the Metriq Platform: an open, collaborative workflow for

running benchmarks reproducibly across hardware from different vendors,
publishing the resulting data with transparent provenance, and
making it easy for the community to explore and discuss results constructively.

📃 Alongside this release, we've posted a <a href="https://arxiv.org/abs/2603.08680" target="_blank" rel="noopener noreferrer">companion paper on arXiv</a>. The paper provides technical background for the platform: how the workflow is designed, how the benchmark suite is implemented, and how we think about aggregation, cost, and the practical blockers that keep “benchmarks in theory” from becoming “benchmarks people can actually run.” The paper also showcases a collection of cross-vendor results obtained through the Metriq platform itself.

What makes Metriq different?

Metriq is designed to act as a neutral reference point — a shared foundation for constructive comparison rather than a stack-specific performance lens. The platform is:

Vendor-neutral: Metriq is an independent project maintained by the nonprofit Unitary Foundation.
Cross-platform by design: The same benchmark configuration runs across multiple providers.
A living platform: Benchmarks are periodically re-executed, enabling longitudinal tracking as devices and stacks evolve.
Open and transparent: Code is fully open source, and datasets and schemas are public and structured around FAIR principles.
Community-driven governance: Benchmarks are proposed via open RFCs, results are peer-reviewed, and aggregation choices are discussed in the open.
Schema-validated reproducibility: Benchmark configurations are formally defined and validated so "the same benchmark" actually means the same experiment.

A runner, a dataset, a new website

In practice, the Metriq platform is built around three complementary components that together form the benchmarking workflow.

metriq-gym is the runner: a Python toolkit that dispatches benchmark circuits to different quantum providers and collects results in a standardized format.
metriq-data is the dataset: a public, versioned repository of benchmark results.
metriq-web is the web interface (currently in beta at https://metriq.info), which turns the dataset into a set of interactive dashboards.

<figure> <img style="display:block; margin:auto;" src="/images/2026_metriq_platform/metriq-platform.png" alt="Metriq platform component" /> <figcaption>The Metriq platform architecture.</figcaption> </figure>

An initial suite of benchmarks

Along with the infrastructure, we are releasing a curated suite of benchmarks designed to probe different aspects of quantum computers. A device can have excellent two-qubit gate fidelity but poor connectivity, or great coherence but low throughput. We wanted a suite that assesses different dimensions of performance, and that people can actually afford to run.

The suite currently includes eight benchmarks spanning system-level diagnostics and application-inspired workloads. We see this as a first draft that will evolve with community input.

We chose benchmarks that are frugal (cheap enough to reproduce) and scalable (still meaningful as devices grow). The suite is intentionally opinionated — these are the benchmarks we think matter today — but it's designed to evolve (see it as a version 1.0 and we are looking forward to many more versions to come!)

<figure> <img style="display:block; margin:auto;"
src="/images/2026_metriq_platform/metriq-gym.gif" alt="metriq-gym CLI" /> <figcaption>metriq-gym CLI in action.</figcaption> </figure>

For the first release, we ran the full suite across devices from IBM, Quantinuum, IQM, Rigetti, and OriginQ — eleven devices in total. The results are aggregated into a composite Metriq score that normalizes each benchmark against a baseline device and combines them with scale-aware weights. It's a single number meant to start conversations, not end them. The paper goes deep on how the scoring works, the tradeoffs involved, and why we made the choices we did.

A starting point

The results in our companion paper are a snapshot of the dataset at this point in time. Quantum hardware is a moving target: devices get recalibrated, new systems come online, and providers update their software stacks regularly. Any static set of benchmark numbers will drift out of date. That's exactly the point of Metriq: it is designed as a living platform rather than a one-off study. Benchmarks get re-executed periodically, new results are submitted regularly, and the dataset grows over time. Follow along at https://metriq.info/ to see the latest results.

An open invitation

The Metriq Platform only works if people use it, contribute to it, and discuss it. Above all, this post is a call to the community to contribute ideas, feedback, and code.

Here is how to get involved:

Run benchmarks and submit results. Pick a device you have access to, run the suite with metriq-gym, and open a PR to metriq-data. Every submission is reviewed and becomes part of the public dataset.
Review existing data. Spot something that looks off? Flag it. Peer review of benchmark results is just as valuable as peer review of papers.
Propose new benchmarks. Think something important is missing from the suite? Open an <a href="https://github.com/unitaryfoundation/metriq-gym/issues" target="_blank" rel="noopener noreferrer">issue</a> and make the case.
Join the conversation. Find us on the #metriq channel in the <a href="https://discord.unitary.foundation" target="_blank" rel="noopener noreferrer">Unitary Foundation Discord</a>, or start a thread in <a href="https://github.com/unitaryfoundation/metriq-gym/discussions" target="_blank" rel="noopener noreferrer">GitHub Discussions</a>.
Contribute code. Whether it's improving the runner, adding new benchmarks, or building new features for the website, contributions to the codebase are always welcome.
Simply star the repositories. ⭐️

We also hope that our platform creates a positive flywheel for the benchmarking ecosystem: as Metriq scores become more visible and useful, we hope that hardware vendors and cloud providers will make it increasingly easy to run benchmarks on their systems.

Benchmarking is ultimately a community effort. We would like to acknowledge the <a href="https://unitary.foundation/posts/2024_benchmark_committee/" target="_blank" rel="noopener noreferrer">Open Quantum Benchmark Committee (OQBC)</a>, an initiative we launched in 2024 to bring together researchers, hardware providers, and practitioners around open benchmarking discussions. Members of the committee have helped us iterate on Metriq by providing feedback on benchmark definitions and methodology. Within the Metriq Platform, we see the committee playing a role similar to a working group, comparable to those in initiatives like <a href="https://mlcommons.org/working-groups/" target="_blank" rel="noopener noreferrer">MLCommons</a>.

We would like to thank our paper co-authors Tom Lubinski, Siyuan Niu, and Neer Patel, as well as the early contributors to the Metriq codebase who helped make this launch possible – including contributors to <a href="https://github.com/unitaryfoundation/metriq-gym/graphs/contributors" target="_blank" rel="noopener noreferrer">metriq-gym</a>, <a href="https://github.com/unitaryfoundation/metriq-web/graphs/contributors" target="_blank" rel="noopener noreferrer">metriq-web</a>, and <a href="https://github.com/unitaryfoundation/metriq-data/graphs/contributors" target="_blank" rel="noopener noreferrer">metriq-data</a>.

What's next?

A few directions we're actively thinking about for developing the platform further:

More benchmarks, more providers. The current suite of eight benchmarks is a starting point. We plan to continue adding new benchmarks, supporting additional hardware providers, and scaling existing benchmarks to larger problem sizes as devices catch up.
Logical-qubit benchmarks. As fault-tolerant devices start to emerge, benchmarking needs to move beyond physical qubits. We're working on protocols that evaluate logical-level performance.
Quantum error mitigation. Integration with Mitiq to optionally layer error suppression techniques (ZNE, PEC, dynamical decoupling) on top of benchmark runs.
Community features. The Metriq website will make it easier to interact and discuss results.

The goal isn't to declare winners. It's to build a shared empirical record of quantum hardware performance that helps the field track progress toward quantum advantage and fault-tolerant computing.

We look forward to continuing to develop Metriq with and for the quantum computing community.

From Code to Choreography: Highlights from the NYC Quantum Design Sprint

Fri, 06 Mar 2026 00:00:00 GMT

This is a collaborative post between UF + Harmoniqs staff. All photography by Won Jun Seok · wonjunseok.com

The Vision.

<figure style="text-align: left;"> <img src="/images/QDH/MS garage.jpg" alt="microsoft garage before the event started" width="500"> <figcaption style="font-style: italic; color: #555; margin-top: 8px;"> The calm before the creative storm </figcaption> </figure>

On February 20, 2026, a group of quantum enthusiasts gathered in NYC for the first ever Quantum Design Hackathon, a unitaryDESIGN event presented by Harmoniqs and Unitary Foundation. We brought together 80+ participants to tackle one big question: <br> <div style="text-align: center;"> <em>"How do we communicate the quantum world?"</em> </div>
<br> With a crowd spanning design, art, physics, and engineering, it wasn't just a technical challenge—it was some of the most fun we’ve ever had.

As organizers, our goal was simple: bring new voices into quantum. By pairing creative newcomers with veteran researchers, we set out to spark fresh excitement and bridge the communication gap between the lab and the world.

Accessibility was our north star. Between collaborative hacking sessions, we hosted a series of talks designed to orient, inspire, and demo the future of the field:

Ben Castanon, CEO of Unitary Foundation – Welcome to Quantum Design Hackathon
Mike Pell, Director of the Microsoft Garage (Keynote) – Creativity, Quantum, and the "Why"
Aaron Trowbridge, CEO of Harmoniqs – QC Fundamentals & Harmoniqs Demo
Stewart Smith, Head of Experience Design, Moth Quantum – Hackathon Visualizations & Inspiration
Francesco Valenti, IBM – Qiskit Platform Demo
Dalila Pasotti, Art & Natural Sciences – Artistic applications
Ishaan Pakrasi, Quantum Product, AWS / Specialist Lecturer, UAL – Quantum and Creative applications
David Bryant, Chief Creative Officer of IBM (Keynote) – Closing Perspectives

The Challenge.

The challenge was intense: a "One Day, Six Hours" sprint to make the invisible tangible. With hackers split across 9 powerhouse teams, each group (with the support of mentors from diverse disciplinary backgrounds) took on the challenge of demystifying a specific qubit through creative storytelling and design—ranging from interactive simulations to a hackathon first: a full-blown theatrical debut. (Keep an eye out; they might just be headed for Broadway!)

<figure style="text-align: center; margin: 0;"> <img src="/images/QDH/Hacker team v1.jpg" alt="group working together at a table" style="width: 100%; aspect-ratio: 1 / 1; object-fit: cover; border-radius: 4px; border: 1px solid #eee;"> <figcaption style="font-style: italic; color: #555; margin-top: 10px; font-size: 0.9em;"> Team working together during the hack. </figcaption> </figure>

<figure style="text-align: center; margin: 0;"> <img src="/images/QDH/Showing work.jpg" alt="whiteboard table with writing on it" style="width: 100%; aspect-ratio: 1 / 1; object-fit: cover; border-radius: 4px; border: 1px solid #eee;"> <figcaption style="font-style: italic; color: #555; margin-top: 10px; font-size: 0.9em;"> Gotta show your work. </figcaption> </figure>

<figure style="text-align: center; margin: 0;"> <img src="/images/QDH/A phenomenal performance.jpg" alt="two men dancing as part of their presentation" style="width: 100%; aspect-ratio: 1 / 1; object-fit: cover; border-radius: 4px; border: 1px solid #eee;"> <figcaption style="font-style: italic; color: #555; margin-top: 10px; font-size: 0.9em;"> A phenomenal performance. </figcaption> </figure>

<figure style="text-align: center; margin: 0;"> <img src="/images/QDH/Youngest participant age 9.jpg" alt="back view of a child high fiving a woman on stage" style="width: 100%; aspect-ratio: 1 / 1; object-fit: cover; border-radius: 4px; border: 1px solid #eee;"> <figcaption style="font-style: italic; color: #555; margin-top: 10px; font-size: 0.9em;"> Our youngest participant receiving kudos. </figcaption> </figure>

</div>

The Winners!

As our opening keynote Mike Pell reminded us, the heart of this hackathon was collaboration, learning, and community—not just competition. In that spirit, we moved away from a single "grand prize" to celebrate excellence across five distinct categories. Here are the teams that took home the honors (and you can check out all of the projects in detail here!):

Best Visual Design
PHOTON & Quantum Rescue (Group 8)
Eloise Yalovitser, Arsh Kaushik, Shawn Dai, Ilayda Dilek, Ethan Feldman, Allen Tu, and Kezia Widjaja
<img src="/images/QDH/Group 8.jpg" alt="group8" width="375">

Best Experience
Silicon Pulse: Silicon Spin Explorer (Group 7)
Hannah Zhao, Raghav Mysore Vishveshwara, Sara Andotra, Atsuko Shimizu, and Ann Mahe
<img src="/images/QDH/Group 7.jpg" alt="group7" width="375">

Best Translation of a Quantum Concept
CAT Qubit Visualization (Group 2)
Will Stark, Elizabeth Jiang, Yuni Jung, Amiratabak Bahengam, and Christina Lu
<img src="/images/QDH/Group 2.jpg" alt="group2" width="375">

Most Original Abstraction/Metaphor
Transmon Quantum Computer (Group 1)
Han Qin, Samriddhi, Senuri, Sherly Deng, Miguel Palma, and Obi Nami
<img src="/images/QDH/Group 1.jpg" alt="group1" width="375">

Audience Favorite
The Qubitarium of Trapped Ions (Group 5)
Ricky Soto, Mahnoor Fatima, Carrie Jaquith, Jasper Sands, Dylan Kawalec, Timothy Clark Dauz, and Alex [age 9!]
<img src="/images/QDH/Group 5.jpg" alt="group5" width="375">

Voices from the Hackathon.

“We built this hackathon with the Harmoniqs team to serve the unitaryDESIGN goal of an open-source quantum community. Unitary Foundation has always been about making quantum technology benefit as many people as possible—and seeing this community come together in NYC felt like watching that mission come to life in real-time.” – Veena Vijayakumar, Unitary Foundation

"As was echoed by the incredible speakers we managed to get, the understanding of the natural world, what we call physics, and visual design have been entangled from the start. Today, we can build the most incredible devices that harness and wrangle quantum physics, but the visualizations of these devices have not kept pace with technological progress. Seeing what teams of designers and physicists could accomplish—in just four hours of hacking—that gap is inexplicable. We need more of this: more creativity, more ingenuity, more harmony, more unitarity!" – Aaron Trowbridge, Co-Founder & CEO, Harmoniqs

Hacker quotes

“I'm a product designer so I've always worked with software engineers and designers, so working with physicists was a very new and exciting experience for me”

“The most valuable part was the interdisciplinary collaboration—learning quantum concepts through hands‑on making with designers, artists, and engineers, supported by accessible mentors. This made complex ideas feel approachable and enabled creative, intuitive interpretations rather than purely theoretical discussions.”

“Seeing the mentors' work and how it bridged the creative and scientific fields was inspiring. And meeting new people in totally different fields was a great way to get out of my own circle.”

“Meeting people outside of work, especially designers (since I mostly work with STEM folks). Very refreshing to get other perspectives on the QC field. Very interdisciplinary event!”

“The diversity of voices in the room. Such a unique combination of people to learn from, all in one night.”

Gratitude & Supporters.

At the start of the day, we didn’t fully know what would unfold. Bringing artists, designers, physicists, and engineers into the same room was an experiment in itself. What conversations would emerge? What would happen when radically different disciplines shared an eight-hour sprint? What emerged was more than a hackathon — it was proof that quantum needs creative collaboration to move forward.

This event was made possible by the right people and the right partners.

A huge thank you to Microsoft Garage for hosting us in a space built for bold experimentation and real innovation. It was the perfect setting to explore what happens when science meets design.

We’re grateful to J.P. Morgan for their strategic support and belief in advancing emerging technologies through community-driven initiatives.

Thank you to our community partner, Moth Quantum, for helping bridge quantum and experience design — and for championing better ways to translate complex science into human understanding.

And to our mentors: this sprint worked because of you. Across nine teams, you helped participants navigate qubit architectures, clarify technical concepts, pressure-test ideas, and push creative boundaries:

Deborah Berebichez, AI and Quantum Leader
Kate Bonner, Columbia University + Independent Designer/Artist
Tyson Jones, NVIDIA
Alberto Maldonado, QOSF
Jordan Harvey, Remote Control
Grace Lindsell, IBM
Stewart Smith, Moth Quantum
Francesco Valenti, IBM
Dalila Pasotti, Independent Artist
Ishaan Pakrasi, AWS + UAL

As the night wrapped and projects hit the stage, one question kept coming up: When’s the next one? So…

What’s next?

Here's what YOU can do right now to make sure you're in the know for the next Quantum Design Hackathon:

Explore the Work: <a href="https://quantum-design-hackathon.github.io/index.html" target="_blank" rel="noopener noreferrer">Check out↗</a> all of the projects that were presented in this iteration of the hackathon and feel free to reach out to us with feedback!
Join the Community: Follow Harmoniqs and Unitary Foundation on socials to be the first to find out when we announce the next quantum design event
Chat with us: We have a Quantum Design channel on the Unitary Foundation Discord server. You can learn more about what's happening next, ask questions about ways to upskill what you've learned, and more!

Our Vision for the NSF Tech Labs Initiative

Thu, 12 Feb 2026 00:00:00 GMT

At Unitary Foundation, our mission has always been to ensure that the quantum ecosystem benefits the most people. The National Science Foundation’s (NSF) new Tech Labs initiative opens up an exciting new mechanism to lay the foundations of our software ecosystem, keeping it free, accessible, and heterogeneous.

What are the NSF Tech Labs?

The NSF recently announced the Tech Labs initiative through its Directorate for Technology, Innovation and Partnerships (TIP). This program represents a shift in how the federal government supports innovation. Rather than focusing solely on early-stage academic research, Tech Labs are designed to bridge the gap between laboratory discovery and real-world, commercialized technology.

These labs are meant to be agile, multidisciplinary hubs that focus on scale-up and translation. They aim to provide the resources—funding, infrastructure, and personnel—necessary to take "deep tech" from a proof-of-concept to a robust, reliable platform that can support entire industries. By fostering system-level innovation, the NSF hopes to secure U.S. leadership in critical emerging fields like AI, biotechnology, and, most importantly for our community, quantum information science.

Why This Matters Now

Progress in quantum technology is reaching a critical inflection point. We are moving past the era of pure physics breakthroughs and into an era of engineering challenges. However, the current ecosystem is fragmented. We see a landscape of vendor-specific stacks, bespoke compilers, and non-interoperable runtimes.

This fragmentation creates vendor lock-in and slows down the entire field. Without a shared, trusted software foundation, we risk slower capability diffusion compared to other fields. We believe a Tech Lab is required now to address this market failure—creating a platform that private companies alone cannot justify building, but that the entire industry needs to thrive.

Private and public investment in quantum is at a record high, scaling to $8Bn+ private venture investment in 2025 and with large scale USG programs like the DARPA QBI program and the DOE National Quantum Initiative Science Research Centers. Despite this investment, the software bottleneck persists. This is because the bottleneck fits in a gap between traditional academic grants, vendor roadmaps, or venture-backed startups. It requires a mission-driven, full-time, multidisciplinary, hardware vendor-independent team operating with autonomy, a long-term horizon, and milestone-based accountability.

With the advancements in the field’s infrastructure and hardware developers beginning to demonstrate advantage for end users, it is no longer premature to have a uniform layer of software on top of heterogeneous hardware. Instead, this opportunity will allow the cross-platform hardware R&D work done within the quantum industry and academia to reach the market quicker and more cost effectively. Siloed roadmaps would inevitably lead to significant delays in the development of operating systems and pose significant disadvantages to US leadership in quantum technology. Furthermore, according to a recent study by the Harvard Business School, existence of strong open source tools has been shown to reduce the costs of software for companies by 3.5x, while investments totaling $4.15B in open source tools has generated $8.8T in value across technology fields, creating strong incentive for ongoing industry support for Tech Labs projects such as this. To that end, Tech Labs IP rights should be structured to allow for open source contributions, while maintaining flexibility for those who would like to conduct further research, or pursue new start-up entities.

Our Idea: An Open Quantum Operating System

Our vision is to design, build, and deploy what we call a quantum Linux: a shared, open, production-grade system software layer for hybrid quantum–classical–AI computing. Just as Linux catalyzed decades of innovation in classical computing by providing a stable, common foundation, an open quantum operating system will:

Unlock Interoperability: Enabling hardware platforms, cloud providers, and researchers to work together seamlessly.
Reduce Friction: Lowering the barrier to entry for application developers and startups.
Secure National Infrastructure: Providing auditable, transparent software for defense and critical infrastructure.

Why Unitary Foundation?

The UF community isn’t just theorists; we are builders. Since 2018, Unitary Foundation has operated in the exact institutional gap that the NSF Tech Labs are designed to fill. Our credentials include:

Proven Stewardship: We maintain the largest global open quantum software community, with over 5,800 developers and 400+ active contributors, and long-term projects like QuTiP.
Global Impact: Through our microgrant program, we have supported 130+ open-source projects, resulting in widely adopted libraries, startups, and follow-on funding.
Neutral Governance: We have a track record of convening competing stakeholders—including IBM, AWS, Microsoft, and IonQ—to work toward the common good.
Technical Excellence: Our internal technical team stewards essential projects like Mitiq (error mitigation), Metriq (benchmarking), and the long-term maintenance of QuTiP.
Cross-sector Partnerships: Our work has been supported by partners across academia, industry, government, private foundations and individuals.

We operate today in the institutional gap that NSF Tech Labs are designed to fill and this informs our recommendations here. We see the most effective management and structure for the Tech Lab, to ensure speed, operational autonomy, and best use of resources, as an entity housed within the non-profit with full time leadership and a technical team wholly devoted to achieving the goals for each phase of the Tech Labs project, with the ability to spin out into an independent entity if needed for sustained growth.

How a Tech Lab Can Impact Our Community

This initiative isn't just about big-picture policy; it’s about the researchers, hackers, and builders who make up the Unitary Foundation community. Here is how a Quantum Tech Lab will directly benefit our grantees:

Seamless Integration: Currently, many of our micrograntees build brilliant tools that struggle to find users because they are "islands" in a fragmented ecosystem. A standardized "Quantum Linux" means your tool—be it a new compiler or an error mitigation technique—can be integrated into a common stack used by major hardware providers.
A Career Pipeline: We envision the Tech Lab as a destination for the talent we discover through microgrants. It provides a path for early-career practitioners to transition from a single project to contributing to national-scale infrastructure.
Reduced Development Costs: By providing robust, open-source "plumbing" (like runtimes and drivers), we allow you to focus your energy on high-level innovation rather than reinventing the wheel.
Sustainability: One of the hardest parts of open source development is maintenance after the initial grant ends. The Tech Lab model provides the long-term stewardship needed to ensure your contributions remain useful and maintained for years to come.
Community Building: A large-scale open source project like a Tech Lab will provide new opportunities to gather, learn, critique, and contribute to field-defining projects. With Unitary Foundation’s ongoing community initiatives, we will be able to build a more connected and cohesive ecosystem.

How Program Design Can Help Tech Labs Succeed

Program design should emphasize potential for impact over restrictions on size or structure. Partnerships should be enabled by the program structure, but not demanded if unnecessary for the ultimate de-risking of the technology in question. Further, milestones should ensure that new standards, products, and services can emerge organically from each Tech Lab. And IP and contract rules and regulations should help this effort, not hinder it.

The Tech Labs initiative provides a unique opportunity to pursue systems changing projects with more freedom than traditional grantmaking programs. As such, we believe team eligibility should be as broad as possible. Each field has its own unique needs that will be best suited by an entity tailored to address them, rather than conform to any universal model. An emphasis should be placed on team capacity, expertise, ability to execute, and potential to scale, above other eligibility criteria. Team independence will be paramount for Tech Labs projects to move quickly, take advantage of new opportunities, and respond to the needs of the fields they serve. Independence can be defined here as the ability to make new programmatic decisions that serve the Tech Lab’s stated goals, the ability to hire new team members, and the ability to form new strategic partnerships that serve the Tech Lab goals, without unnecessary hindrance from bureaucratic overhead.

Announcing Our New CEO

Mon, 09 Feb 2026 00:00:00 GMT

Unitary Foundation has grown by leaps and bounds since its origins as a microgrant fund in 2018. With 136 grants distributed across 30+ countries, hundreds of thousands of downloads of public goods projects like Mitiq, Metriq, UCC, and QOSS, and a fantastic community of 5,700+ developers using our Discord, we are building the infrastructure necessary to ensure quantum technology is accessible and useful to all.

The future of quantum tech needs strong open foundations.

The quantum tech industry is also scaling rapidly ($3Bn+ in private VC in 2025) and the open source ecosystem needs to grow with it. Our public goods and open source work across quantum is more useful and important than ever. It will remove bottlenecks and ensure we have the widest possible participation in our field’s advancement.

To ensure we respond to this moment, we began a search last year to find a CEO for Unitary Foundation, with the goal of driving open-source projects critical to the quantum ecosystem, scaling funding, partnerships, and community, and fulfilling the Foundation's mission across industry, government, and academia.

After completing our search, I am thrilled to announce Ben Castanon as Unitary Foundation's first CEO!

Ben has been with Unitary Foundation over three years, beginning in the role of Chief of Staff, before being named COO in 2024; overseeing partnerships, community, and grantmaking. Under his direction, UF has grown its Labs initiative including expanding its open benchmarking initiative and the Quantum Open Source Software Survey, securing the first private foundation support of the non-profit, inaugurated the unitaryCON workshop series, opened Unitary Foundation France, scaled the membership program, and much more.

Prior to his work at Unitary Foundation, Ben spent 15 years in philanthropy and non-profits focused on scaling innovative support mechanisms and community development resources for scientists and artists operating at the vanguard of their fields.

On behalf of the rest of the board of directors, we are thrilled to work with Ben to continue to scale our work and impact on the open source quantum community.

Open source tools and public goods will be the backbone of the field, a multiplier and democratizer for research and innovation. Our work lies at the center of it all. I’m thrilled to lead the Foundation to ensure our growing open source community is well-resourced, connected, inclusive, and thriving. - Ben Castanon, CEO, Unitary Foundation

Want to get involved? Join nearly 6,000 developers from around the world on our Discord to learn more about building the quantum open source ecosystem.

Unitary Foundation 2025 Annual Report

Thu, 05 Feb 2026 00:00:00 GMT

Read the full 2025 Annual Report here.

To the UF community,

2025 gives me the privilege to reflect on what has yet again been the largest year for quantum technology. Private investment in 2025 surpassed $10Bn, more than double the previous high water mark in 2024. We now see several large public quantum technology companies, increased acquisitions and dealmaking, new public initiatives and spotlight focus at the national level. Quantum technology ranked second, right after AI, on the list of 2025 Science and Technology Highlights released by the White House.

In 2025, we’ve also seen an openness to support new funding structures, with new Focused Research Organizations and the newly announced NSF Tech Labs program. This validates our view that new and independent organizations, with dedicated teams in a specific space, can go faster in new fields. Unitary Foundation has operated as a startup research organization from the beginning, and we are encouraged to see more partners adopting this approach.

If you want to feed a fire then you need to open breathing space between the logs to allow air in as fuel. At Unitary Foundation, we continue to build these open spaces through the microgrants, community programs, and open source software that draw in the talent to grow the quantum industry. In 2025, we hosted our largest unitaryHack yet, with 65% of participating hackers engaging in open source for the first time.

Our mission is to lower the barriers to entry in quantum technology by building open, durable infrastructure that helps the field grow faster, and grow well.

While quantum tech advances, it has done so alongside a remarkable acceleration in artificial intelligence. It remains striking that some of the world’s most powerful foundation models are so widely accessible through cloud platforms, open source releases, and global communities of builders. Sci-fi might have you expect that such tech would only be available in a secret base, but these tools are being used by people all over the world to solve problems that matter to them, to express creativity, and to explore science and mathematics. Increasingly, they are also being used to help build quantum technology itself.

We will all benefit if quantum technology grows with this same openness: scaling responsibly, remaining accessible, and shaped to advance human flourishing through the fundamental rules of nature: quantum mechanics.

William Zeng, PhD

President, Unitary Foundation

Read the full 2025 Annual Report here.

Welcome to our Newest Microgrant Advisory Committee Members

Fri, 23 Jan 2026 00:00:00 GMT

Unitary Foundation is excited to welcome the newest additions to our 2026 Advisory Board! <br> Many in this global group of volunteer champions have been active participants in the UF community, from organizing in-person workshops to co-authoring research papers with the UF team. A subset of these advisors are also UF microgrant alumni who bring a special point of view to the application review and mentorship process.

The microgrant advisors are all experts in their fields, and they bring experience across the quantum technology stack and beyond. They work at academic research centers, corporate research divisions, and startups, both collaborating on large open source projects and having authored personal projects. Importantly, they all share our commitment to growing the community of open science and technology.

The advisory board will help source and review grant applications, mentor projects, and provide technical advice on UF’s research program. We are grateful for their help and are excited to bring them on board to recognize their contribution!

Below are the newest members of the committee. Continue scrolling to see the veteran advisors and UF staff rounding out the team.

A warm welcome to the newest advisors

Dr. Edoardo Altamura is a quantum software engineer and research scientist specializing in quantum algorithms and their applications to the natural sciences. He is a Principal Investigator in several award-winning STFC–HNCDI quantum computing projects, and a technical lead of Qiskit Machine Learning, one of the world’s most used open-source quantum applications libraries, with over one million downloads and thousands of active users. He also serves as a Visiting Research Fellow at the University of Cambridge Yusuf Hamied Department of Chemistry, where he co-leads collaborative work on quantum machine learning and quantum chemistry methods.

Coleman Collins is a professional product manager, semi-professional writer, and intermittent entrepreneur and angel investor. He serves as VP of Product Management, Quantum Computing at IonQ a leading public quantum technologies company. Before IonQ, Coleman was an innovation- and New Product Introduction (NPI)-focused strategic technology consultant, serving a variety of Fortune 50 and Global 500 clients across the banking, consumer technology, retail, and transportation sectors.

Dr. Leonardo Disilvestro has 10+ years of experience in quantum computing and holds a mathematical physics degree from the University of Edinburgh and a Ph.D. in quantum information theory from Telecom ParisTech. As Head of Integrations at Entropica Leonardo works at the interface between Entropica’s software stack and partners, with the goal of bringing fault-tolerant quantum computations closer. One partnership at a time!

Dr. Shangjie Guo is a quantum physicist and research leader whose work connects quantum algorithms, machine learning, and the foundations of quantum theory. With more than a decade of experience, he has contributed to quantum algorithm design, quantum computing hardware modeling, error mitigation, and theoretical quantum physics. Shangjie currently leads digital science and quantum computing strategy at bp, where he develops quantum approaches that bring business value to optimization, chemistry, sensing, and secure communication. He is also the president and co-founder of FinQ Tech, one of the largest quantum-technology communities in the United States, dedicated to education, innovation, and academia–industry collaboration.

Klem Jankiewicz is a design expert focused on making quantum computing more accessible through user-centered interfaces and visualization. As Head of Design at Classiq Technologies, she leads the product design of Classiq's quantum algorithm development platform, creating intuitive graphical tools for quantum engineers and researchers. She co-founded Quantum Flytrap, an educational initiative supporting learning and experimentation in quantum technologies, and has collaborated with organizations including Pasqal, Xanadu, and the Centre for Quantum Technologies at the National University of Singapore.

Dr. Charles Yuan is an Assistant Professor of Computer Science at the University of Wisconsin–Madison. His research examines the challenges of programming quantum computers and other emerging models of computation. His work has appeared in the ACM SIGPLAN POPL, OOPSLA, and PLDI conferences and has been recognized with the SIGPLAN Distinguished Artifact Award and the CQE-LPS Doc Bedard Fellowship.

Welcome back to our returning advisors

UF is lucky to have advisors who continue to contribute their time year after year to support explorers in the quantum computing space. Here are our continuing advisors for 2026.

Dr. Jamie Friel, Oxford Quantum Circuits </br>Dr. Sonika Johri, Coherent Computing Inc </br>Dr. Ryan LaRose, Michigan State University </br>Dr. Roger Luo, QuEra Computing Inc. </br>Dr. Ying Mao, Fordham University </br>Dr. Daniel Mills, Quantinuum </br>Elena Pena Tapia, IBM </br>Dr. Ryan Shaffer, AWS </br>Nate Stemen, University of Amsterdam </br>Misty Winsor, Q-CTRL

UF Staff

Brad Chase </br>Alessandro Cosentino </br>Farrokh Labib </br>Changhao Li </br>Vincent Russo </br>Nathan Shammah </br>Will Zeng </br>Ben Castanon </br>Veena Vijayakumar

Introducing unitaryDESIGN - Save the Date!

Thu, 11 Dec 2025 00:00:00 GMT

Unitary Foundation is excited to announce the inaugural edition of unitaryDESIGN, our newest online hackathon!

unitaryDESIGN encourages people to make contributions to the open source quantum ecosystem through the lens of community engagement and science communication. If you've ever participated in our annual unitaryHACK, this hackathon runs quite similarly but with more of a focus on repository documentation, data visualization, and overall science communication.

The event will run February 16-27, 2026, and hackers at all experience levels have the opportunity to win cash bounties!

Interested in participating in this new effort? Here’s what you can do right now:

Check out the unitaryDESIGN website to learn more about the rules and take a peek at the participating projects
Register for unitaryDESIGN through this link (give Airtable a minute to load)
Join us on Discord to be the first to hear announcements and ask our team any questions you may have leading up to the event
Share this opportunity with your friends and colleagues in other networks!

Keep an eye out for new announcements coming in the new year. See you all in February!

unitaryDESIGN is made possible by a generous donation from Shift Grants as well as support from Unitary Foundation members. Thank you all for your support and guidance!

A Warm Welcome to Classiq, UF’s newest Supporting Member

Wed, 03 Dec 2025 00:00:00 GMT

Dear UF Community,

We’re delighted to announce a major addition to the Unitary Foundation community: Classiq has joined us as a Supporting Member!

Classiq is a pioneer in the quantum industry, known for its powerful software platform that allows developers to design, synthesize, and optimize complex quantum circuits. Their work is all about making advanced quantum development more accessible and efficient — a goal that aligns perfectly with our mission. The Classiq library, which is one of the most comprehensive in the industry, features over 200 maintained notebooks. Check it out here.

We are incredibly proud to partner with a company that is innovating at the intersection of software and quantum hardware. Classiq's support ensures that we can continue to grow our community and provide the essential resources needed to keep the quantum ecosystem open, diverse, and robust.

Thank you, Classiq, for committing to this shared vision!

With warmth,</br> The Unitary Foundation Staff

How Canada’s Quantum Arcade Came To Be

Wed, 26 Nov 2025 00:00:00 GMT

The following is the story of Canada’s Quantum Arcade from the point of view of Ella Meyer and Timothy King who have been working to stand it up since 2023.

Ella and Timothy are 2024 Unitary Foundation micrograntees. </br> </br>

diversifying talent and increasing interest in quantum through gaming.

Ella: Beginning in 2019, UBC Geering Up had been working with multiple partner organizations to introduce K-12 students in British Columbia to quantum computing. Through the (now 6 years) of the project, we had tried a ton of different types of programs to get students engaged and excited about this field. Part of this was developing some online games and demos for students to play. In 2023, I received an out of the blue email from Tim.

Tim: I’d been teaching computer technology from an engineering angle in Ontario for twenty years when I was asked by the Information & Communications Technology Council who ran the CyberTitan competition my students and I competed in if I’d like to be seconded and do cyber-education outreach nationally. In my high school I was always going after the next big thing. We did a VR pilot in 2016, had a gamedev program in place years before others popped up, and then got into cybersecurity when education still (as it does now) thought it was someone else’s problem. What’s nice about cyber-education is that you’re always working with edge cases, so looking at emerging technologies feels (relatively) comfortable.

In 2023, a year into my secondment, I was looking into the next big thing when quantum computing popped into my news stream. A bit of research showed the only program actively doing quantum education in Canada was UBC’s Geering Up engineering outreach, so I dug up an email and cold called them!

the idea for a quantum boot camp at UBC summer of 2023.

Ella: I wanted to give Tim and two other collaborators an opportunity to dive headfirst into quantum learning. I organized a 2-day crash course with PhD students, researchers, and a tour of D Wave Systems, a Burnaby-based quantum computing company. We had an awesome time diving into game design, quantum concepts, and left really inspired to continue working together.

Tim: The week at UBC was wonderful. Ella said finding post-secondary researchers was easy because they were all gamers and the thought of a quantum game resonated with them. By the end of the week my head was buzzing with possibilities. The other collaborators wanted to pitch a big game concept and go for lots of funding but being a pragmatic teacher, I was stuck on the idea of small, easy to access, engaging games that might even be simple enough for my gamedev class to build.

The other thing that happened was Ella invited the Quantum Algorithms Institute in for one of the meetings and I hit it off with the CEO. At the end of the week my family and I went up to Whistler in the mountains for the weekend and she happened to live out that way. We had a cup of tea together and asked if I’d like to extend my secondment with QAI. This amped up my quantum engagement and eventually led to presenting research on quantum disruption to cyber systems in Africa, Mexico, and across Canada. It also had me building a Q-Day cyber-range, designing curriculum to engage cyber professionals with the coming encryption challenges and connecting with many quantum groups – one of which was the Unitary Foundation. When the opportunity came up to pitch the Quantum Arcade idea Ella and I had been batting around for months with UF, I took it!

Q2048 development and standing up the arcade.

Ella: In a small lull in our curriculum development cycle, I asked my staff if there were any professional development or passion projects they wanted to take on. Harshinee, a PhD candidate in computer science and a developer on my team, asked if she could explore game development through a quantum lens. She had experience building 2048 due to her previous work in serious games and wanted to put new spins on it. It was the perfect time to contact Tim again and reignite all the ideas we had for an online quantum game hub.

Tim: I’d always wanted to make the arcade an opportunity for student game developers to share their love of gaming through a quantum lens, but I also knew (from Ella’s diversifying quantum talent program) that there were lots of orphaned quantum games out there. They’d get funded and put online until the money ran out then end up (if they were lucky) sitting on a USB key in a forgotten drawer.

I’d come across hints of ‘Quantum Cats’ from University of Waterloo’s Quantum Computing Institute but couldn’t find it. Ella put me in touch with John Donahue there and he happened to have a copy on a USB in his desk! A quick chat later the Quantum Arcade went from one to two games, and then a third when Ella dug up one of her orphaned games from the previous diversifying talent project.

In summer of 2025, I was in Ottawa at Good Shepherd School, and we were trying some early quantum awareness education with grade fives. One of the students was a gifted programmer already and was keen to consider a quantum game. For an activity I had the students put together a pitch for a quantum themed Scratch game. The class was right into it, so I emailed Ella afterwards wondering if we might not do what I’d hoped for all along and encourage students to make quantum-themed games – we could publish the top ones on the Arcade!

what the game jam is all about.

Ella: We are diving headfirst into a National Game Jam in partnership with KnowledgeFlow. Games developed by grade 6-12 students featuring quantum mechanics as part of their gameplay, story, or mechanics are all welcome! Scratch, Unity, or other frameworks are all encouraged so that students can play to their strengths and design their dream games. Submissions are open until December 20th, 2025. Find out more about it here: https://knowledgeflow.org/initiative/ubcs-year-of-quantum-arcade-game-jam/

Tim: There are many challenges with the Quantum Arcade Student Game Jam. One is that most teachers have no idea that it’s the hundredth anniversary of quantum mechanics. The next is that quantum is always said to be the next big thing instead of something we’ve been building technology out of for most of the 20th Century. The last challenge is that despite gaming being the predominant medium for anyone under forty, almost no one teaches how to build them in schools – even the basic coding skills needed are thin on the ground in Canada.

We’ve ploughed ahead anyway because there are a few brave teachers who are willing to dive into this deep end with us and explore a subject most people are oblivious to using technological skillsets almost no one teaches. Out on the edge like this is never going to be an easy sell, but that’s why it’s so important that we do it.

looking to the future.

Ella: Teaching with the quantum arcade is a dream come true. We are constantly finding new ways to use the games in programming, and being inspired to create more and more new games to match demand. Hearing the kids ask great questions, coach each other, and celebrate wins is exactly why we built the arcade. In future years, we are aiming to build sustainable momentum and ideally have the arcade grow into a self-sustaining, vibrant hub for quantum education.

Tim: My hope is that in five years the Quantum Arcade is an established entity with dozens of games and regular opportunities for students both in K12 and post-secondary, to build games that allow everyone to play with quantum concepts and demystify the technology that surrounds us. At the moment I’m noodling something similar to the old Lemmings game where the player directs electrons through transistors of various types after writing a piece on it last month.

about the micrograntees.

Ella Meyer is the Quantum Computing Outreach Coordinator at UBC Geering Up and the Project Manager for the Diversifying Talent in Emerging Technologies Program. She graduated with a B.Sc. in Astronomy from the University of British Columbia in 2020 and still lives in Vancouver, BC, Canada. Ella has been working in science education and communication for over four years in partnership with industry and academics worldwide!

A pioneering cyber-educator in Canada, Timothy King was the first teacher in the country to become cyber operations instructor qualified, and the first with MITx's Quantum Computing certification. Winner of the Cisco Networking Academy alumni innovator and shooting star awards in 2023 and 2024 International Security Journal global leadership award winner for mentorship, Timothy has presented research on emerging technology in the cyber domain around the world, and is diligently trying to raise the quality of cyber-education in Canada.

Mozilla Foundation joins UF to Further Open-Source Mission

Mon, 17 Nov 2025 00:00:00 GMT

Dear UF Community,

We are delighted to share a significant milestone for the Unitary Foundation: Mozilla Foundation has officially become a Supporting Member of our organization.

This partnership is a powerful convergence of missions. Mozilla Foundation has spent decades championing openness, accessibility, and ethical design on the internet. Now, they are extending those core values to the foundational layer of quantum computing by supporting our efforts to build a public-interest quantum ecosystem.

The alignment here is clear: just as the internet must be a public resource, the future of quantum must be built on open, trustworthy grounding. Mozilla Foundation's standing and experience will be indispensable as we work together to ensure quantum computing benefits the greatest number of people.

</br> <div class="flex flex-col items-center space-y-10">

<blockquote class="w-2/3 self-start italic"> “Mozilla Foundation is a pioneer in demonstrating how open-source principles and community-driven governance can lead to world-changing technology," said <strong>Will Zeng, UF President and CEO.</strong> "We are thrilled to partner with them as we scale our work in open-source quantum software, research, and community support. The quantum ecosystem needs to be built on open foundations from day one, and the Foundation's expertise will be crucial in that mission.” </blockquote>

<blockquote class="w-2/3 self-end italic"> “Quantum technologies will define the next era of computing, and the principles behind them will shape the world,” said <strong>Ziyaad Bhorat, Senior Advisor at Mozilla Foundation.</strong> “Partnering with the Unitary Foundation reflects our shared belief that openness must be built in from the start. The future belongs to those who imagine and build it together, and our collaboration is a commitment to ensuring emerging technologies remain rooted in human values. That’s what open source truly means.” </blockquote>

</div>

</br>

In addition to welcoming them to the membership program, Unitary Foundation is thrilled to be partnering with Mozilla Foundation to host a 2026 Open Source Fellow to help advance the quantum OSE. You can learn more about the fellowship and nominate a colleague (or yourself!) here. Deadline to submit nominations is January 30, 2026.

We look forward to a dynamic collaboration and the powerful results it will yield for the entire quantum ecosystem. Thank you, Mozilla Foundation, for joining our community!

With gratitude and excitement, </br> The UF Team

2025 Quantum Open Source Software Survey Results

Mon, 03 Nov 2025 00:00:00 GMT

Dear community members,

Unitary Foundation is happy to share the results of this year’s Quantum Open Source Survey! Now in its fourth iteration, the survey is meant to serve as a snapshot of our community to provide illuminating and actionable insights as we look to develop a quantum ecosystem that is the most useful to the most people.

Topics covered include Demographics, Experience, Cloud Services, Full-Stack Development Platforms, Compilers and Simulators, Software for Applications and Tools, User Experience, OSS Development and Research, and Community.

Thank you to you all for your input, answers, and participation! We continue to be amazed at the tools being developed all the time that push the science forward in ways both big and small. A special thank you as well to our supporting and core members, for their guidance, thought leadership, and ongoing support of Unitary Foundation and the open source ecosystem.

Read the full survey results here. We've provided some insights below and look forward to hearing what you think as well! Write to us at info(at)unitary(dot)foundation with any questions or comments.

Warmly, </br> The UF Team

📊 Demographics

This year's survey revealed several fascinating shifts within the quantum community. In terms of Roles, the profile of the respondents remained largely consistent, with one key exception: the number of self-identified hobbyists has now surpassed educators, a key role for any open source ecosystem, and one we continue to strive to cultivate.

For Background, we observed an increase in classical software professionals entering the field, while the percentage of dedicated researchers saw a slight decrease.

The community is overwhelmingly young. The largest age group is 21-25 (32.8%), and over half of all respondents (53.6%) are aged 30 or younger. This indicates a strong pipeline of early-career professionals and students entering the field, suggesting sustained growth and high energy for new development and research.

The data on Affiliation and Pay shows mixed signals regarding the rise of the DIY quantum developer. The "No affiliation" response jumped significantly, from 7% to 11%, potentially indicating more individuals are working on open source quantum projects independently. Yet, more respondents (up from 53% to 56%) now report that this is their full-time job, not just a side project. An especially fascinating point is that nearly 40% of people working in the field do so without pay.

Finally, the Educational Background of respondents appears more evenly dispersed this year, with the percentage split between those holding Masters degrees and PhDs becoming closer compared to last year, which saw a higher percentage of PhDs.

⚙️ Full-stack development platforms, compilers, and simulators

We noted significant interest in up-and-coming and smaller packages. Here are the ones that jumped the most this year:

OpenQ: Grew from 1.1% to 7.7% in current/future usage.
Yao.jl: jumped from 1.3% to 7.9% in current/future usage.
UCC (Unitary Compiler Collection): Had the highest jump from 2% to 10% in current/future usage.

🛠️ Software for Applications and Tools

This year saw the addition of a dedicated section to Quantum Error Correction (QEC) Software. It's encouraging to see such an even split between people already using QEC software and those interested in trying it, and we encourage you to take a further look at the data to find out more

🔬 Open Source Software (OSS) Development & Research

When respondents were asked about the type of quantum computing research they perform, compilation (infrastructure) emerged as the third most popular area. The top three areas are Algorithms, Applications, and Compilation. This confirms a community-wide recognition that building efficient tools and the quantum software stack is just as critical as developing new algorithms or applications.

Regarding the areas of quantum computing believed to be the most promising for future research, there were a few significant drops from 2024 to 2025:

Hardware Development: While 34% of respondents believed it was the most promising in 2024, only 27% believe this to be true in 2025.
Error Mitigation: While 28% of respondents believed it was the most promising in 2024, only 23% believe this to be true in 2025.
Algorithm development, Error Correction, and Application development continue to be considered the most promising!

It’s encouraging to see high interest in respondents wanting to co-author a research paper based on work with open-source software. Unitary Foundation will look to encourage new engagement around this topic in the coming year.

Finally, the data on Programming languages the respondents would like to learn was unambiguous: Everyone wants to learn Rust!

💬 Community

We are thrilled that nearly 95% of respondents reported a positive experience with the quantum OSE! As always Unitary Foundation will strive to increase this number and ensure the ecosystem is providing the right resources to its community.

This year, there continued to be a relatively even spread of resources the community looks to use to learn or contribute to the OSE, however, video resources surpassed hackathons as the number one method for engagement assistance.

When asked about the Source of answers or information when developing quantum software, we are encouraged that project documentation and source code remain higher-ranked than chatbots. This confirms that having good docs and readable code still matters most to developers.

In the open-ended feedback section, the top two categories of responses were: Learning, Mentorship & Training (e.g., requests for structured learning, workshops, tutorials) and Collaboration & Community Building (e.g., importance of inclusivity and support for newcomers). This suggests that the community is actively calling for more formalized educational pathways and stronger structural support to welcome and onboard new members.

Read the full results!

From Micrograntees to Members: Announcing OrangeQS as UF’s Newest Supporting Member!

Fri, 17 Oct 2025 00:00:00 GMT

We are beyond ecstatic to announce that OrangeQS has joined Unitary Foundation as a Supporting Member! Based in the Netherlands, OrangeQS builds products for fast and reliable testing of quantum chips.

This collaboration is especially meaningful because two of the OrangeQS founders, Adriaan Rol and Amber Van Hauwermeiren, began their involvement with us as Unitary Foundation micrograntees in 2021 for Quantify—less than a year after OrangeQS was founded! Since then, various members of their team have continued to participate in and support the UF community in multiple ways, including serving as maintainers during unitaryHACK and as speakers at unitaryCON.

This support comes in the midst of OrangeQS’ newest open-source project OrangeQS Juice. OrangeQS Juice is a Linux-based open-source operating system specifically engineered for quantum R&D labs. Juice operates by running a JupyterHub instance directly on the lab’s control computer, which hosts multiple shared Python kernels. Juice is currently in a closed beta phase at AQT Berkeley, QuTech and Chalmers Next Labs and will be made open-source soon!

For more information join the OrangeQS Juice channel on the UF Discord and check out orangeqsjuice.org.

"Adriaan and Amber were in an early cohort of our microgrant winners back in 2021. Their work growing for them and OrangeQS to become UF Members illustrates just what we would hope for in our community programs. The OrangeQS Team has already been a dedicated supporter of the Unitary Foundation community for years through initiatives like unitaryHACK and unitaryCON, and, on behalf of our community, we are grateful for their increased support." - Will Zeng, President, Unitary Foundation

“We’re excited to support the vibrant UF community. Since the very beginning we have enjoyed working with the Unitary Foundation, receiving a micro-grant together with Qblox to develop Quantify and joining the unitaryHACK. Now we’re proud to introduce an open-source operating system for quantum R&D labs that we hope will be further developed together with the community. Looking forward to engaging with the best open-source quantum software community out there! - Amber Van Hauwermeiren, Co-founder & Branding Lead, Orange Quantum Systems

2025 Q3 Updates: unitaryCON Recap, Merit Systems Collaboration, and Final Days to Take the QOSS Survey!

Thu, 02 Oct 2025 00:00:00 GMT

Dear Unitary Foundation community,

It's officially Fall in the US, and the UF team is celebrating by looking back at all of our accomplishments during Q3 2025!

On September 2-4, we gathered our community in Albuqurque, New Mexico, for our annual unitaryCON conference. This year's unitaryCON was co-located with IEEE Quantum Week, allowing our community to grow as well as connect to a larger network. You can read a full recap here.

In July, we also held the UF Staff retreat and WERQSHOP, our newest workshop on Quantum Error Resilience (you can check out blog post for an informal summary of the event, and our technical report for the key takeaways on the future of error mitigation). Below are a few photos of all of our summer in-person adventures!

During unitaryCON we also announced a very exciting collaboration with Merit Systems, a payment service platform designed to help reward open-source contributors. Our aim is to use the Merit System platform to pay community members who contribute to our projects, starting with UCC and Mitiq. You can read more about this opportunity and how to get involved here.

Finally, if you haven't heard, the 2025 Quantum Open Source Software Survey is still open! We've extended the deadline from this Friday to this Sunday, October 5th. If you haven't already, we hope you consider contributing and sharing with your open source networks. The Survey is a cornerstone of our work at UF and plays a large part in informing our community of what its current needs and challenges are.

Read more about our other news below and make sure you're subscribed to our newsletter, LinkedIn, and Bluesky if you don't want to miss any UF news!

Warmly,<br> The UF Team

New from Unitary Foundation

Mitiq

0.46.0 and 0.47.0 releases
- Across the last two releases, Mitiq has added new functionality for error mitigation workflows including support for custom calibration circuits, new visualization tools for comparing ZNE fits, and a full implementation of Probabilistic Error Amplification (PEA). Alongside these, there are improvements to documentation, tutorials showing how to combine multiple QEM techniques, and utilities like compare_cost to better track resource overhead.

Metriq

Metriq-gym (now licensed under GPL-3) saw steady growth with three releases (0.2.0–0.4.0):
- Introduced benchmark suites
- LR-QAOA benchmark by micrograntee Alejandro Montanez Barrera
- Integration with Quantinuum Nexus
- Automated result uploads to GitHub data repository
- Easier onboarding with dedicated docs at metriq-gym.readthedocs.io
Collaborated with Neer Patel, Tom Lubinski, and Siyuan Niu from QED-C (The Quantum Economic Development Consortium) for experimenting with application-based benchmarks in metriq-gym.
Designed a new pipeline to share metriq-gym results with the community (stay tuned for a redesigned metriq.info!)

UCC

Launched weekly public community calls on Discord
New versions released:
- V0.4.8 [July 2025]: In v0.4.8, we updated documentation based on user feedback, improved infrastructure for automated releases and CI/CD, and bumped dependencies. For UCC-bench, we added new observables for simulation benchmarks and in UCC-FT added new QEC benchmarks.
- V0.4.9 [August 2025]: Version 0.4.9 optimizes target gate selection for hardware devices, introduces code test coverage reporting, bumps dependencies, and introduces Merit systems issue tagging for external contributors.

Other UF-Supported Projects

QuTiP was featured on the AWS technical blog. You can read more here!
UF supported the launch of the Jeff quantum exchange format.

Conferences + Events We Attended in Q3

Nate Stemen served on the organizing committee of the Quantum Software 2.1 Workshop at IEEE Quantum Week 2025 alongside colleagues at Xanadu, ORNL, and more
Jordan Sullivan presented a UCC lightning talk and compilation panel during the Quantum Software 2.1 Workshop (linked above)
Brad Chase and Jordan Sullivan presented talks on UCC and UCC-FT at the International Workshop for Quantum Compilation(IWQC)
Changhao Li presented metriq-gym in NYC Quantum Computing Meetup, IEEE QCE in New Mexico, and at Sandia National Labs' APQC 2025 Workshop in Colorado
Ben Castanon presented Unitary Foundation's work at Quantum World Congress in DC last month
Veena Vijayakumar spoke about quantum education and worksforce developmenton during a virtual panel hosted by the National Communication Museum in Australia

Q3 Grants

To Maria Gragera Garces for HDH: Hybrid Dependency Hypergraphs for Distributing model agnostic quantum workloads. During this project period, the grantee will develop a consistent framework for the HDH library in order to release a complete and stable v1.0. The HDH library introduces a novel intermediate representation for distributing quantum workloads across heterogeneous quantum networks. Learn more on their Github Repo here
To Jop Briët, Arjan Cornelissen, Francisco Escudero Gutiérrez, and Sander Gribling for designing quantum query algorithms on a laptop. This is a project to develop a software tool capable of generating optimal quantum query algorithms for approximating Boolean functions. The core of this project involves the implementation of semidefinite programs derived from two central methods in quantum query complexity: the adversary method and the (completely bounded) polynomial method.
To Benny Zong Liu and Ilan Iwumbwe for QuteFuzz, a solution for detecting potentially semantic changing bugs in quantum compilers, weeding out simple but critical errors that can be very time consuming to detect conventionally.
To Seun Omonije for Qernel, an agentic command line interface (CLI) to prototype and share quantum code.

Micrograntee Updates

From Timothy King and Ella Meyer: the Quantum Arcade project is entering into a new phase: the Quantum Arcade Student Game Jam! Read more through Timothy’s post here.
From Maxime Garnier and Thierry Martinez: the UF-Funded Graphix workshop came to a close last month. Read more about their work in Maxime’s post here. And check out the team’s github repo here.
From Stephen DiAdamo: At Qoro, we recently open-sourced our application library called Divi, designed for generating batch jobs for quantum programs using parallelization techniques. It comes with a lot of built in tools to make it easy to add things like error mitigation and observable grouping. It allows users to simulate beyond 20 qubits in applications like QAOA by using partitioning. We're always looking for more users to see how they find using Divi, so we can improve on it. We'd be happy if they try it out and also join our Slack community.
From Davide Gessa: The new stable release of Qlasskit tagged as version v0.1.36 is now available. It now fully works with python >= 3.13.
From Alejandro Montañez-Barrera: From Sept 22-25, I attended the APQC (Assessing Performance of Quantum Computers) 2025 workshop as an invited speaker, presenting the LR-QAOA Benchmarking. The title of my talk was "Evaluating the performance of quantum processing units at large width and depth." I described the benchmark and mentioned that this is available for users in metriq-gym. Also, to mention that the LR-QAOA benchmarking is available in metriq-gym and with a digestible description at https://quantumbenchmarkzoo.org/
From Eduardo Maschio: H-hat working version roadmap was announced at https://github.com/hhat-lang/hhat_lang/discussions/72 and https://github.com/hhat-lang/hhat_lang/discussions/74, and it's to be released by January 2026. H-hat will also be presented at Munich Quantum Software Forum software pitches on October 20th-21st.
From Seun Omonije: The alpha release (0.1.0-alpha1) of the Qernel CLI, an agentic CLI to prototype and share quantum code, is out now at https://github.com/computabeast/qernel. This is the first step of a project that aims to automate the conversion quantum computing research into runnable programs, and feedback on the project is requested! Tutorial videos and examples are on the way.

Other News from the Community

Riverlane announced the release of Deltakit, their toolkit for QEC. The Deltakit SDK is now open-source under the Apache 2.0 license. You can explore the source code and start contributing on GitHub: https://github.com/deltakit/deltakit.
In mid-September, the Quantum Women's Network gathered for their inaugural event in NYC. Read more about the event, the mission of the QWN, and how you can get involved here (their next event is coming up at the end of October!).

Coming up

Stay tuned for the the results of the 2025 QOSS Survey!
Stay up-to-date on all things UF and Quantum Open Source Computing by following us on our communication channels:

WERQSHOP 2025 Technical Report

Thu, 02 Oct 2025 00:00:00 GMT

Following the energy of Operating at the edge of failure: WERQSHOP 2025 Recap, we took the time to further distill the themes of the talks, breakouts, and discussions into one place.

The full WERQSHOP 2025 Technical Report captures speaker summaries, discussion highlights, and the threads the community wants to pull next. Give it a read, share it, and let us know what else would help you keep the conversation going.

Abstract:

The 2025 Workshop on Error Resilience in Quantum computing (WERQSHOP) brought together 60 researchers, software developers, and practitioners across the field of quantum computing to critically assess the role of quantum error mitigation (QEM) as quantum devices enter the early fault-tolerant era. With presentations spanning limitations, experimental breakthroughs, and emerging QEM-QEC hybrid strategies, the event highlighted the lack of general-purpose solutions, the promise of tailored mitigation techniques, and the growing importance of open infrastructure to support research. This report synthesizes key insights, challenges, and forward-looking recommendations from two days of talks, panels, and discussions.

See a spelling mistake or want to correct a misconception in the report? Open a PR to edit the LaTeX on the werq.shop repo.

A Recap on unitaryCON 2025

Tue, 30 Sep 2025 00:00:00 GMT

Dear UF Community,

unitaryCON 2025 was a massive success! From September 2–4, 2025, we brought close to 100 Unitary Foundation community members together—members, advisors, current and former micrograntees, staff, and collaborators—for our annual, high-energy gathering dedicated to pushing the Quantum Open Source Software (QOSS) ecosystem forward.

Hosted in Albuquerque, New Mexico, and running alongside IEEE Quantum Week, this year's event was a critical forum for sharing progress and mapping out our future strategy. The agenda was packed with great content: insightful intro talks, technical deep-dives from featured speakers, hands-on breakout sessions, and participant-driven 'unconference' discussions. If you’d like to see the full schedule and talk abstracts, be sure to check out the unitaryCON 2025 webpage here.

The key focus? Building robust, platform-agnostic tools. We spent a lot of time tackling challenges in quantum compilation, error correction (QEC) toolkits, and standardized SDKs, all with the goal of making quantum programs easier to access, verify, and run efficiently on any hardware. unitaryCON reinforced the idea that open standards and community collaboration are the fastest way to get to the quantum future.

Group selfie during the conference

Tuesday, September 2nd (Day 0)

On Tuesday night, we gathered at the Smoky Note in the Nob Hill neighborhood of Albuquerque to welcome all attendees. IEEE Week has tons of activities for attendees, and it was great to connect with many micrograntees, maintainers, partners and friends before the workshop sessions kicked off.

Photos during the welcome event

I must say that this is my favorite conference, and it's because I share the passion of others for open-source quantum software. So meeting each year with them and seeing the amazing projects they are bringing to the community is special.

Wednesday, September 3rd (Day 1)

Welcome Talks

Our first official day of unitaryCON was focused on project updates and presentations from both emerging professionals and veterans within the field. The day started with short welcome talks from UF President Will Zeng and unitaryCON Co-Director Veena Vijayakumar.

UF welcomes were followed by welcomes from colleagues in the local (Mountain West) Quantum ecosystem including Dr. Ivan Deutsch from University of New Mexico and Jake Douglass from Sandia National Labs and Elevate Quantum. Both Ivan and Jake did a wonderful job of painting a portrait of the extensive research and collaborative work being done across institutions in the Mountain West.

Intro Speakers from left to right: Veena Vijayakumar, Dr. Will Zeng, Dr. Ivan Deutsch, and Jake Douglass

Featured Talks

The day continued with 5 featured speakers who have been making strides in industry. Dr. Lukas Burgholzer from TUM & MQSC presented the newest developments with the Munich Quantum toolkit, particularly MQT Bench, their open-source benchmarking framework. Tom Hartley from Riverlane introduced (and shared a private beta of) Deltakit, Riverlane’s newest Python library for QEC researchers that makes it easy to run QEC experiments in simulation and real hardware using Stim. Ryan Hill from qBraid demonstrated the newest updates and the benefits of the platform agnostic qBraid-SDK. Kai-Hsin Wu from QuEra introduced Bloqade, an open-source Python SDK designed for programming neutral atom quantum computers. And finally Dr. Luciano Bello from IBM presented the newest updates to Qiskit 2.x and shared all of the community initiatives (both new and old) that IBM has been fostering.

To read more in-depth abstracts for each featured talk, check out the unitaryCON webpage.

Featured Talk Speakers from left to right: Dr. Lukas Burgholzer, Tom Hartley, Ryan Hill, Kai-Hsin Wu, and Dr. Luciano Bello

Lighting Talks

After a short break following the Featured Talks, we had 10 community members come up and share their project updates. These speakers submitted to a Call for Proposals that UF put out in early August and were chosen from 30+ submissions. The speakers were Dr. Lia Yeh (“ZXLive: drag-and-drop to draw and apply ZX-calculus”); Catalina Albornoz (“The Quantum Compilation hub: centralizing the scattered knowledge on quantum compilation”); Zefan Du (“CCMap: Lightweight Compiler Integration for Chiplet-Based Modular Quantum Systems”); Dr. Christa Zoufal (“Quantum Optimization Benchmarking Library — The Intractable Decathlon”); Dr. Tim Chen (“Intrinsic error mitigation in quantum-classical auxiliary-field quantum Monte Carlo”); Marlo Kuerner (“OrangeQS Juice: an open-source OS powering Quantum Experiments and Innovation”); Gennadi Ryan (“ pypiccolo, a novel julia-based python package for robotics-inspired quantum optimal control”); Dr. Elaine Wong (“Some progress on QIR-EE: A Cross-Platform Execution Engine for QIR”); Dr. Jiaqi Leng (“Quantum Advantage for Nonlinear Optimization: Theory and Open-Source Software”); and Ed Younis (“OpenQudit: Extensible and Accelerated Numerical Quantum Compilation by JIT-Compiling a Qudit Gate DSL”).

To read more in-depth abstracts for each lightning talk, check out the unitaryCON webpage.

The day ended with an hour of open networking and the group slowly made its way back into the IEEE programming afterwards.

The featured talks and the lightning talks were by far the best talks I attended at IEEE Quantum Week, and the UNM excursion was fascinating.

The open networking sessions were great for [meeting others]. This has led to some future collaboration projects that are already in the works!

Attendees during the open networking session at the end of Day 1

Thursday, September 4th (Day 2)

Unconference Sessions

Day 2 of unitaryCON was focused on group discussion and brainstorming. There were two parts of unconference sessions led by UF staff, collaborators, micrograntees, and ambassadors. The topics and leaders were as follows:

Part 1
- Quantum Education led by Monica VanDieren
- Benchmarking led by Alejandro Montanez
- Error Correction led by Abraham Asfaw
- Compilation led by Jordan Sullivan + Nate Stemen
Part 2
- Quantum Education led by Alberto Maldonado Romo
- Open Source Software led by Shangjie Guo
- Error Mitigation led by Nate Stemen

Attendees walked away with potential strategies to incorporate into their own work in all of the discussion areas.

Unconference Session Conversations and Notes

Group Excursion to University of New Mexico

The day (and conference) ended with a group excursion to University of New Mexico’s Physics campus. Professors Ivan Deutsch and Francisco Becerra showed the group around the research building and attendees were able to see the school’s research labs and other facilities that are offered as resources to students, staff, and faculty.

This excursion was a special opportunity for unitaryCON attendees to see what sorts of activities are happening in the area. The UNM campus was beautiful and the faculty and staff were all extremely knowledgeable. We are so grateful to the UNM team, particularly Dr. Ivan Deutsch and Dr. Bob Ledoux, for helping us make this happen!

Photos from the tour at University of New Mexico

Thank you for organizing! I really appreciate it and am thankful for the experience, especially to finally meet people with a common cause and interest.

Final Takeaways and Thank Yous

Our third edition of unitaryCON provided a safe and engaging space to discuss both the opportunities and challenges open source developers are facing in our field today. We continue to strive to create a workshop that offers something for senior researchers to curious newcomers, and a platform where all voices can be elevated and anyone can be a new collaborator. We are proud to continue to prioritize learning, accessibility, and advancing an emerging field openly and equitably. These were a special three days filled with collaboration and connection that we won’t be forgetting any time soon!

A quick thank you to all of our collaborators and sponsors who made this year’s unitaryCON possible:

The Event Sponsors: University of New Mexico, QNMi, and Classiq
UF Core Members: IBM Quantum, DoraHacks, Open Quantum Design
UF Supporting Members: AWS, Microsoft, QC Ware, Quantum Machines, Riverlane, SandboxAQ
And last but absolutely not least OUR COMMUNITY MEMBERS. Thank you for joining us and making unitaryCON 2025 so special!

Getting paid for your open-source quantum work with Merit Systems

Thu, 04 Sep 2025 00:00:00 GMT

A critical gap in open source...

Open-source software powers all of the most widely used tech tools we rely on, from web protocols to the Linux kernel -- and incredibly, most of the people who write it do so on a volunteer basis.

Our mission at Unitary Foundation is to help grow a quantum OS ecosysytem that benefits the most people. To this end, we are dedicated to compensating and recognizing individuals for their work in this field, like with our microgrant program and annual unitaryHACK hackathon -- with record participation this year with 172 GitHub issue bounties closed and $19,710 earned by 78 hackers. Spurred on by this success, we were looking for a way to extend the issue bounty program into the rest of the year.

Introducing Unitary Foundation x Merit Systems

That's why we're partnering with Merit Systems, a payment service platform designed to help reward open-source contributors. It interfaces with your GitHub account and makes the process of getting paid straightforward in a wide array of countries.

What does that mean for our work at Unitary Foundation? Well, to start off we are piloting Merit in two of our open-source software projects: mitiq and ucc, where we'll be using Merit in slightly different ways:

Mitiq - rolling release payments

If you're not already familiar, mitiq is a toolkit for applying quantum error mitigation. We plan to distribute $1,000 per release to non-Unitary Foundation contributors. The amount will be distributed according to Merit's default attribution algorithm, which rewards more substantial contributions more heavily. Don't worry though, the distribution will be audited by myself (nate) along with other maintainers and we will do our best to ensure fair distribution. If the algorithm doesn't catch that a PR was as crucial as it was, we can make the changes necessary to ensure that is reflected.

This method means you can get paid for your contributions, no matter how small![^1]

[^1]: Small contributions do mean smaller payout, but it's something!

UCC - "pass of the month" bounty

ucc stands for Unitary Compiler Collection, a set of tools for quantum compilation. We will be using Merit bounties to reward folks for implementing new, performant compiler passes in the repo: this can be be one of our existing issues with the merit-bounty tag, or a new compiler pass that you propose!

We plan to award between $250-$500 per month to the strongest contributions[^2] to UCC's compiler passes. [^2]: If we get multiple strong UCC contributions in a particular month, we may award more than one bounty!

Get involved

The next few months will be a trial phase for us using Merit, so our distribution mechanisms may change, but we certainly remain adamant about rewarding open-source contributions. To take the first step, make sure your GitHub account is connected to Merit so you can claim your payments Let's get you paid!

GitHub repo	Documentation	Merit Terminal
`unitaryfoundation/mitiq`	`mitiq.readthedocs.io`	mitiq on Merit
`unitaryfoundation/ucc`	`ucc.readthedocs.io`	ucc on Merit

The 2025 QOSS Survey is Open!

Wed, 03 Sep 2025 00:00:00 GMT

It's that time of year again: the Quantum Open Source Software survey is now open! This annual survey is a chance for anyone in quantum technology to share their voice and help create an informative and representative snapshot of the community and field. The survey includes questions ranging from demographics to research, tools, platforms, and more.

If you are a user or developer of software for any kind of quantum technology, we kindly encourage you to take this ~10 minute survey. The QOSS survey will be open through Friday, October 3rd, 2025. We appreciate you taking the time to fill it out!

Are you ready to take the survey? Click here to get started! <a href="https://www.surveymonkey.com/r/QOSSSurvey25" target="_blank"><img src="/images/2025_QOSS.png"></a>

All anonymized results will be shared publicly so the survey can serve as a resource for anyone who wants a better understanding of the quantum tech community’s needs. Unitary Foundation will also analyze the data, report our findings, and publish the aggregated results on our website.

A very special thanks to the Unitary Foundation members, advisors, and partners who continue to help us provide this survey as a resource, including work in designing, testing, and providing general feedback.

Fill out the QOSS Survey

ucc-ft: Verifying Fault-Tolerance in Quantum Circuits

Wed, 20 Aug 2025 00:00:00 GMT

The Critical Need for Fault-Tolerance

As we build larger and more powerful quantum computers, we face a fundamental obstacle: noise. Qubits, are incredibly sensitive to their environment, which can introduce errors that corrupt our computations. The leading strategy to combat this is Quantum Error Correction (QEC), which uses redundant qubits to encode and protect logical information.

However, QEC introduces a new challenge: the very circuits that perform the error correction must themselves be fault-tolerant. This means they can't introduce or spread more errors than the code can handle. Manually proving that a circuit is fault-tolerant is a painstaking and error-prone process, especially for the complex codes needed for large-scale quantum computers.

Recently, researchers developed a powerful technique using formal verification to automatically prove whether a quantum circuit is fault-tolerant [^1]. This method uses symbolic execution to analyze all possible error propagation paths, providing a rigorous guarantee of a circuit's fault tolerance. The authors also released a Julia language implementation of the technique, and demonstrate it's performance on a variety of codes.

ucc-ft builds on this foundation to make these sophisticated verification techniques accessible to the entire quantum community. By providing a user-friendly Python interface and accepting standard circuit formats like OpenQASM3, ucc-ft bridges the gap between cutting-edge research and practical application. ucc-ft is part of the Unitary Compiler Collection (UCC), a broader initiative to build a modular, open-source, and community-driven quantum compiler stack. You can read more about UCC in the launch announcement blogpost.

How it Works: An Example

So, what does ucc-ft look like in action? Let's take a common task: preparing a Quantum cat state, a fundamental building block in many quantum algorithms and error correction gadgets. Although itself a quantum error correcting code, we can still consider how well it tolerates errors. A standard approach is to prepare the state and then run a check, repeating the process if the check fails. However, a subtle bug in the checking part of the circuit can allow errors to go undetected.

Consider the faulty cat state preparation circuit shown below (figure from [^1]). An error at a specific point (marked with an X) can propagate in a way that the parity check fails to catch.

Using ucc-ft, we can automatically detect this flaw. The tool takes the stabilizer definition of the desired state and the circuit implementation in OpenQASM3 and checks if it meets the fault-tolerance criteria.

Here's a code snippet showing how you would use ucc-ft to find the bug:

from ucc_ft.codes import CatStateStabilizer
from ucc_ft.checker import ft_check

# Define the stabilizer code for the cat state
code = CatStateStabilizer(num_qubits=4, max_faults=2)

# The circuit implementation in OpenQASM
circuit = """
OPENQASM 3.0;
include "stdgates.inc";
const uint size = 4;
qubit[size] state;
qubit ancilla;

def cat_prep() {
    bit res = 1;
    while(res != 0) {
        reset state[0];
        h state[0];
        for int i in [1:(size-1)] {
            reset state[i];
            cx state[0], state[i];
        }

        // Parity check
        reset ancilla;
        cx state[1], ancilla;
        cx state[2], ancilla;
        res = measure ancilla;
    }
}
"""

# Run the fault-tolerance check
result = ft_check(code, circuit, "cat_prep", "prepare", num_ancilla=1)

# The tool identifies the fault!
print(result)
# Prints:
#  Circuit is not fault-tolerant. Fault-tolerant error locations:
#  [Line  15] X-Pauli error on qubit 0 after CNOT(qubit 0,qubit 2)

As you can see, ucc-ft not only tells us that the circuit is not fault-tolerant but also pinpoints the exact location and type of error that causes the failure. Notice the use of complex control flow and looping supported by QASM3. This level of automated, precise feedback is invaluable for designing and debugging robust quantum circuits.

What's Next?

The journey for ucc-ft is just beginning; it's really at a proof of concept phase today. We are interested in exploring

Support for alternative definitions of fault-tolerance and different error models, such as those including correlated noise, to better reflect physical realities.
Integration with other error correction tools like Stim and Crumble to create a more seamless workflow from code definition to verification and visualization.
Automating synthesis and discovery of new, optimized, and provably fault-tolerant gadgets in a feedback loop with the checker.
Performance improvements and a library of pre-validated sub-circuits to enable validating larger codes

Get Involved

ucc-ft is an open-source project and we'd love your input! Whether you're a researcher designing new QEC codes, a developer building compilers, or simply passionate about reliable quantum computing, we welcome your contributions and feedback. Please check out the repository unitaryfoundation/ucc-ft, or join us on #ucc channel the Unitary Foundation Discord to discuss the future of fault-tolerant quantum computing!

Acknowledgements

Huge thank you to Kean Chen and Gushu Li for their fantastic research work, Julia implementation, and willingness to answer questions and support prototyping this tool.

[^1]: Chen K, Liu Y, Fang W, Paykin J, Wu X-C, Schmitz A, Zdancewic S, Li G (2025) Verifying Fault-Tolerance of Quantum Error Correction Codes. https://doi.org/10.48550/arXiv.2501.14380

Inaugural Quantum Device Workshop!

Fri, 15 Aug 2025 00:00:00 GMT

<em> This is a guest post by the Quantum Computing Student Association at UCLA. Unitary Foundation is proud to have been a sponsor of the event.

</em>

The Quantum Computing Student Association ignited the community this year with the launch of its first-ever Quantum Device Workshop—a four-day celebration of innovation, hands-on learning, and cutting-edge quantum hardware design. Drawing a vibrant mix of students, researchers, and industry professionals from around the world, the workshop delivered high-impact lectures, immersive technical sessions, and dynamic networking opportunities that showcased the rapidly growing excitement around open-source quantum engineering.

<p style="text-align:center;">Quantum Device Workshop Group Photo!</p>

So what exactly occured at this workshop? We will break down what occured day by day.

Day 1

The first day started off with attendees checking in and grabbing breakfast, followed by Professor Eli Levenson-Falk giving an overview and goals of the workshop. After that, the workshop was split into the two separate tracks, beginner and advanced. For the beginner track, Zlatko Minev from Google taught a two hour workshop on circuit quantum electrodynamics (cQED) and the basic principles behind designing a transmon qubit coupled to a resonator. After Zlatko's workshop, the beginner track had lunch. After lunch, Professor Devoret discussed how a superconducting qubit compares to atom based qubits. This was followed by a talk by Daniel Sank from Google who discussed how to do readout of a superconducting qubit. To cap off the day for the beginners, Professor Andreas Wallraff talked about the physics on how to couple two qubits for the purpose of preforming two qubit gates.

<p style="text-align:center;">Professor Eli Levenson-Falk giving the opening talk to a packed house!</p>

For the advanced track, Daniel Sank talked about how to optimize the design of readout resonators for superconducting qubits, issues with scaling up dispersive readout, and designing alternatives for dispersive readout that could be more scalable. This was followed by a workshop session by Ofer Naaman from Google on how to use Keysight ADS to design a Snake Parametric Amplifier. After Ofer's workshop, the advanced track had lunch. After lunch, we resumed with Professor Andreas Wallraff's talk about how to implement a surface code on superconducting quantum devices. During the talk, he also showed a image of a GDS file of chip designed for surface codes and allowed the participants to ask questions about the different circuit elements on the chip, which was very useful for the audience as these images are rarely shared in actual publications. After this, Professor Devoret taught the advanced track participants about constructing Hamiltonians and Lagrangians from a circuit diagram following a second quantization framework. To cap off the day for the advanced track, Zlatko Minev did a deep dive into the backend behind PyEPR and Qiskit Metal and discussed a little bit on optimal meshing conditions for electromagnetic simulation of superconducting qubit devices.

<p style="text-align:center;">Quantum Device Workshop Organizer Cody Fan helps Professor Devoret do a quick A/V check before his advanced track talk.</p>

After concluding the first day of workshop sessions and talks, many attendees went out to Santa Monica Brew Works for a Los Angeles Quantum Beers social with representatives from many companies present, such as HRL, Google Quantum AI, AWS Quantum, Phasecraft, and etc.

<p style="text-align:center;">Zlatko Minev takes a selfie during a busy Quantum Beers social!</p>

Day 2

On Tuesday, the beginner track kicked things off with a 3-part workshop from David and Lukas Pahl (who we affectionately refer to as the Pahl brothers) from MIT who discussed the ABCD matrix formalism for designing quantum circuits. This was followed by lunch, after which Professor Jens Koch taught the beginners track participants how to use the open source SCqubits package, which models cQED systems and superconducting quantum devices. To cap off the day for the beginners track, Murat can Sarihan from Google led a two hour workshop on electromagnetic simulation, EPR, and LOM analysis of superconducting devices.

For the advanced track, Professor Jens Koch kicked the day off with an advanced tutorial of modeling cQED systems with the open source scQubits and qFit packages. Then Professor Eli Levenson-Falk discussed how to optmially teach design to students in a way that is scalable. Then the advanced track took a break for lunch. After lunch, Sadman Ahmed Shanto (whom we typically just refer to as Shanto) from USC led a workshop on advanced features and the backend of the open source SQuAADS package, which uses machine learning to generate a GDS file or chip design from a given cQED Hamiltonian. This was followed by a breakout session on formalizing cQED and quantum device design education, namely how do we make an interactive textbook and set aside dedicated lab equipment for an open source educational ecosystem for cQED and superconducting qubits.

During lunch, we also hosted an industry networking session where companies like Keysight, Zurich Instruments, and Quantum Machines had table top demos or brochures about their microwave control system interfaces and design tools for quantum computers that attendees could walk around and see. This same session was hosted during lunch on day 3 as well.

Day 3

On Wednesday, the beginner track kicked things off with a tutorial from Shanto about how to use SQuAADs to generate circuit layouts and best practices for accurate electromagnetic simulation of quantum devices such as best practices for meshing, convergence criteria, and DRC rules. This was followed by a talk by Professor Hakan Tureci on his open source package, DEC-QED that can take into account flux quantization, kinetic inductance, and penetration depth. After that, the beginner session took a break for lunch. After lunch, Loren Alegria from Lawrence Livermore National Laboratory gave a talk about designing superconducting qubits with material science considerations and using large language models to design qubits. Finally, the day was capped off with Ben Jarvis-Frain from Rigetti Computing who gave a talk on designing large-scale quantum devices and accounting for cross talk, flip chip architectures, and other 3D architectures.

The advanced track started things off with Arpit Arora from UCLA who gave a talk on designing superconducting diodes and nonreciprocal quantum circuits. This was followed by a workshop on running microwave simulations on a large scale quantum device in a scalable way and how to simulate 3D and flip chip integrated quantum circuits. After this, the advanced track had lunch. After lunch, Dung Pham from Princeton gave a talk about DEC-QEC and modeling open quantum systems and nonlinear phenomena in superconducting circuits. The last talk of the day was given by the Pahl brothers who discussed quantum device architecture for qLDPC codes in superconducting qubits. Finally the day was ended with a breakout session where the advanced track participants discussed open source design software maintnence and feature additions. During this time, a group dedicated to software maintnence was also formed. The discord link to join this group is here

<p style="text-align:center;">Lukas Pahl from MIT gives a talk on designing superconducting devices for quantum low density parity check codes.</p>

Day 4

For day 4, the beginner and advanced track was combined. To kick things off, Jin Sung Kim from Nvidia gave a workshop on how to use CUDA-Q for fast quantum simulations of the Jaynes-Cummings Hamiltonian and the Landau-Zener effect. After this, the participants had lunch. The day and the workshop was capped off by the panel event and reception, where Andrew Bestwick (senior VP of quantum systems at Rigetti Computing), Professors Andreas Wallraff, Michel Devoret, Eli Levenson-Falk, and Jens Koch discussed the future of designing quantum devices and scaling up superconducting qubits. This panel was moderated by Zlatko Minev.

<p style="text-align:center;">All smiles among the panelists as they dive into the future of quantum device design!</p>

Post-Event Summary

The inaugural Quantum Device Workshop successfully brought together a global community eager to learn, collaborate, and contribute to the future of quantum hardware design. Across both tracks, participants gained hands-on experience with leading simulation tools, explored emerging research directions, and engaged directly with experts advancing the state of the art.

Highlights

Exceptional turnout from academic, industry, and student communities
High engagement across both technical tracks, from foundational cQED concepts to advanced architectures
Interactive breakout sessions supporting open-source development and education
Networking opportunities that sparked new collaborations and community connections

Looking Ahead

Building on the momentum of this year’s program, the organizing team plans to expand session offerings, strengthen accessibility, introduce additional mentorship opportunities, and continue broadening the workshop’s reach. Planning for next year is already underway, with the vision of welcoming an even more diverse and enthusiastic quantum hardware community.

Join the Community

To stay involved with open-source quantum device design tools and receive updates on future workshops, we welcome you to join the Community Discord and pre-register for next year’s event. For more events hosted by the Quantum Computing Student Association, feel free to join the QCSA Discord.

<p style="text-align:center;">From all of the sponsors, speakers, and organizers, we wish you long coherence times and fast two qubit gate times in your designs! See you next year!!</p>

Unitary Foundation and unitaryHACK mentioned in recent NVIDIA blogpost

Wed, 13 Aug 2025 00:00:00 GMT

UF is proud to announce that we were recently featured in a blogpost put out by NVIDIA.

As a sponsor of unitaryHACK2025, the NVIDIA team put out bounties on their open source project, CUDA-Q. Because of this collaboration, the newest version of CUDA-Q (v0.12) now includes three community contributions: • A dynamics example for preparing a GHZ state with trapped ions • A tutorial on Approximate State Preparation using MPS Sequential Encoding • An API to retrieve the unitary matrix of a quantum kernel

Read more about the newest release and unitaryHACK participant contributions here!

Operating at the edge of failure: WERQSHOP 2025 Recap

Wed, 06 Aug 2025 00:00:00 GMT

WERQSHOP: Building a Community for Error Resilience in Quantum Computing

<div style="width:100%;"> <div style="float:right;width:40%;margin-left:2em;"> <figure> <img class="not-prose" src="/images/2025_werqshop/sticker-nyu.png"/> <figcaption><a href="https://werq.shop">WERQSHOP</a> was made possible by Unitary Foundation, NYU, and grants from the NSF and DOE.</figcaption> </figure> </div> </div>

On July 17<sup>th</sup> and 18<sup>th</sup> we convened 60 people from across the quantum computing ecosystem to discuss the current state and future of error mitigation. We brought together everyone from hardcore error correction theorists, to seasoned software maintainers working on mitigation tools. The goal was to bring a relatively small group of people together who have a vested interest in the topic to teach, learn, and discuss what's next for our field.

Depending on how you count it, error mitigation emerged as a field in 2017 with Error mitigation for short-depth quantum circuits and Efficient variational quantum simulator incorporating active error minimisation when early versions of <abbr title="Zero-Noise Extrapolation">ZNE</abbr> and <abbr title="Probabilistic Error Cancellation">PEC</abbr> were introduced.[^1] At the time, there was considerable excitement about the promise of <abbr title="Noisy Intermediate Scale Quantum">NISQ</abbr> devices, and <abbr title="Quantum Error Mitigation">QEM</abbr> techniques were seen as a means to enhance their utility while the field progressed toward fully fault-tolerant quantum computers.

Nearly a decade later, the context in which error mitigation is studied has changed dramatically. This raises a new and timely question:

What role does error mitigation play on early fault-tolerant computers?

That, in essence, is what we brought people together to discuss.

[^1]: There are multiple other techniques that were invented and studied prior to ZNE and PEC in 2017 (for example, dynamical decoupling and decoherence-free subspaces), but these are generally not regarded as QEM techniques following Cai et al arXiv:2210.00921.

The workshop took place over two days (with a fun mixer the night before to get things started), and the schedule comprised of a mix of invited talks, contributed/lightning talks, and discussion sessions. The full schedule, talk abstracts, and slides are available on werq.shop.[^2] The talks were broken into 5 sessions:

[^2]: Still waiting for someone to challenge my claim of best conference domain to date.

From Theory to Experiment where we heard about both theoretical scaling limitations of QEM from Yihui Quek and how QEM aided simulations of quantum magnetism on Quantinuum devices.
QEM on Next-Gen Devices where Zhenyu Cai discussed two ways to merge QEM and QEC, and Raam Uzdin introduced methods for mitigating noise on circuits with mid-circuit measurements.
QEM and QEC was a popular session where applying mitigation techniques to logical qubits was discussed from Yongshan Ding, and William Huggins presented work on resource estimation in the early fault-tolerant era.
On the second day we had a large session on QEM in practice where
1. Thomas O'Leary discussed symmetries in QEM
2. Jin Ming Koh showcased error mitigation applied to condensed-matter simulations
3. Matea Leahy presented a sample-optimal tensor-network error mitigation technique
4. Pablo Bonilla talked on quantum error correction for neutral atom processors
5. María Gragera Garcés evangelized the need to consider QEM in the context of distributed quantum computing
6. Sam Ferracin showcased how performant software has led to drastically faster application of QEM techniques at scale
Lightning talks on
1. Simulating quantum field theories (with error mitigation) from Zhiyao Li
2. Machine learning applied to QEM from Simone Cantori
3. Quantum error detection from Ethan Egger
4. Adapting QEM on the fly from Yvette De Sereville
5. mitiq and all its joy from Nathan Shammah

We also had a panel where attendees got to grill 3 brave panelists (Misty Wahl, Raam Uzdin, and Andrea Mari) on the future of QEM. Andrew Arrasmith (IonQ) led a discussion on the topic of interfacing open- and closed-source software,[^3] followed by breakout sessions on compilation, QEM software, and QEM+QEC.

[^3]: A topic mitiq maintainers know painfully well.

The two days flew by, and before I knew it we were at a local bar discussing the things we learned, and what we were most excited to continue working on , both individually and for the community. There are many memorable moments and quotes (some of which will be shared in a more formal post-event report, and some which will not be shared 🙉), but one of my favorites is

we will always be pushing these devices to the edge of failure to get advantage

Yongshan Ding

Regardless of the role that error mitigation plays in the coming years, we can be sure that we'll be pushing devices to the absolute limit.

Themes

A few themes came up again and again throughout the two days:

First and foremost, there's no one-size-fits-all solution. Despite years of work, the field lacks a shared understanding of when and why different QEM techniques succeed. If you're handed a device with a specific noise model, good luck finding prescriptive advice that doesn't boil down to "try everything."
QEM + QEC is still underexplored. Several talks proposed new ways of layering or integrating mitigation techniques with early fault-tolerant architectures. This is very likely going to be very important over the next decade, but we're still early.
Tailored techniques are showing real results. Some of the most compelling results came from teams designing mitigation strategies specific to the structure of the problem or algorithm. This may be where error mitigation can have the most near-term impact.
Everyone is using multiple techniques. Whether it's randomized compiling, dynamical decoupling, zero-noise extrapolation, or learned calibrations — in practice, people are stacking methods.

It's clear there is a lot of work to do, and many side streets and alleyways to explore, but I think many of us are walking away from this event with a few of those possibilities pruned, and a more solid sense of direction. If you attended, I hope you're feeling similarly, and if you didn't make it, I hope this, in combination with a coming soon technical report will help you feel the same way.

🙏 Thank you ❤️

To end, I want to give a few thanks:

To the Unitary Foundation for letting me organize this event
To my wonderful WERQSHOP co-organizers (Nathan Shammah, Greg Quiroz, Ryan LaRose, Andrea Mari, Pranav Gokhale, Peter Orth, Misty Wahl, Will Zeng)
- The best local organizers: Veena Vijayakumar, Ben Castanon, Javad Shabani, Monna Sabouri
All of the speakers listed above: this wouldn't have been an event without you!
Every single attendee: everyone who showed up engaged with hard questions and brought many amazing ideas on what to do next. Thank you for fueling the future of error resilience!

<figure> <img class="not-prose" src="/images/2025_werqshop/group.png"/> <figcaption>Group photo taken on our very theatrical stage.</figcaption> </figure>

Community-Driven Quantum Compilation w/ UCC @ unitaryHACK 2025

Thu, 31 Jul 2025 00:00:00 GMT

This year marks our fifth annual unitaryHACK hackathon (check out our post-event wrap-up blog)! It's also the very first year Unitary Foundation's new open-source quantum compiler UCC has been a part of the event. In this blog, we're going to let three of the UCC unitaryHACK Bounty winners tell you about their projects.

We created UCC to be a quantum compiler that's genuinely community-driven -- that's part of our mission to make quantum computing more accessible and beneficial to the most people -- and so we did something a little different from the typical unitaryHACK bounties. We put out an open call for new quantum compiler passes, and the community delivered! Let's hear from them:

Verifying logical equivalence of quantum circuits

Hacker	Bounty Amount	Description
WingCode	$200	In order to complete this issue, you should aim to demonstrate the use of one of these tools to verify the logical equivalence of a raw quantum circuit of O(100) qubits and O(1000) gates with its UCC compiled equivalent with a runtime <1 hr, excluding compilation time.

My name is Gregory Varghese, I have a Undergraduate degree in Computer Science & Engineering, and I work as a Senior Backend Expert, currently focused on QML methods for chemical simulations.

I wanted to work on this issue because I am fascinated by this as a fundamental problem at the intersection of quantum computing and computational complexity.

<div style="display: flex; flex-direction: column; align-items: center; margin: 12px 0;"> <div style="display: flex; justify-content: center; align-items: flex-start; gap: 16px;"> <img src="/images/2025_ucc_unitaryhack/MQT.png" alt="Munich Quantum Toolkit logo" width="200" height="200" /> <div style="display: flex; flex-direction: column; align-items: center;"> <img src="/images/2025_ucc_unitaryhack/ZX-diagram.png" alt="ZX diagram rewrite rules" width="300" height="200" /> <span style="font-size: 0.9em; color: #666; margin-top: 4px; display: block; text-align: center;"> Source: <a href="https://arxiv.org/abs/1904.04735" target="_blank" style="color: #666; text-decoration: underline;">PyZX: Large Scale Automated Diagrammatic Reasoning</a> </span> </div> </div> </div>

I faced two main challenges: first, developing a solid understanding of how compute time and memory requirements grow with circuit size; second, working across multiple frameworks—such as PyZX and the Munich‑Quantum‑Toolkit/QCEC—that use differing definitions of circuit equivalence. By tackling these, I clarified scaling behaviors in my equivalence tests and identified which frameworks are best suited to our needs for establishing logical equivalence within UCC.

Verifying circuit properties for benchmarking

Hacker	Bounty Amount	Description
WingCode	$75	For this issue, the completion criteria is to check that the compiled circuits in the benchmarks only use Rx, Ry, Rz, H and CX gates. This check should not be included in the measured compilation time.

I was drawn in by the compelling opportunity to enhance benchmarking reliability through direct gate‑set verification. Because the issue was clearly described, I was able to proceed smoothly, encountering minimal difficulty. As a result, I enabled robust checks for gate‑set‑specific compilations, strengthening benchmarking accuracy within UCC.

<div style="display: flex; flex-direction: column; align-items: center;"> <img style="margin-top: 0; margin-bottom: 0;" src="/images/2025_ucc_unitaryhack/gate-control.png" alt="cartoon of a Matrix Product State (MPS) drawn as a strip of paper with scissors poised to cut at regular intervals" width="200"/> <span style="font-size: 0.9em; color: #666; margin-top: 4px; display: block; text-align: center;"> Source: <a href="https://pennylane.ai/qml/demos/tutorial_optimal_control" target="_blank" style="color: #666; text-decoration: underline;">PennyLane gate compilation tutorial</a> </span> </div>

In the future, I am interested in researching additional transpilation passes within the UCC framework, particularly by leveraging large language models (LLMs). Additionally, I aim to design scalable and predictive models capable of evaluating the logical equivalence of black-box quantum circuits, focusing on metrics such as compute time and memory usage.

Introducing an approximate compilation module

Hacker	Bounty Amount	Description
ACE07-Sev	$500	Sequential MPS encoding [[1]] is a way to approximately encode a matrix product state up to arbitrary fidelity in $O(N)$ circuit depth where $N$ is the number of qubits. The cap fidelity is based on the bond dimension $\chi$ which trades off memory and runtime with potential for squeezing more fidelity from the encoding.

Greetings! I am Amir Ali Malekani Nezhad, a Quantum Compilation Researcher and Developer currently pursuing MPS/MPO (Matrix Product State/Operator) utilization for approximate compilation of arbitrary statevectors and operators in O(N) depth.

What drew me to this issue or to UCC? During unitaryHACK 2025, I had the pleasure of contributing to UCC, a Quantum Compilation library maintained by Jordan Sullivan and Brad Chase. Given my current obsession with anything related to Quantum Compilation, the issue immediately intrigued me. Upon reading about the premise of the issue, and the creative freedom provided by UCC’s supportive team, I proposed an approximate quantum compilation module. This was intended to complement the current compilation pipeline present within UCC to tradeoff slight infidelity with exponential depth reduction for certain class of states known as area-law entangled states.

<div style="display: flex; flex-direction: column; align-items: center;"> <img style="margin-top: 0; margin-bottom: 0;" src="/images/2025_ucc_unitaryhack/MPS-cartoon-pennylane.png" alt="cartoon of a Matrix Product State (MPS) drawn as a strip of paper with scissors poised to cut at regular intervals" width="200"/> <span style="font-size: 0.9em; color: #666; margin-top: 4px; display: block; text-align: center;"> Source: <a href="https://pennylane.ai/qml/demos/tutorial_mps" target="_blank" style="color: #666; text-decoration: underline;">PennyLane MPS tutorial</a> </span> </div>

Challenges I faced in hacking on this issue: While developing the open-source qmprs project for compression and compilation of quantum circuits using tensor networks, I had become familiar with the side-effects of approximation in state encoding. However, it was through UCC’s suggestion to benchmark the compiler using their suite that a critical limitation came to light—random Clifford circuits revealed themselves as a particular weakness of MPS-based approaches. Digging into the entanglement properties of both the benchmark circuits and the typical states I had used, I realized the circuits exhibited volume-law entanglement, whereas the states I had relied on were coincidentally area-law entangled. This contrast helped explain the discrepancy and highlighted both an opportunity and a constraint for the proposed compiler.
I spent time during and after the event exploring ways to reconcile this, eventually incorporating a method to ensure consistency for volume-law circuits via variational fine-tuning.

The experience was deeply instructive, and I was fortunate to contribute to the project, though it was UCC’s benchmarking approach that uncovered the limitation in the first place—a contribution I remain genuinely thankful for. Additionally, UCC’s infrastructure emphasized the importance of compatibility between approximate and exact compilation methods. To support this, I introduced a fallback mechanism that checks fidelity and cost metrics, defaulting to UCC’s exact compiler when approximation underperforms. It was a straightforward solution, but in hindsight, one that proved to be quite practical.

Future projects I'm interested in working on: My current focus is on finishing qmprs. Given the approximate compilation module making it to production, I will be looking forward to integrating qmprs once it reaches a minimum mature stage in UCC with the help of the supportive maintainers. Feel free to reach out to me via LinkedIn, or Discord, or email should you have any questions or would like to collaborate.

Porting over a BQSKit compiler pass

Hacker	Bounty Amount	Description
WolfLink	$500	I plan to integrate BQSKit into a UCC compiler pass. BQSKit offers a suite of techniques, but for the circuits in the UCC-bench suite, partitioning and resynthesis by LEAP will likely be most effective.

Hi, I'm Marc Davis, currently pursuing a PhD at MIT researching quantum compiling techniques.

What drew me to UCC: In the course of my research, I work with a variety of quantum circuit compilation, transpilation, and optimization tools, and a common problem is interfacing between different tools, which often rely on different underlying circuit formats, sometimes with different sets of features. UCC's goal of making a wrapper that allows the interplay of many different tools is a worthy one.

<div style="display: flex; flex-direction: column; align-items: center; margin: 20px 0"> <img src="/images/2025_ucc_unitaryhack/bqskit-logo.png" alt="BQSKit logo" width="200" height="auto" /> <span style="font-size: 0.9em; color: #666; margin-top: 4px; display: block; text-align: center;"> Source: <a href="https://bqskit.readthedocs.io/" target="_blank" style="color: #666; text-decoration: underline;">BQSKit: Berkeley Quantum Synthesis Toolkit</a> </span> </div>

Challenges I faced: My idea was to combine UCC and BQSKit. BQSKit is a quantum compiling tool I have previously worked on that provides a suite of optimization techniques. By implementing BQSKit as a UCC pass, I enabled many powerful circuit optimization tools to be used with the UCC ecosystem. However, many of BQSKit's tools are focused on providing highly efficient circuits at the cost of runtime on the order of hours. UCC has strict runtime limits on the order of less than a second. Since these compilers have different underlying goals, for this issue, we made the design decision to make BQSkit an optional pass rather than a core part of the UCC workflow. This way users can easily import the pass, but the benchmarks for UCC won't be affected by extended runtimes.

Another difficulty in implementing BQSKit was encountering the limitations of the Qiskit TransformationPass that UCC uses as the base class for its compiler passes. This class does not maintain information about the target hardware, such as the coupling map, which prevents UCC passes from taking advantage of this information.

Future Projects: I am currently working on compiler passes working on T-count minimization. If UCC targets fault tolerant circuit optimization in the future, I hope to include my T-count minimization tools.

Get involved

Did you get inspired by something you read here? Tell us about it! Comment on this blog post, reach out in the #ucc channel on Discord for casual or time sensitive questions -- or create a GitHub discussion for code, repo, or theory stuff :]

About UCC

The Unitary Compiler Collection (UCC) is a Python library for frontend-agnostic, high performance compilation of quantum circuits. UCC's goal is to gather together the best of open source compilation to make quantum programming simpler, faster, and more scalable.

GitHub Repos:
ucc - our main Unitary Compiler Collection source code repo
ucc-bench - our quantum compiler benchmarking suite
ucc-ft - our prototype Fault Tolerance checker for quantum circuits

Want to know more?

Read the launch announcement to get a feel for UCC's design philosophy.
Watch our introductory video on UCC from FOSDEM 2025 by @natestemen.
Explore research publications that utilize UCC.

2025 Q2 Updates: New Supporting Members, UnitaryHACK Wrap-up, and Hitting Community Milestones!

Fri, 11 Jul 2025 00:00:00 GMT

Dear Unitary Foundation community,

We're happy to share our 2025 Q2 quarterly update!

In this first half of 2025, we were honored and excited to bring on two new supporting members, Riverlane and Quantum Machines. With the support of these two companies and all of our ongoing members, UF can continue to commit deeply to our research and community development. You can read more about our new members here.

Last month, we closed out our largest unitaryHACK in UF's history. In this fifth edition of the HACK, we welcomed 900+ hackers and 100+ maintainers from 76 countries around the world. Hackers closed 172 bounties and collected a total of $19710 USD. Read more about the leaderboard, our in-person HACKdays, and more here.

We also hit a major milestone in the growth of our community. The Unitary Foundation Discord server now has 5,000+ members! If you're not already, join us on Discord as well as our other social channels (e.g. LinkedIn and Bluesky account) to keep up-to-date on all things UF + open source quantum computing.

Finally, a few things in Q3 that should be on your radar (you can read more about these below):

unitaryCON 2025 will take place on September 3-4 alongside IEEE Quantum Week in Albuquerque. Reach out to us at [email protected] if you'd like to join us this year!
The Quantum Open Source Survey will open at the end of Q3. Keep an eye out - we'd love to hear your thoughts!

See you soon! The UF Team

New from Unitary Foundation

Research Papers

Tight bounds for antidistinguishability and circulant sets of pure quantum states, N. Johnston, V. Russo, J. Sikora [Quantum 9, 1622, (2025)][2311.17047].

UCC

First paper published using UCC to achieve SOTA results in multi-chip architectures: Hardware-aware Compilation for Chip-to-Chip Coupler-Connected Modular Quantum Systems, Z. Du, et al [2505.09036].
New versions released:
- V0.4.7 [June 2025]: In v0.4.7, on the heels of UnitaryHACK 2025, we have integrated our first compiler passes developed by external contributors. This includes a BQSKiT port and a new approximate compilation module. We have also made a slew of documentation and infrastructure improvements based on feedback from UHack contributors, including streamlining the new compiler pass proposal to PR acceptance workflow
- V0.4.6 [May 2025]: Version 0.4.6 introduces major workflow improvements, including migrating UCC benchmarking to the standalone ucc-bench repository, enabling automated performance checks on PRs with results posted directly as comments. This release prepares for dynamic circuit support by allowing user-defined target gatesets post-compilation and begins prototyping a fault tolerance checker (tracked in ucc-ft). Additionally, the project now uses uv for faster package management and enables Dependabot for dependency updates, streamlining development processes
- V0.4.5 [April 2025]: In version 0.4.5, we enabled plotting of relative errors on the simulated benchmarks and continued refinement of the expectation value benchmarking flow, including the addition of a custom observable for QCNN circuits and adjustments in the applied gate error rates to reflect capabilities of current devices. We also automated the pypi publishing workflow upon release, added support for Qiskit 2.0 along with other dependency upgrades, and updated our infrastructure to reflect the GitHub rebranding of UCC's home organization, Unitary Foundation

Mitiq

We reached 250k downloads! Check out this post (and graphic) to learn more
New citations
- Anomalous slow-down of the bound state dynamics in a non-locally coupled quantum circuit, B. Paul, S. Mondal, T. Mishra [2506.09818].
- Deep-learned error mitigation via partially knitted circuits for the variational quantum eigensolver, S. Cantori, A. Mari, D. Vitali, S. Pilati [2506.04146].
- Quantum-Accelerated Supercomputing Atomistic Simulations for Corrosion Inhibition, K. Elgammal, M. Maußner [Link].
- Quantum Resilience: Canadian Innovations in Quantum Error Correction and Quantum Error Mitigation, G. Saxena,et al [2505.20534].
- Quantum error mitigation, N. Milazzo [Blogpost].
- Quantum Artificial Intelligence for Software Engineering: the Road Ahead, X. Wang, S. Ali, P. Arcaini [2505.04797].
- Analysis of Innovative Quantum Optimization Solutions for Shor’s Period Finding Algorithm Applied to the Computation of, K. Dias, E. Ezin [Link].
0.45.0 release
- Upgraded many tutorials to use latest versions of qiskit
- Mitiq <> UCC tutorial
- Virtual Distillation user guide now live

Metriq

We have released the Metriq-Gym beta on PyPI. This is an open source command-line tool to define, collect, review, and publish quantum hardware benchmarks directly to the Metriq web app. More news on Metriq-Gym will be released in the coming weeks. For now, check out our Github page for more info!
We presented at the third international workshop on quantum benchmarking, organized by Teratec in Palaiseau, France. All slides from the talks can be found here

QLASS

QLASS was the first project in unitaryHACK 2025 to be fully completed
QLASS was demoed in a webinar at the European Space Agency Φ-lab Collaborative Innovation Network on Open Source Quantum Technology
More info can be found on the QLASS website

Conferences + Events We Attended in Q2

April 9, 2025 at Quantum Group @ UW Allen School, "On Error Mitigation and its sample complexity" by Nate Stemen
May 13, 2025 at International Conference on Quantum Computing, about the paper “Quantum amplitude estimation from classical signal processing” [2405.14697] by Farrokh Labib
May 29, 2025 at PyCon Italia, “Quantum computing without leaving Python behind” by Alessandro Cosentino
June 4, 2025 at Edge Esmeralda 2025, "An Intro to Unitary Foundation and the unitaryDESIGN program" by Ben Castanon
June 18, 2025 at The Coding School’s Early Quantum Career Immersion Program, “Building Out the Next Steps in Your Quantum Computing Journey” by Veena Vijayakumar
June 25, 2025 at the TQCI Quantum Benchmark conference, "Independent, systematic, reproducible and open-source quantum benchmarking with metriq-gym" by Nathan Shammah

Q2 Grants

To Andi Gu and Pablo Bonilla for Fast Neural Decoders for Universal Logical Quantum Algorithms
To John van de Wetering for Future-proofing PyZX
To Yudong Cao, Shangjie Guo, Manuela Rivas Gómez, and Aleyna Küçükçolak for quantum_factoring_resource_estimation
To Shuwen Kan and Zefan Du for Pauli Atlas: Pauli-Based Computation Compiler for Quantum Error Correction
To Balint Pato for PlanqTN
To Rakhim Davletkaliyev for Quantum Computing for Software Engineers

Other News from the Community

Micrograntee Katherine Van Kirk presented her project, Derandomized Shallow Shadows, at the 2025 Quantum computing theory in practice (QCTiP) conference in Berlin, Germany
Micrograntee Amber Van Hauwermeiren and her team at OrangeQS have even more updates from their company for this quarter:
- OrangeQS raised a €12M seed round, the largest quantum seed round in The Netherlands
- A new development project by OrangeQS and TU Delft focuses on automation and parallelization of protocols for testing quantum chips
- The team will be hosting an upcoming workshop about open-source OrangeQS Juice and Quantify at SQA Delft 2025 on Wednesday August 27th
Several UF micrograntees brought their projects to unitaryHACK 2025, closed out issues, and built new relationships with contributing hackers. Participating projects included: graphix, PauLie, Piccolo.jl, H-hat quantum programming language, Quantify, PyZX, Quantum Open Source Foundation, and Quantum Universal Education. Check them out on the unitaryHACK website!

Coming up

The 2025 QOSS Survey will open at the end of this quarter - follow us on socials and our newsletter to be the first to know when it drops! Here are last year’s results
Save the date: unitaryCON will be co-located with IEEE Quantum Week in Albuquerque this year. If you'll already be in Albuquerque for IEEE, we hope you'll join us for unitaryCON 2025 on September 3-4 at the Albuquerque Convention Center. Reach out to [email protected] for more information
Stay up-to-date on all things UF and Quantum Open Source Computing by following us on our communication channels:

Unitary Foundation Welcomes Two New Supporting Members - Quantum Machines and Riverlane

Mon, 30 Jun 2025 00:00:00 GMT

We are excited to share that Quantum Machines and Riverlane are now a part of our Member Program as Supporting Members!

<table style="width: 100%; border-collapse: collapse; margin: 64px 0; border: none;"> <tr style="vertical-align: middle; border: none;"> <td style="width: 40%; text-align: center; vertical-align: middle; border: none;"> <a href="https://www.quantum-machines.co/" target="_blank"> <img src="/images/logo_quantum_machines.png" style="max-width: 100%; height: auto; display: block; margin: 0 auto; object-fit: scale-down;"> </a> </td> <td style="font-size: 1rem; padding-left: 40px; vertical-align: middle; border: none;"> <a href="https://www.quantum-machines.co/" target="_blank" style="font-weight: bold; text-decoration: none; color: inherit;"> Quantum Machines </a>is a team of quantum physicists, software and systems engineers, and chip designers, all passionate to advance the world of quantum computing further than it has ever gone before. </td> </tr> </table> <table style="width: 100%; border-collapse: collapse; margin: 64px 0; border: none;"> <tr style="vertical-align: middle; border: none;"> <td style="font-size: 1rem; padding-right: 40px; vertical-align: middle; border: none;"> <a href="https://www.riverlane.com/" target="_blank" style="font-weight: bold; text-decoration: none; color: inherit;"> Riverlane </a>'s mission is to make quantum computing useful far sooner than previously imaginable, and they are working to achieve this by building Deltaflow – the quantum error correction stack. </td> <td style="width: 25%; text-align: center; vertical-align: middle; border: none;"> <a href="https://www.riverlane.com/" target="_blank"> <img src="/images/logo_riverlane.png" style="max-width: 100%; height: auto; display: block; margin: 0 auto; object-fit: scale-down;"> </a> </td> </tr> </table>

We are so grateful for Quantum Machines and Riverlane’s ongoing support of the quantum open source tools, and look forward to continuing to grow the ecosystem together with them. To learn more about our new member program, email [email protected].

Optimizing the Molecular geometry of the Haber-Bosch Process with Pennylane

Fri, 27 Jun 2025 00:00:00 GMT

This work was done during the Quantum Open Source Foundation mentorship program, Cohort 9. I would like to express my gratitude to my mentor Danial Motlagh and to QOSF.

Introduction

Catalytic processes are the workhorses of industry – for example, the Haber–Bosch synthesis of ammonia $$\text{N}_2 + 3\text{H}_2 \overset{\text{Fe}}{\longrightarrow} 2\text{NH}_3$$ runs under extreme conditions and consumes roughly 1% of the world’s energy supply.

Understanding the reaction pathway with catalyst hopes to gain insights into the process, enhancing its efficiency. [1] has simulated the reaction using VASP using Fe211 as a catalyst as shown in Fig. 1. However, classical simulation methods like VASP quickly become forbiddenly expensive as the system grows, whereas quantum algorithms have long been predicted to outperform classical computers in modeling complex chemical processes. Indeed, hybrid quantum–classical approaches offer a natural way to handle the many-body quantum chemistry and the classical geometry search in tandem. By offloading the hardest electronic-structure parts to a quantum processor, we can efficiently evaluate energies for different molecular configurations, then use classical routines to adjust positions and orientations. <figure> <img src="/images/c124-4041-9f75-2d0e40e0a42d.png"> <figcaption>Fig 1. Reaction pathway of the Harber-Bosch process in [1] </figcaption> </figure>

This post explores how we can use Pennylane to execute the first steps with limited computer resources. Concretely, we replicate the first three steps of [1] in Fig. 2, which are the most complex reactions in the whole pathway. It is computationally cheaper than the method used in [1].

Method

Varies the coordinates of the reactant: The transition in $$x,y,z$$ axis and rotation angle around its center.
- We use two optimization methods: Gradient descent and Bayesian optimization (BO). The former method has good coverage in these Pennylane demoes in a 1D setup.
- In this work, we focus on the latter in a 3D setup. For a comprehensive review of BO, we refer readers to [3].
Construct the Hamiltonian
Measure and Optimize: Measure the expectation value of the Hamiltonian using the quantum circuit and optimize the parameters using a classical optimizer to minimize this value.

Motivation

To define a 3D affine transformation for a molecule, we need to define three translation parameters $$t_x, t_y, t_z$$ and three rotational parameters $$\theta_x,\theta_y,\theta_z$$. Calculating the gradient needs $$t_\bullet \pm \Delta_t$$ and $$\theta_\bullet \pm \Delta_\theta$$. Therefore, each learning step requires $$6 \times 2$$ Hamiltonian, which is expensive.

Bayes Optimization (BO)

BO, being a gradient-less method, does not have these requirements. Here is how it works. After the initial samplings $$\pmb{X}=x_1, x_2, ... , x_n$$ , Gaussian processing (GP) assume that

$$\pmb{X} \sim \mathscr{N}\begin{bmatrix}\begin{pmatrix} \mu_1 \ \vdots \ \mu_n\end{pmatrix},\begin{pmatrix}1 & K_{12} & \cdots & K_{1n}\ K_{21} & \vdots & \ddots & \vdots \ K_{n1} & K_{n2} & \cdots & K_{nn} \end{pmatrix} \end{bmatrix}$$

and fixes a regression curve through these data points. Only the observed data points have absolute certainty (variance = 0). For an unknown point $$x'$$, GP returns a prediction from the distribution of $$\mathscr{N}(\mu,\Sigma\lvert\pmb{X})$$.

A beautiful property of Gaussian is that when conditioning the Gaussian on a set of variables, the result is also a Gaussian $$\mathscr{N}(\mu',\Sigma')$$. In Fig.2, the prediction value of the unknown point is $$\mu'$$, whereas the confidence interval is $$\Sigma'$$.

<figure> <div class="row"> <div class="column"> <figure> <img src="/images/af199fd0-5dbe-4a2c-addb-e9fb6f2ecd2b.png"> <figcaption>A</figcaption> </figure> </div> <div class="column"> <figure> <img src="/images/358421422-033cceb6-5ea3-4663-af1f-b17e4708a085.png"> <figcaption>B</figcaption> </figure> </div> </div> <figcaption>Figure 2: A. Given initial samplings (red points), how do we predict an unknown point? B. How GP fits a regression line given these ground truths. The confidence interval is the variances of the Gaussian at an arbitrary point, and the prediction is the means</figcaption> </figure>

Here, we face a dilemma. In $$\pmb{X}$$ there is a point with the smallest value $$x_{min}$$. Therefore, the next minima should be somewhere close to it. However, it is also possible that points in the wide confidence interval have smaller values than the current minima. To quantify this trade-off, we define an acquisition function $$\alpha$$ to obtain new positions to sample. There are several approaches to define $$\alpha$$, we are using the Expected Improvement (EI) approach here.

EI works by generating random functions that lie inside the confident intervals, as demonstrated in Figure 3. The intuition is a larger confidence interval would have more diverse sampling functions. Afterward, we sample the point at the extrema and update the prior. The process continues for a predefined number of steps. <div class="row"> <div class="column"> <figure> <img src="/images/a3cd9cbd-da05-40a2-a61d-8f18760cda38.png"> <figcaption>Figure 3. Given the prior in solid blue, EI generates two candidates (dashed red and green lines) that satisfy the confidence interval requirements. Consequently, we sample the real value at the point marked with "?"</figcaption> </figure> </div> </div>

Simplification

To facilitate the calculation with our limited computing resources we made the following simplification

Calculating the Hamiltonian with $$\text{STO-3G}$$, a minimal orbital basis.
Simplyfing the catalyst substrate. <div class="row"> <div class="column"> <figure> <img alt="image" src="/images/c981aea2-1fb2-4cad-95b8-0ba84b8cee11.png"> <figcaption>The Fe211 catalyst substrate used in [1] </figcaption> </figure> </div> <div class="column"> <figure> <img src="/images/aa6a75ec-c8f5-406b-82df-9de6bb4838a6.png"> <figcaption>Our simplified catalyst substrate</figcaption> </figure> </div> </div>

Visualization

We will replicate the first three steps of Figure 2, whose Hamiltonians are the most complex in the whole pathway.

In the below visualization, we color-coded the atoms as <span class="boxed fe"> $$\text{Fe}$$ </span> <span class="boxed n"> $$\text{N}$$ </span>, and <span class="boxed h"> $$\text{H}$$ </span>. Please open the GIFs/videos in a new tab for a full-resolution version.

Step 1

We fix the coordinates of the catalyst substrate and use the gradient descent method to optimize the coordinates of the reactants. The result is as follows. <figure> <div class="row"> <div class="column"> <figure> <img style="scale: 80%" src="/images/355275392-0463d31a-b969-42af-9cef-c7c4c7cbbb72.png"> <figcaption>A</figcaption> </figure> </div> <div class="column"> <figure> <img src="/images/355273309-3213af70-d246-43c7-859d-5c12cb607d5e.gif"> <figcaption>B</figcaption> </figure> </div> <div class="column"> <figure> <img src="/images/356906338-ad7863f8-26a2-4ebd-93fa-83bdc119fc14.gif"> <figcaption>C</figcaption> </figure> </div> </div> <figcaption>A. The ground truth from [1] B. Our simulation from a randomized position C. The ground state energy of the Hamiltonian</figcaption> </figure> Even with the same learning rate, the speed of the reactants slows down greatly compared to the beginning. Therefore, we conclude that in this step, the learning converged.

Step 2

In this step, we add $$H_2$$ as a reactant. To minimize the time to build the Hamiltonian, we fix the coordinates of all the reactants of the previous step. Since gradient descent works before, let's apply the same method. <div class="row"> <div class="column"> <img alt="image" src="/images/354735960-e02f4911-6a03-4fde-82bf-d81f0250f94f.png"> </div> <div class="column"> <img alt="image" src="/images/354742674-523ecb70-6cf6-4c20-a077-0f957f0b255e.gif"> </div> </div> Note the moving speed of the reactants is much slower than the previous step. Therefore, it is clear that we are stuck at a local minimum, and gradient descent would have a hard time escaping it without modeling the endothermicity of this reaction ($$0.98$$ below the arrow). Let us try with BO to see if it can overcome this minima.

<div class="row"> <div class="column"> <img alt="image" src="/images/356371643-513c5f1e-ec65-4a97-b6d7-403902fb096a.gif"> </div> <div class="column"> <img src="/images/356761793-ede2698a-2db0-41d1-a3c5-27c8bb818aa9.gif"> </div> </div> Due to the nature of the acquisition function, the plot of the ground state energy does not decrease nicely as seen in the gradient descent. Most of the $$\text{H}$$ atoms went too far away from the catalyst substrate, due to our initial setup of the search margin, which is $$1 nm$$ bigger than the catalyst substrate. Here we filter only what went inside the substrate.

We conclude that the search boundary condition is of utmost importance. Accordingly, we modify the search space as below. <figure> <img src="/images/0fd1987e-55d7-40f3-ac2d-6231d561a95d.png"> <figcaption>The size of the search boundary in comparison with a $$\text{Fe}$$ atom</figcaption> </figure>

Here is the optimization after setting the search boundary. We made these demonstration videos instead of GIFs so that readers can control the frame shown. <div class="row"> <div class="column"> <video controls autoplay mute loop> <source src="/images/357620305-58da4eaa-548d-4c2b-8c57-eb7368073973.mp4" type="video/mp4"/> </video> </div> <div class="column"> <video controls autoplay mute loop> <source src="/images/357975419-000ac2a4-21fe-4055-b48f-da7da6998d4f.mp4" type="video/mp4"/> </video> </div> </div>

$$\text{NH}_3$$ molecule is produced in a total of 6 trials (namely 12th, 13th, 25th, 26th, 27th, and 28th), which coincidentally matches the efficiency of the Harber-Bosch process of about 20%^a. It also offers an explanation for that number, which is the coordinates that create $$\text{NH}_3$$ have higher ground state energy than the other configurations where $$\text{H}$$ atoms float away. Note that there are times that the BO chooses to sample two very close points consecutively (12th and 13th frame for example), it is because of the exploitation and exploration trade-of that we mentioned earlier

Conclusion

This blog post provides an alternate method to optimize the geometry of the Haber-Bosch process. Due to the lack of computational resources we have to reduce the catalyst platform, number of active orbitals, and electrons. These parameters are visible in chem_config.yaml. Even with a simple orbital basis and reduced numbers of active electrons and orbitals, the experiments still take up a lot of time.

Gradient descent: 32 CPU, 256 GB RAM, 50h runtime
BO: 8 CPU, 64 GB RAM, 60h runtime

The parameters of free electrons and free orbitals are crucial parameters to make this project possible as a full configuration interaction can take up to TBs of RAM to calculate. That being said, our current simple setup can replicate the location where $$\text{NH}_3$$ is produced on the catalyst surface.

Comments? Questions? Please let us know at Issues page

References

[1] Reaction mechanism and kinetics for ammonia synthesis on the Fe(211) reconstructed surface. Jon Fuller, Alessandro Fortunelli, William A. Goddard III, and Qi An. Physical Chemistry Chemical Physics Issue 21, 2019

[2] Reiher Markus, Nathan Wiebe, Krysta M. Svore, Dave Wecker and Matthias Troyer. Elucidating reaction mechanisms on quantum computers. Proceedings of the National Academy of Sciences 2017

[3] Kevin Patrick Murphy. Machine Learning: a Probabilistic Perspective. MIT Press, 2012

.fe { background: #e06633; } .n{ background: #3050f8; } .h{ background: #fefefe; } div.flex { display:flex; justify-content:space-between; flex-wrap:wrap; align-items:center } figcaption { text-align:center } div.row { display:flex; flex-direction:row; flex-wrap:wrap; width:100%; align-items:center; justify-content:space-between } figure image { margin-left:auto; display:block; margin-right:auto } div.column { display:flex; flex-direction:column; flex-basis:100%; flex:1; align-items:center; justify-content:space-between } </style>

unitaryHACK 2025: That's a Wrap!

Tue, 24 Jun 2025 00:00:00 GMT

Dear Unitary Foundation community,

Last week, unitaryHACK 2025 officially came to a close. After 2+ weeks of working together, our community pushed out a record amount of code within the hackathon’s history (see below for the full stats)! Each year, unitaryHACK grows larger, and this is a testament to the importance and staying power of open source quantum computing.

It was such a pleasure to work with all of the maintainers and hackers for this fifth edition of the HACK. A hearty thank you to everyone who took part. We’re looking forward to working with you all next year!

Hack on,<br> The unitaryHACK Team

What is unitaryHACK?

unitaryHACK is a unique bug-bounty style program that rewards individuals at all experience levels, building professional skills by substantively supporting our most important open source tools and contributing to a more functional, and featured, quantum computing stack. 2025 welcomed the 5th edition of unitaryHACK, which ran from May 28 - June 11, 2025.

With the generous support of our sponsors and members, unitaryHACK was able to further expand our deeply engaged, global, and continuously growing developer community as well, with 65% of this year’s hackers claiming to have engaged in the open source computing world for the very first time. Take a look below for more stats and a full recap of this year’s HACK!

2025 Stats

This year, 172 bounties were closed and $19,710 was earned by 78 hackers (compared to 139 bounties, $13,142 earned, and 68 hackers in 2024)! Congratulations to everyone who closed bounties, contributed to projects in meaningful ways, and built relationships both online and in person during the two weeks of unitaryHACK.

The 2025 leaderboard can be found here. And keep an eye out for more blogposts coming soon about meaningful contributions and collaborations that came out of this year's HACK!

HACKdays

While the majority of unitaryHACK takes place digitally, the HACKday program's goal is to foster in-person meetups with students and quantum enthusiasts to network and build community at local colleges and companies around the world.

6 HACKdays took place in the US, Portugal, Finland, Mexico, Switzerland, and Italy. Thank you to all of our HACKday organizers who spent their free time putting together these meaningful and fun in-person events at the University of Washington, the University of Coimbra, Aalto University, Universidad Nacional Autónoma de México, EPFL, and the QLASS Project!

Projects + Maintainers

unitaryHACK thrives thanks to our incredible community of maintainers, who generously guide and support new contributors on their projects. This year included the increase of Rust projects to accelerate compilers like Qiskit and PyZX with backends like QuiZX and rustworkX (similar to NetworkX, but not in Python). We also saw projects that return to unitaryHACK year after year, like scqubits and KQCircuits, packages for modeling and simulating superconducting circuits and chips. And of course, we brought in new projects including Incospiquous, HUGR, Qualtran, and many others.

This year's full cohort of projects is below! You can learn more about their projects and the issues they curated on the bounties page of the unitaryHACK website!

"Personally, it was very valuable to get new contributions on some issues, and also getting a new long-term contributor! The community is very supportive and welcoming, so I'm happy to see it develop and mature that way even more over time. We have a special thing being done here for the quantum industry." — Eduardo Maschio, UF Micrograntee + Maintainer of the H-hat project

A Special Thank You to Our Sponsors

unitaryHACK continues to grow thanks to our generous sponsors. Here are some of the things that their support goes towards:

Health and sustainability of the quantum open source software community
Maintenance of early stage quantum open source projects
Bounty payout rewards for hackers in the community. Often, unitaryHACK is the first monetary support a developer receives in their career in quantum development!
Expansion of in-person HACK days for students and student groups around the world
Open source community initiatives including our Discord and the unitaryhack.dev website

Thank you once again to all who supported us this year!

ADVOCATE Level Sponsors

Moth Quantum

CHAMPION Level Sponsors

ADDITIONAL SUPPORTERS

Include Unitary Foundation and its Members:

Core Members: IBM Quantum, DoraHacks, and OQD
Supporting Members: AWS, Microsoft, Pasqal, QC Ware, SandboxAQ, Quantum Machines, and Riverlane

Keep the Party Going by Purchasing uHACK and UF Merch!

In celebration of unitaryHACK, we opened a new version of the Unitary Foundation Shop. And for a limited time we have some awesome unitaryHACK 2025 merch available as well. If you're interested in grabbing some merch, check out the shop today! Note that the unitaryHACK merch will leave the shop by the end of the month!

Better Together: Mitiq meets UCC

Wed, 18 Jun 2025 00:00:00 GMT

Combining error mitigation and compilation for stronger quantum performance

Error mitigation and circuit compilation are two critical components of an effective quantum computing stack. Error mitigation works to reduce the impact of unwanted physics on the results of quantum circuit runs, enabling larger achievable volumes, and more accurate expectation values. Circuit compilation reduces the overall circuit volume, which in turn reduces the number of possible errors in circuit execution -- more gates means more chances of encountering an error.

While these two components of the stack are often used and studied independently, we have found that using them in conjunction can lead to even better results. In this blog post, we will walk you through our first demonstration combining quantum error mitigation and quantum circuit compilation.

mitiq

For the past five years, Unitary Foundation has developed a powerful open-source library for quantum error mitigation called Mitiq which has amassed 248k downloads on PyPI to date. Mitiq provides a suite of error mitigation techniques, including:

Zero-Noise Extrapolation (ZNE): Extrapolates results from noisy runs at different noise levels to estimate the ideal result, and the subject of our first demonstration.
Probabilistic Error Cancellation (PEC): Uses hardware calibration data to create modified circuits to selectively cancel out noise in resulting expectation values.
Clifford Data Regression (CDR): Leverages the efficient simulability of Clifford circuits to train a primitive model to correct the impact of errors.

UCC

The Unitary Foundation team has a unique vantage point on the open-source quantum software landscape, and last year we decided to dive into what we see as one of the biggest missing pieces of an open-source quantum stack: a modular, cross-platform quantum circuit compiler. Last year the Unitary Foundation team decided one of the biggest missing pieces of an open-source quantum stack was a modular, cross-platform quantum circuit compiler. We set to work and launched the Unitary Compiler Collection (UCC) earlier this year.

Bringing Them Together

With UCC's launch, and a stable interface put forth, we were excited to test how the two tools work together. Code-wise, the tools work together seamlessly. First, you compile your quantum circuit with UCC, then you pass the compiled circuit into one of Mitiq's error mitigation routines.

E.g. with Zero-Noise Extrapolation (ZNE) the code is as simple as:

import ucc, mitiq

circuit = ...  # Your quantum circuit here

# compilation
compiled_circuit = ucc.compile(circuit, target_device="ibmq_mumbai")

# mitigation
my_executor = ...  # Your method of running circuits.
                   # e.g. a function that takes a quantum circuit
                   # and returns a (noisy) expectation value
                   # such as a Qiskit or Cirq simulation wrapper

mitigated_result = mitiq.zne.execute(
    compiled_circuit,
    executor=my_executor,
    scale_noise=mitiq.zne.scaling.fold_gates_at_random
)

A more fleshed-out and complete example can be found in our Mitiq + UCC tutorial, but the plot below shows the important part: compiling before applying ZNE leads to the most significant reduction in error amount the four combinations of compilation and mitigation.

<figure style="display: flex; flex-direction: column; align-items: center;"> <img src="/images/2025-mitiq-ucc/compilation-impact.png" width="600" alt="Horizontal bar plot with two bars showing the performance of compiled and uncompiled expectation values under a depolarizing noise model. Mitigation is shown as a shaded bar on top of each bar."/> <figcaption style="text-align: center; font-style: italic; color: gray; max-width: 600px;"> The impact of ZNE on pre- and post-compiled circuits which simulate the Heisenberg model on a square lattice. The circuit acts on 8 qubits, and contains 241 layers with 144 two-qubit gates. The error model used is depolarizing noise impacting two-qubit gates with a noise rate of 1%. </figcaption> </figure>

What's Next?

We're working to study further how error mitigation and circuit compilation combine to improve performance. Ongoing research can be found in Unitary Foundation's research repository.

If you're a quantum developer or researcher, using a workflow like this, we'd love to hear any feedback you may have. Your insights can help shape the future of these tools!

Get Involved

Project	Repository	Documentation	Discord Channel
`mitiq`	unitaryfoundation/mitiq	mitiq.readthedocs.io	`#mitiq`
`ucc`	unitaryfoundation/ucc	ucc.readthedocs.io	`#ucc`

Let's build quantum tools that are greater than the <s>sum</s> (tensor) product of their parts.

Extending UCC simulation benchmarks with Hamlib

Thu, 05 Jun 2025 00:00:00 GMT

Unitary Compiler Collection (UCC) is an open source software toolkit for quantum circuit compilation recently developed by the Unitary Foundation team, in collaboration with the quantum open source community. UCC combines a platform-agnostic interface with circuit optimization techniques that are competitive in compile time and gate reduction efficiency, on a suite of representative benchmarking circuits: Quantum Approximate Optimization Algorithm (QAOA) of the Barabási–Albert graph, Quantum Volume (QV), Quantum Fourier Transform (QFT), Heisenberg spin model on a square lattice, GHZ state preparation, and Quantum Convolutional Neural Network (QCNN). The UCC team actively surveys and benchmarks compiler toolchains and techniques across the ecosystem and continuously improves UCC’s default compilation sequence, integrating passes from existing tools and developing custom passes. UCC also accepts a wide array of input circuit formats and seamlessly compiles and converts between them by simple keyword arguments, affording cross-platform flexibility in compilation workflows. More information about the UCC package can be found in the launch announcement.

UCC benchmarking

The benchmarking circuits, as well as the utilities and infrastructure for running them are stored in a dedicated repository, unitaryfoundation/ucc-bench. The QAOA, QV, QFT, and square Heisenberg circuits were ported into ucc-bench from the Qiskit Benchpress package [^1]. In addition to compile time and gate reduction benchmarks, simulation benchmarks have been performed on the circuits output by UCC and other leading quantum compilers, to compare resilience to the effects of noise. The primary metric of interest for the simulation benchmarks is the error in the expectation value of a problem-relevant observable or similar figure of merit. For simulation benchmarks with circuits representing the Heisenberg spin model on a square lattice and QAOA of the Barabási–Albert graph, the chosen observable of interest is the problem Hamiltonian, while for QV and QFT circuits, computational basis measurements on all qubits are sufficient for benchmarking purposes.

Implementing Heisenberg spin model simulation benchmarks with the Hamlib Hamiltonian Library

The Heisenberg spin model describes interacting quantum spins on a lattice, where the energy depends on the alignment of neighboring spins through dot products of their spin operators, capturing magnetic behaviors like ferromagnetism and antiferromagnetism. In the UCC simulation benchmarking workflow, the square Heisenberg circuits implement the isotropic Heisenberg spin model on a square lattice, with external magnetic field and periodic boundary conditions. The square Heisenberg benchmarking circuits are parameterized in the number of qubits, with a default size of nine qubits. To implement the problem Hamiltonian as the observable of interest in the simulation benchmarks, the UCC team leveraged an existing implementation within the Hamlib (Hamiltonian Library) dataset [^2]. Each Hamiltonian within Hamlib is represented as a of a set of Pauli strings and coefficients, which the UCC benchmarking workflow then combines into a qiskit.quantum_info.SparsePauliOp object to generate the observable. Hamlib contains a large collection of qubit-based quantum Hamiltonians to support the evaluation and development of quantum computing systems, across a diverse set of problem instances.

The dataset is freely and publicly available online at https://portal.nersc.gov/cfs/m888/dcamps/hamlib. In addition to the Heisenberg model used for the UCC benchmarks, HamLib features models such as Fermi-Hubbard, Bose-Hubbard, various molecular structures, and optimization problems such as MaxCut and the traveling salesperson problem. Supported problem sizes within Hamlib range from 2 to 1000 qubits. The Hamlib dataset was developed and published to streamline research by reducing the need for manual problem preparation, enabling robust benchmarking, and promoting reproducibility and standardization in quantum studies, all shared goals of the UCC project and Unitary Foundation.

UCC is a community driven project

The UCC team and our collaborators continue to collect and integrate performant and user-friendly tools for quantum compilation and compiler benchmarking. You can help by:

Connect with us!

GitHub: unitaryfoundation/ucc
Docs: UCC Documentation
Stay Updated: Mailing List

[^1]: Paul D. Nation, Abdullah Ash Saki, Sebastian Brandhofer, Luciano Bello, Shelly Garion, Matthew Treinish, Ali Javadi-Abhari. Benchmarking the performance of quantum computing software for quantum circuit creation, manipulation and compilation. Nat. Comput. Sci. (2025). online.

[^2]: Nicolas PD Sawaya, Daniel Marti-Dafcik, Yang Ho, Daniel P Tabor, David E Bernal Neira, Alicia B Magann, Shavindra Premaratne, Pradeep Dubey, Anne Matsuura, Nathan Bishop, Wibe A de Jong, Simon Benjamin, Ojas Parekh, Norm Tubman, Katherine Klymko, Daan Camps. HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware. Quantum 8, 1559 (2024) online.

WERQSHOP, the Workshop on Error Resilience in Quantum computing

Fri, 02 May 2025 00:00:00 GMT

Today's quantum scientists and developers are constrained by a fundamental limitation: high error rates prevent meaningful quantum programs from running at scale. While we can run small, illustrative algorithms on current devices, their depth and complexity are tightly bounded by noise. Progress toward useful quantum computing will depend not just on hardware improvements, but on how well we can reduce, manage, and mitigate errors in the systems we already have.

In recent years, researchers have responded with a wave of innovations in quantum error mitigation (QEM) — techniques that suppress or reverse the effects of noise without requiring full fault tolerance. At the same time, we're entering an era where early fault-tolerant quantum computing (eFTQC) is starting to emerge. This moment calls for a serious look at how QEM and quantum error correction (QEC) should be used together, and what the software and infrastructure around them must support.

As developers and researchers ourselves, we want to better understand what to build and research next — and we know others in the community are asking the same. Which QEM techniques are most promising? What tooling is missing? Where are the biggest gaps between research and deployment? And how should the lessons from QEM be integrated into the architectures and compilers that support fault tolerance?

WERQSHOP is an attempt to answer these questions together. It's a space to share hard-won insights, identify dead ends, highlight open challenges, and align around practical next steps—both for the near-term and for the longer path to scalable, reliable quantum computing.

About the workshop

The Workshop on Error Resilience in Quantum computing (WERQSHOP) will take place July 17–18, 2025 at New York University in New York City.

WERQSHOP will bring together researchers, developers, and practitioners working on all aspects of quantum error mitigation and error-resilient compilation—from sample complexity and theoretical performance bounds to real-world implementations in noisy hardware pipelines.

The goal is to foster collaboration between:

Software developers building open-source QEM tooling and integrations
Researchers exploring the feasibility and limitations of QEM techniques
Practitioners applying QEM to improve near-term hardware outcomes
Compiler and infrastructure developers enabling seamless QEM support

By bringing these communities together, we aim to surface shared challenges, generate focused research directions, and identify key software infrastructure gaps — especially in the context of early fault-tolerant quantum computing (eFTQC).

Invited Speakers

The workshop will feature a series of invited talks and panel discussions, as well as open sessions for participants to share their own work and ideas. Invited speakers span both industry and academia with background in both QEM and QEC, and will include:

Zhenyu Cai (Oxford)
Yongshan Ding (Yale)
Sam Ferracin (IBM)
William J. Huggins (Google)
Jin Ming Koh (Harvard)
Matea Leahy (Algorithmiq)
Yihui Quek (MIT)

Important Dates

📅 Talk & session proposal deadline: May 15, 2025
📝 Deadline to register your interest in attending: May 31, 2025

Want to join us — or propose a talk? Fill out this short form.

About the Organizers

WERQSHOP is organized by the team behind Mitiq and the Unitary Compiler Collection (UCC), an emerging suite of tools for noise-resilient quantum compilation. Both projects are developed and maintained by Unitary Foundation, a nonprofit that supports open-source quantum software and research.

In addition to Unitary Foundation's core team, the workshop is co-organized by researchers from six universities and companies who are actively working at the intersection of quantum error mitigation, error correction, and software tooling. Find the full list of organizers and confirmed speakers at werq.shop.

To learn more about our past research, community projects, and publications, visit unitary.foundation/research.

Funding & Acknowledgements

WERQSHOP is made possible by support from the National Science Foundation (NSF) through a POSE Phase II grant to grow the open-source ecosystem around Mitiq.

Additional support for Mitiq, QEM research, and related software efforts has come from:

IBM Research
The DOE ARQC TEAM program
The DOE ASCR SMART Stack initiative
And of course our community of Unitary Foundation Members

Special thanks to the many volunteers and co-organizers helping shape this event. You can find the full list of organizers and confirmed speakers at werq.shop.

2025 Q1 Updates: UCC Launch, UnitaryHACK, upcoming workshops, and more

Fri, 11 Apr 2025 00:00:00 GMT

Dear Unitary Foundation community,

We are excited to share our 2025 Q1 quarterly update!

Earlier this year, we introduced the Unitary Compiler Collection (UCC) to foster collaboration and streamline quantum compilation. By working with the quantum open source ecosystem, we are excited to build a new tool designed to help the most people: integrating performant and user-friendly tools into UCC, and creating a platform-agnostic interface with competitive compile time and gate reduction efficiency. Introduced in its foundational stages, we are committed to building UCC public and inviting the quantum open source community to shape its development with us. Learn more about UCC and how you can start to contribute today here.

Last month, we announced the 5th edition of unitaryHACK, our annual bug-bounty style hackathon! Last year, 873 participants joined us and 68 hackers won bounties that spanned 49 projects. In this milestone year we aim to be bigger and better than ever, including an expansion of our Hackday Program, where students can meet in person on their campus for a day to team up and close bounties together. Currently, we’re working with partners to set up sites in Seattle, Germany, Finland, Mexico, Portugal, and more. Keep an eye out for specific venues and dates to be announced soon! To learn more about unitaryHACK, Hackdays, and the myriad ways to participate, check out our website and blogpost.

This summer we’ll also be hosting WERQSHOP, an NSF-funded workshop bringing together researchers, developers, and practitioners to advance error resilience in quantum computing. WERQSHOP will be held in New York City on July 17-18, with more information about confirmed speakers, topics, and venue to come soon. Learn more and register now on the WERQSHOP website to stay in the loop.

Looking forward to seeing you all at these upcoming events and more!

New from Unitary Foundation

UCC

We’ve officially launched the Unitary Compiler Collection (UCC)!! The UCC team is currently hosting sessions where we share a private demo of UCC’s capabilities with members of the quantum compiler community, share our design philosophy and roadmap, and ask for their feedback. A few ways our community can contribute right now: (1) creating custom compiler passes, (2) reporting bugs and requesting features, (3) contributing code and (4) joining the discussion. We’re looking forward to hearing your thoughts!

Mitiq

The Mitiq project continues to see steady growth. You can read more about about new release highlights on the Mitiq github page:

In v.0.43.0: This release marks the first step toward Virtual Distillation (VD) in Mitiq, with an initial helper function that vertically copies a circuit M times. A team of students at the University of Amsterdam worked for the month of January on implementing the technique that will be integrated into Mitiq over the coming releases. We also have a new tutorial (thanks to our colleague Purva Thakre) on combining Pauli Twirling and Zero-Noise Extrapolation!
In v.0.44.0: This release introduces the first version of the Virtual Distillation (VD) technique in Mitiq, which is now available for use! This technique was prototyped and implemented by a team of students at the University of Amsterdam. VD uses additional qubits to distill a purer version of the quantum state of interest. The implementation is in its early stages so lacks support for all QPROGRAM types. Currently only programs written in cirq are supported. We welcome feedback and suggestions for improvement.

Metriq

Metriq.info received a UI refresh where the team simplified its design and presentation to bring the most relevant information right to the forefront of the user experience!
Metriq-Gym: We have a public working prototype of a command-line tool to define, collect, review, and publish quantum hardware benchmarks directly to the Metriq web app. More news about Metriq-Gym and opportunities to collaborate will continue to be shared with the public over the upcoming months, but you can learn more on our Github page for now.

Qlass

The repository for the software tool to compile Lithium ion battery problems into photonics chips is open source at https://github.com/unitaryfoundation/qlass. We hope you’ll take a look!

Conferences + Events We Attended in Q1

University of Amsterdam Mitiq RFC project | Jan 8
FOSDEM 2025 Quantum Computing Devroom in Bruxelles | Feb 2 [Blogpost here]
QuSoft Seminar | Feb 7 [Link to presentation deck here]
APS Global Physics Summit 2025 | Mar 18 [Talk info here]

Q1 Grants

To Fenton Clawson to further develop FLiMESolve (short for Floquet-Lindblad Master Equation Solver), which is a tool for use in solving open quantum systems that fall under the regime of Floquet theory - namely those systems with periodic Hamiltonians.
To Katherine Van Kirk, Christian Kokail, Jonathan Kunjummen, Hong-Ye Hu, and Yanting Teng to develop an intuitive, open-source python package for the derandomized shallow shadows (DSS) algorithm using tensor network techniques to ensure efficient runtimes and enable experimentalists to quickly identify low-depth circuits for Pauli learning.
To Le Vu Trung Duong, Vu Tuan Hai, and Pham Hoai Luan for QIMAX: A Quantum Emulator on FPGA for High Power Efficiency. The team aims to create an emulator that outperforms CPUs, GPUs, and state-of-the-art (SOTA) emulators in speed and energy efficiency, offering a valuable tool for researchers.
To Alejandro Montanez Barrera to further develop and test LR-QAOA quantum benchmarking, which is a scalable volumetric benchmarking tool that allows the comparison of quantum process units (QPU) with different topologies.
To Konstantin Golovkin and Oxana Shaya to further develop and extend their project, PauLie.
To Sohum Thakkar to develop Qubi, an interactive device that the team hopes will be used by quantum enthusiasts as a teaching tool and by quantum newbies looking to learn quantum in an intuitive way.
To Gennadi Ryan for Python Piccolo, an open-source Python package wrapping the Piccolo.jl library, integrated with the popular QuTIP package for simulation of quantum systems.

Other News from the Community

Micrograntees Amber Van Hauwermeiren and Adriaan Rol and their team at OrangeQS have been very busy with their project. During a closed beta test phase during March Meeting, they revealed OrangeQS Juice, their new operating system for quantum systems. The team is currently running more closed beta test phases with the Advanced Quantum Testbed (AQT) at Berkeley Lab, Chalmers Next Labs, and QuTech. The system will be made open source and shared with the public later this year. You can read more here. The team also released a new version of their Quantify framework, which is now compatible with Zurich Instruments and LabOneQ hardware. And finally, the team put out a new paper called Optimizing the frequency positioning of tunable couplers in a circuit QED processor to mitigate spectator effects on quantum operations.
Micrograntee Piotr Migdal translated their project (now a new nonprofit!), Quantum Flytrap, into several languages. Piotr hopes this will make quantum physics more accessible worldwide and will give lecturers, teachers, and educators the opportunity to conduct classes in their native languages. Read about Piotr’s on the process here.
From UF Community member Tyson Jones: QuEST v4 has been released! It has an overhauled API, a new software architecture, a greatly accelerated backend and a variety of new functions - including an auto-deployer to automatically distribute quantum registers in heterogeneous and multi-GPU settings. C-language-family distributed full-state simulators have never been sexier! See the repo, or check out the new work here.

Coming up

Sign up for WERQSHOP and unitaryHACK!
Stay up-to-date on all things UF and Quantum Open Source Computing by following us on our communication channels:

Announcing unitaryHACK 2025 - Save the Date!

Mon, 24 Mar 2025 00:00:00 GMT

We’re excited to announce the 5th annual edition of unitaryHACK! The hackathon is set to take place May 28th - June 11th, 2025, and we hope you’ll join us.

For those who are newer to the community, unitaryHACK is a unique bug-bounty style program that rewards individuals at all experience levels, building professional skills by substantively supporting our most important open source tools and contributing to a more functional, and featured, quantum computing stack.

Last year, unitaryHACK had 1000+ participants, with 139 bounties claimed, and more than $13,000 awarded around the world. You can read more about last year's unitaryHACK here.

Interested in participating in this year’s HACK? Here’s what you can do right now:

Register for unitaryHACK25 through this link
Check out the unitaryHACK website to learn more about the rules and see the projects that have signed up so far
Join us on Discord to be the first to hear announcements and ask our team any questions you may have leading up to the event
Consider hosting an in-person hackday at your college or university as part of unitaryHACK. Ready to host? Reach out to us at hack(at)unitary(dot)foundation to set up your Hackday
Become a sponsor of the event. The threshold for sponsorship of unitaryHACK is lower than other events out there - we hope you'll take advantage and support our open source community in a meaningful way! Reach out to us at partners(at)unitary(dot)foundation for more information

See you all in May!

Introducing the Unitary Compiler Collection (UCC)

Wed, 05 Mar 2025 00:00:00 GMT

As quantum hardware advances, so does the complexity of programming it. Increasing qubit counts, diverse gate operations, and varied architectures present new challenges for quantum compilation. If we want quantum computation to be useful and accessible to more people, which we do at Unitary Foundation, we are going to need great open source compilers.

Two major challenges that we see are:

Compiler improvements are often isolated in separate libraries or one-off repositories without integration into existing tools.
There are high switching costs between quantum computing frameworks and hardware platforms.

To address these, Unitary Foundation has started building the Unitary Compiler Collection (UCC) to foster collaboration and streamline quantum compilation.

Why UCC?

With UCC, we are building a home for quantum compiler experts to develop new passes and at the same time reducing friction for quantum algorithm developers to transition between simulation and hardware.

By surveying the ecosystem, we have begun using the best of open source: integrating performant and user-friendly tools into UCC, creating a platform-agnostic interface with competitive compile time and gate reduction efficiency.

Key Features

1. Best-in-Class Compilation

We benchmark various compilers and continuously improve UCC’s default compilation (currently "UCCDefault1") by integrating passes from existing compilers and developing custom transpiler passes—and we need your help!

Right now, UCC leverages a subset of Qiskit’s transpiler passes optimized with Rust for circuit optimization. We regularly benchmark UCC’s default passes against existing compilers and SDKs to ensure we are capturing the best the ecosystem has to offer to reduce compiled gate counts and runtime.

You can suggest adding a new compiler to our benchmarks or explore the workloads and backends we benchmark continuously here.

2. No Code Changes to Switch Between Frontends

UCC leverages qBraid to support Qiskit, Cirq, TKET, and a growing number of other quantum frameworks, so developers can use their preferred tools to define circuits without rewriting code.

from ucc import compile
compiled_qiskit_circuit = compile(my_qiskit_circuit)
compiled_cirq_circuit = compile(my_cirq_circuit)

3. Compatible with Any Backend Supporting OpenQASM

Not only does UCC accept a wide array of input circuit formats, but it can compile and seamlessly convert between them the return_format keyword – no extra imports needed:

tket_circuit = compile(my_qiskit_circuit, return_format="tket")
qasm2_circuit = compile(my_qiskit_circuit, return_format="qasm2")

Supported return formats also include OpenQASM 2.0 and 3.0, making UCC compatible with major quantum hardware providers, including: IBM Quantum, Rigetti, IonQ, Amazon Braket, and more.

The Future of UCC

We are releasing UCC in its foundational stages because we are committed to building in public and inviting the quantum open source community to shape its development with us.

For development priorities post-launch, we want to focus on what we think is most impactful for the progress of quantum computing – and where we have unique expertise at Unitary Foundation – leveraging our diverse and dynamic quantum open-source community to push into the regime of thousands of qubits, 10s of thousands of gates, where compilers require novel architectures and abstractions to handle errors.

Key roadmap items include:

Quantum Error Mitigation (QEM): Integration with Mitiq, our cross-platform QEM library with 212k+ downloads and 100+ citations.
Hardware-Aware Compilation: Custom routing and scheduling optimized for emerging architectures.
Quantum Error Correction (QEC): Implementing early fault tolerance protocols in conjunction with error mitigation
Hybrid classical-quantum programming: Mid-circuit measurements, fast feedback, repeat-until-success, etc.

We will collaborate with the broader quantum software and hardware communities to develop new abstractions and tooling for the Early Fault Tolerance era. We are grateful to partner with collaborators in the SMART Stack, a DOE-funded project to develop novel approaches in quantum stack design that are Scalable, Modular, cross-platform Adaptable, dynamically Reconfigurable, and error-Targeted. We look forward to collaborating with UF members and the wider Unitary Foundation community.

Help out by contributing to UCC

We’re building UCC as a community-driven project! You can help by:

Get involved and help shape the future of quantum compilation!

GitHub: unitaryfoundation/ucc
Docs: UCC Documentation
Stay Updated: Mailing List

UF Recent Updates

Thu, 27 Feb 2025 00:00:00 GMT

Dear Unitary Foundation community,

Over the past few months there have been some exciting updates in the UF community! We’re now Unitary Foundation, to better reflect the breadth of our work across the open source quantum community; we recently brought 3 new team members on board; and, in case you missed it, we published the results of the most recent QOSS Survey. Check out more below for updates from micrograntees, new open source research, as well as Mitiq, Metriq, and much more.

New from Unitary Foundation

2025 Microgrant Advisory Committee Announced Late last year we announced our 2025 Advisory Committee (with two more members joining early this year). Each year, UF’s advisory committee, composed of dedicated experts from across the quantum technology community, works hand-in-hand with our staff to administer our microgrants. Thank you to our committee for joining us and supporting our mission - we’re excited to be working with you this year!

Welcome to the new UF staff members! At the beginning of this year, we added three new staff members. Changhao Li and Brad Chase joined the technical team, while Veena Vijayakumar joined the operations team.

Research

Unitary Labs Research N. Lambert, E. Giguère, P. Menczel, B. Li, P. Hopf, G. Suárez, M. Gali, J. Lishman, R. Gadhvi, R. Agarwal, A. Galicia, N. Shammah, P. Nation, J. R. Johansson, S. Ahmed, S. Cross, A. Pitchford, F. Nori, QuTiP 5: The Quantum Toolbox in Python. arXiv preprint (2024), [2412.04705]
Other UF Staff Research: T. Gupta, S. Murshid, V. Russo, Somshubhro Bandyopadhyay, Optimal discrimination of quantum sequences. arXiv preprint (2024), [2409.08705]

Mitiq We’ve been seeing continued steady growth for Mitiq. Read more about about new release highlights: In v.0.41.0: Layerwise Richardson Extrapolation (LRE) user guide and tutorial video; Increased LRE compatibility to all supported front ends In v.0.42.0: Probabilistic Error Amplification RFC added; Modular PEC functions now available; multiple Developer, Documentation and Dependency improvements

Metriq Metriq.info got a refresh! Check out some of the UX updates we’ve made on metriq.info site

QLASS UF France is building quantum compilers to run quantum chemistry simulations on photonic quantum processors. Learn more about the grant and our work on the QLASS website

Conferences + Events We Attended

Qiskit Fall Fest, Mexico | Oct 28
OpenForum Academy Symposium, Cambridge, MA | Nov 13-14
DoE SMART Stack Kick-off Call | Nov 1
University of Amsterdam Mitiq RFC project | Jan 8
FOSDEM 2025 Quantum Computing Devroom in Bruxelles | Feb 2
QuSoft Seminar | Feb 7

Q4 Grants

To Abbey Pint and Thomas Cervoni to further develop the Quantum Picturalism Website, which has a mission to expand Quantum Picturalism resources to make quantum math more accessible and inclusive.
To Evan Hockings to further develop QuantumACES.jl, an open-source Julia package for designing, optimising, and simulating scalable Pauli noise characterisation experiments for stabiliser circuits.
To Eric Kuehnke and Daniel Miller to further develop the generation of hardware-tailored logical Clifford gates for stabilizer codes using Gurobi.

Coming up

We have new projects as well as upcoming programs (like UnitaryHACK 2025!) that will be announced in the next few weeks. Stay up-to-date on all things UF and Quantum Open Source Computing by following us on our communication channels!

Other News from the Community

IBM held their Quantum Developer Conference (QDC), and made materials from the event available via the IBM Quantum learning platform.
The Quantify community produced a 0.0.1 version of a backend for LabOne Q and Zurich Instruments. This was done within the framework of the European OpenSuperQPlus project. More info can be found on the OrangeQS blog.
GQuantum Education began outreach to Senior high school, and were fortunate to join WiStem-Gh in their camp. In addition, they launched their e-learning African International School on Quantum Science and Technology for 2025.
Micrograntee Andi Gu’s project “An entanglement toolbox for t-doped stabilizer states beyond the classical simulability barrier” was recently published in APS and the code is open sourced here.

Lessons from Organizing Our First FOSDEM Devroom

Fri, 14 Feb 2025 00:00:00 GMT

Hundreds of people crammed into a classroom at Université Libre de Bruxelles on the first Sunday of February, eager to discuss quantum computing and open-source. Some had to be turned away for safety reasons. This was the reality of the Quantum Computing devroom at FOSDEM 2025—our first time actively organizing it, and a whirlwind experience. We left Belgium buzzing with ideas, enthusiasm for open-source quantum computing, and a renewed appreciation for the power of community-driven development.

<div style="width:100%;"> <div style="float:right;width:40%;margin-left:2em;"> <figure> <img class="not-prose" src="/images/2025_devroom_welcome.jpg"/> <figcaption>Alessandro and Nate (blue) scrambling to get set up as the room filled up, alongside the help of a FOSDEM volunteer (green).</figcaption> </figure> </div> </div>

We learned a lot. Both from our amazing cast of speakers 👏, but also from organizing the event. Before we dive into our recap and lessons learned, a huge shoutout and thank you to all the FOSDEM organizers and volunteers who put on this event every year. There's nothing like it.

Wait, what's FOSDEM? 🤔

For those not familiar with FOSDEM (many people in quantum don't know about it -- more on that later), it's a non-commercial, volunteer-organized European event centered on free and open-source software development. This year was the 25th edition, and in each of the latest editions, there have been more than 8,000 visitors.

Each year there are a lot of devrooms (the equivalent of a track at a research conference), and the Quantum Computing devroom was organized in two past editions in 2019 and 2020 by the Quantum Open Source Foundation, namely by Tomas Babej and Mark Fingerhuth.

For four years, the Quantum Computing devroom took a hiatus, but certainly not because there was no progress in quantum computing. Perhaps the opposite, people were too busy building 🙂. This year we had the honor of organizing it, and we worked to put together a Call for Proposal (CfP), and consequently a schedule.

What we learned 📚

FOSDEM is massive, and running a devroom is no small task. These might be obvious to more seasoned devroom organizers, but we would have benefited from these ahead of time!

Collating an awesome lineup -- Many quantum folks don't have FOSDEM on their radar (yet). If you want a strong lineup, individual solicitations are key to having an exceptional speaker lineup. This year we plan to advertise at our own events to ensure our community is more aware.
Day of logistics -- Purva (our third co-organizer) couldn't make it to Bruxelles, and two people on-site were barely enough. Managing the video stream, helping the speakers with the projector, moderating Q&A, and handling the flow of people entering the room -- it was controlled chaos. Big shoutout to Harshit for stepping in to help!
Prepare for overflow -- The room filled up quickly, and unfortunately, we had to turn people away to comply with FOSDEM's capacity requirements. Hopefully, next year we can secure a larger room.
Meet speakers beforehand -- We met most of the speakers 5 minutes before their talk while they were already standing in front of the room, with a laptop in their hands. A pre-event gathering could warm up the room and foster more community among speakers and attendees alike.
Organizer t-shirts -- (ok, this one is minor) We picked up our organizer t-shirts right before the devroom start on Sunday, and there were only XL and XXL sizes left.

What we'll do differently next time 🐞

Was our organization of the devroom perfect? No! Are we going to organize it again? Absolutely yes! Next iteration, we want to try some ideas. Again, these may not sound like new ideas to more seasoned devroom organizers, but they are things we didn't think of implementing this year.

Fix the schedule gaps -- We scheduled five-minute breaks between talks to ensure we had ample time for transitions and Q&A, but it ended up feeling more awkward than useful. More back-to-back talks or lightning sessions would be better.
Promote the livestream -- FOSDEM devrooms have a livestream for people who can't attend in person. Next time, we want to share a link to the livestream on the usual quantum forums and chats ahead of time.
Monitor the Element chat -- In all honesty, we completely forgot to check the chat until half-way through the schedule. At the end of the day, everything was fine, because there wasn't much engagement there, but here is a note to ourselves to monitor the chat next year.
A Quantum Fringe Event -- A hackathon, meetup, or social event ahead of the devroom could allow more people to get involved in quantum, especially since some couldn't make it in the door!
More Club-Mate -- We definitely didn't drink enough. FOSDEM requires high energy and Club-Mate provides. Plus, it's vegan and gluten-free (not sponsored, but reach out if you work at Club-Mate 😅).
More tourism -- And we don't mean seeing more of Bruxelles attractions (although that would be nice too), but attending more of other devroom's talks, and submerging ourselves more in the spirit of the event. We attended some great keynotes and a few talks in other devrooms, but we wish we had time for more.

What went well 🎯

It's easy to focus on all the things we missed, or we can do better next year, but a majority of items passed over smoothly. Is this in large part due to the amazing infrastructure FOSDEM has set up? Yes, for example, we were glad that we were allocated a Sunday afternoon slot. We had the chance to observe how other devrooms were functioning the day before, and as first-time organizers, we weren't overwhelmed by a full-day slot.

We can take some minor credit too.

Welcome slides -- Alessandro got the room warmed up with a brief history of the quantum devroom at FOSDEM and a (very) brief introduction to quantum computing. Since this is such a new field with many newcomers, this was very important to ensure the following talks could hit the ground running.
Fringe events -- While at FOSDEM, we got to meet awesome people through FOSDEM fringe events (Google Summer of Code meetup, GitHub maintainers social, and of course a FOSDEM favorite: Delirium cafè). In retrospect, we are very happy we found the will to go to these night events.
Audio & Visual -- Besides a small hiccup getting Mac's to connect to the projector, everything provided from FOSDEM worked like a charm. Read the documentation ahead of your devroom, and you're all set to go. The audio&video volunteer staff sitting in front of the room gave us a crisp debrief before we started, which was very helpful.
Balancing theory and practice -- We believe the devroom schedule had a good balance of theoretical and more practical talks, but we would like to hear more feedback about this from the audience. If you attended in person, or watched the livestream, let us know by email or in the comments below what you thought.
No cancellation -- Perhaps this was just luck, but we are still glad none of the speakers had to cancel.

Quantum-specific challenges 🧩

Open-source is deeply ingrained in the quantum tech community, though in a slightly different way than in traditional software. Unlike in classical computing, where open-source and proprietary software coexist more evenly, most quantum software is open-source -- whether it's large frameworks developed by major companies or smaller projects created by individuals. However, we've noticed that the communities around quantum software projects are still relatively small, with most contributions coming from core maintainers and project founders rather than a broad base of external contributors.

There are several reasons for this. First, the quantum software industry is still in its early stages, and many projects haven't had the time to establish themselves as firmly as long-standing classical software projects such as, say, Debian or Firefox. Another challenge is that quantum software can seem intimidating to external contributors, as it is often perceived as requiring deep knowledge of quantum physics. This barrier discourages many potential contributors who might otherwise engage with open-source quantum projects. By organizing a devroom at FOSDEM, we aim to break this misconception and make the field more accessible to a broader audience.

Hacking (not in the cryptographic sense) in quantum computing may not be as straightforward as in classical computing, often requiring access to specialized labs and expensive hardware. As a result, the open-source culture in quantum tends to be more academic and publication-driven i.e. more based on open science and less on the open-source hacker culture that thrives at FOSDEM and in more established areas of computing. We hope that as the field matures, more tools are open-sourced, hardware becomes more accessible, and quantum hacking, as a result, will become an eventuality.

Quantum computing is also still very much an R&D field rather than an established technology. While a classical software developer might spend their spare time hacking together a script to automate their thermostat, manage their finances, or experiment with personal projects, a quantum software developer has fewer opportunities to apply their skills outside of work—aside from conventional software development. Quantum applications tend to be more complex and aren't always aligned with everyday needs. This is just the nature of the field.

Moreover, quantum computing practitioners often need a broad understanding of the entire quantum computing stack, from hardware to algorithms. Redefining the full stack of a new computational architecture is a massive challenge—but also an exciting opportunity to do so in an open-source and transparent way. This year, our devroom lacked some perspectives from the hardware and middleware sides of the field, but we hope to broaden that diversity next year! Open quantum hardware is steadily growing, and we'd be excited to bring more representation from that space into our next year's schedule.

Lastly, we hope next year to not only have the quantum devroom, but to also spread the good word of quantum in other devrooms, where people might find our path of interest. FOSS Funding, Open Research, Python, Open Hardware devrooms could all be good venues for some healthy quantum cross-contamination.

Final Thoughts 💭

<div style="width:100%;"> <div style="float:right;width:40%;margin-left:2em;"> <figure> <img class="not-prose" src="/images/2025_fosdem_room.jpg"/> <figcaption>Our room, all cleaned up.</figcaption> </figure> </div> </div>

We left Bruxelles with more ideas than we know what to do with. Most importantly, we saw firsthand that open-source isn't just a byproduct of quantum research—it's a catalyst for real progress, which we need to continue to push for as our field becomes more commercialized. Seeing so many researchers, developers, and contributors connect has only strengthened our commitment to growing this community.

If you're working on open-source quantum software, let's talk! We hope our proposal for a Quantum Computing devroom gets accepted next year as well, because we plan on making it bigger and better.

Reach out to [email protected] for any question or feedback.

Unitary Foundation 2024 Annual Report

Thu, 13 Feb 2025 00:00:00 GMT

To the UF community,

Unitary Fund got started in June 2018 with a blogpost, $6k, and a microgrant program. At the time, the quantum industry was just emerging. I wrote:

“Quantum computing also remains a place where small teams and open research projects can make a big difference… My thesis for what’s happening here is that we are codifying, in open source software, the mathematics of quantum computing that have been developed over the last few decades. This makes the field more accessible and interactive. It allows us to progress faster, together. It is much more effective to stand on the shoulders of giants when you can import them as an API.”

I still believe this. And I believe it even more for what has happened in quantum technology as a whole sector over the last 6.5 years.

The Unitary Fund experiment has supported the truth of this statement and itself has grown so much. We gave our 100th microgrant last year! I am grateful and encouraged by the many of you who have made this happen so successfully: our supporters, team, advisors, microgrants, community and many others..

With this help, we have expanded beyond our core microgrant program. We now:

staff an in-house technical team working on public goods in quantum tech
develop mitiq: the main cross-platform open source error-mitigating compiler
run metriq: an open source platform for quantum tech benchmarks
run unitaryHACK bounty programs, a community discord, and the major global quantum developer survey
publish research on quantum compilation, benchmarking, and foundations

And much more that you will read about in the full 2024 annual report.

We are now more than a micro-grant fund. All of these programs accelerate our drive to build the open foundation for the quantum technology ecosystem.

To better represent our growth, we've rebranded as Unitary Foundation. Though we have a new name, our mission remains the same:

Unitary Foundation: creating a quantum technology ecosystem that benefits the most people.

We are just getting started,

William Zeng, PhD

President, Unitary Fund

A Warm Welcome to Two New Members of our Microgrant Advisory Committee

Thu, 06 Feb 2025 00:00:00 GMT

Unitary Foundation is delighted to announce that we have added two new members to our advisory committee, Dr. Jamie Friel and Dr. Ying Mao.

Jamie is currently the Technology Manager of Quantum Theory at Oxford Quantum Circuits (OQC), where his main focus is quantum error correction research. Previously Jamie was the engineering manager for OQC's open source compiler, QAT. Before joining OQC, Jamie was a software engineer. He completed a PhD at the university of Warwick in the optimization of magnetic field sensing with NV centers.

Ying is an associate professor and associate chair for Undergraduate Studies in the Department of Computer and Information Science at Fordham University in New York City. He earned his Ph.D. from the University of Massachusetts Boston. His current research focuses on distributed quantum computing, qubit mapping, circuit optimization, and quantum cloud computing systems. His projects have been supported by various public and private organizations, including the National Science Foundation, Google Research, and NVIDIA.

Dr. Friel and Dr. Mao have joined our illustrious committee of advisors who support UF’s microgrant program through participation in applicant review meetings as well as the championing and mentoring of accepted grantees. Welcome both!

Unitary Foundation Joins Open Quantum Design as a Prestige Founding Partner

Fri, 31 Jan 2025 00:00:00 GMT

Unitary Foundation is excited to announce that we are now a partner of Open Quantum Design (OQD), the producer of the world’s first open-source quantum computer.

Alongside pioneers in the Quantum world including Xanadu, the University of Waterloo, and Haiqu, UF has joined OQD’s platform to launch a new level of open access to full-stack quantum computing technology.

Open Quantum Design, a Canada-based nonprofit, is working to accelerate quantum research by democratizing quantum computing - breaking down the traditional barriers between academia and industry. Their team is working to accomplish this by opening up both the hardware and software intellectual property for its trapped-ion quantum computer—the first of its kind—to collaborators looking to participate in a global quantum sandbox.

This partnership allows the open source quantum community new opportunities to participate in and benefit from OQD’s novel approach to education and workforce development. By removing traditional barriers and focusing on solutions to hard problems, this highly collaborative approach is well-positioned to speed-up innovation by pooling global quantum expertise.

OQD’s commitment to democratizing quantum computing, accelerating research, and fueling industry aligns with UF’s continued efforts and initiatives towards creating a quantum technology ecosystem that benefits the most people, including our benchmarking tool, research, community engagement through Discord, and public programming such as UnitaryHACK. We are looking forward to leveraging this partnership to deepen support for our community and the larger Quantum industry.

“It is a pleasure to have a quantum heavy hitter like Unitary Foundation signing onto the work of Open Quantum Design,” says entrepreneur and OQD co-founder Greg Dick, “By sharing resources, knowledge, and designs as a global community, we will accelerate the development of quantum technologies. There are researchers and companies all over the world racing towards the realization of a working quantum computer, and what we are providing through this union with UF and our other Prestige Founding Partners is an open platform to scale progress rapidly where people work, build, and innovate together.”

We are thrilled to be joining this initiative and look forward to continuing to grow the open ecosystem with OQD!

Quantum Computing at FOSDEM 2025

Mon, 13 Jan 2025 00:00:00 GMT

After five years, the Quantum Computing devroom returns to FOSDEM.

FOSDEM (Free and Open Source Software Developers' European Meeting) is the largest gathering about open source software in Europe. This year's iteration is scheduled on the weekend of 1-2 February 2025 at the ULB (Université libre de Bruxelles) Solboch Campus in Brussels, Belgium. It's a free-to-attend event, and if you are in the area, you don't want to miss it!

For the first time since 2020, FOSDEM will feature a Quantum Computing devroom, which is slotted for the second half of Sunday 2 February 2025. We will be in room K.4.401.

The full schedule for the Quantum Computing devroom is available here. Whether you're completely new to quantum computing or already familiar with it, everyone is welcome! If you're attending a "classical" track at FOSDEM on Saturday and are curious to explore Quantum Computing, be sure to visit our devroom on Sunday. After the event, recorded talks will be available at the same link.

We hope to see you in Brussels!

Useful Links

Organizers

If you have a specific request or question, you can reach out directly to the organizers at [email protected]

Announcing Unitary Foundation

Fri, 10 Jan 2025 00:00:00 GMT

Unitary Fund got started in June 2018 with a blogpost, $6k, and a microgrant program. At the time, the quantum industry was just emerging. I wrote:

<p style="font-size: 24px;">Quantum computing also remains a place where small teams and open research projects can make a big difference… My thesis for what’s happening here is that we are codifying, in open source software, the mathematics of quantum computing that have been developed over the last few decades. This makes the field more accessible and interactive. It allows us to progress faster, together. It is much more effective to stand on the shoulders of giants when you can import them as an API.</p>

I still believe this. And I believe it even more for what has happened in quantum technology as a whole sector over the last 6.5 years.

With this help, we have expanded beyond our core microgrant program. We now:

staff an in-house technical team working on public goods in quantum tech
develop mitiq: the main cross-platform open source error-mitigating compiler
run metriq: an open source platform for quantum tech benchmarks
run unitaryHack bounty programs, a community discord, and the major global quantum developer survey
publish research on quantum compilation, benchmarking, and foundations

We are now more than a micro-grant fund. All of these programs accelerate our drive to build the open foundation for the quantum technology ecosystem.

To better represent our growth, we are re-branding as Unitary Foundation: https://unitary.foundation. Though we have a new name, our mission remains the same:

Unitary Foundation: creating a quantum technology ecosystem that benefits the most people.

Want to join us on this mission? Email us at: [email protected]">[email protected]

Will Zeng, Founder and President at Unitary Foundation

On the Impact of Mitiq and its Future

Tue, 24 Dec 2024 00:00:00 GMT

It’s been five years since Mitiq’s journey began—there’s a lot to celebrate, and still so much more to explore.

As we approach the five-year anniversary of the Mitiq project in January 2025, I'd like to reflect on the progress we've made and celebrate its ongoing role in shaping the quantum computing ecosystem. Mitiq was created in early 2020 with the intention to make error mitigation easily available to everyone running programs on quantum computers. Have we achieved this goal? Making QEM easily available to everyone is an ambitious target, but as the adoption metrics below demonstrate, Mitiq has significantly lowered the barrier to using Quantum Error Mitigation (QEM) protocols.

As the field of Quantum Error Mitigation has matured, Mitiq has gained recognition as an important component of the quantum computing stack. While some argue that Quantum Error Correction (QEC) could eventually render QEM obsolete, the two techniques can work in tandem. For example, see Unitary Fund's work demonstrating an approach using Mitiq together with a leading QEC tool, Stim. In a talk at Q2B 2024 John Preskill emphasized that the two approaches will complement one another, even in the long term.

<p style="font-size: 24px;">Error mitigation will continue to be useful in the Megaquop era and beyond.</p>

Preskill's statement underscores the importance of error mitigation and highlight the need for an open-source, platform-agnostic tool like Mitiq to support the growing quantum ecosystem. When Mitiq was first introduced in 2020, the landscape of QEM tools was nascent, with early efforts like pyQuil's measurement error mitigation and Qiskit Ignis paving the way. Since then, the ecosystem has expanded, with Mitiq leading the charge by implementing nine QEM techniques and offering official support for 6 quantum SDKs (and unofficial support for more).

Let's take a closer look at how Mitiq has shaped the field and grown over time.

Adoption and Community Growth

At the core of making QEM available to all, is building a platform-agnostic tool. Whether you're writing your quantum program with Qiskit, Cirq, PyQuil, Qibo, Braket, ..., you can use Mitiq! This has been a major driving force behind the growth and adoption of the project, and allows for users to write QEM code once with the flexibility of running on any (gate-based) hardware. As the only SDK-agnostic QEM tool[^2], Mitiq's adoption metrics provide a clear measure of its utility and impact.

[^2]: To create such a tool in the ever-changing quantum software landscape that does not have an established IR, is, to say the least, a lot of work. In particular the maintenance required to stay up to date with $n$ SDKs and the conversions between them.

Downloads: Over 195,000 total downloads (and counting!).
GitHub Engagement: Mitiq has accumulated over 360 stars, 160 forks, and contributions from 77 developers worldwide.
Scientific Reach: Researchers have cited Mitiq over 120 times since 2020 when the whitepaper was put online.

<div style="display: flex; justify-content: center; align-items: center;" class="side-by-side"> <figure style="text-align: center;"> <img src="/images/2024-mitiq/mitiq.png" width="600" alt="Bar chart of the Mitiq downloads per year from 2020 to 2024."> <figcaption>More than 50% growth in Mitiq downloads year over year!</figcaption> </figure> </div>

The Quantum Open-Source Software Survey this year indicated that 8.8% of respondents were using Mitiq, with an additional 4.3% planning to use it in the next year. This positions Mitiq as the 10th most used tool in the quantum software space—or 5th if all Qiskit tools are grouped together.

In addition to the tools high adoption, the thriving Mitiq community is a testament to the importance of open-source collaboration. From first-time contributors to experienced quantum researchers, everyone has played a role in elevating Mitiq to the tool it is today.

Driving Research and Innovation

Mitiq has been an instrumental tool in advancing research across diverse areas of quantum computing, including benchmarking, quantum simulation, and QEM research. Its easy-to-use API, combined with extensive documentation, has empowered researchers from fields like condensed matter and many-body physics to explore techniques that push the boundary of what's possible on today's quantum hardware. Notable examples include:

Computational physics: Researchers used Mitiq's Zero-Noise Extrapolation (ZNE) functionality to mitigate noise in quantum simulations of Heisenberg spin chains, enhancing fidelity and extending simulations beyond hardware coherence times. [Quantum dynamics simulations beyond the coherence time on NISQ hardware by variational Trotter compression]
Statistical physics: Researchers used Mitiq to demonstrate a reduction in noise during quantum simulations of Bethe eigenstates. To quote the authors (of Algebraic Bethe Circuits):

[Our experiments] highlight the utility of error mitigation. In particular [our experiments] show further evidence that learning based error mitigation is practically useful in reducing the effects of hardware noise.
Condensed matter: Researchers used Mitiq's ZNE functionality to mitigate noise in quantum simulations of lattice gauge models, improving the accuracy of observables on noisy hardware. [Towards the real-time evolution of gauge-invariant $\mathbb{Z}_2$ and $U(1)$ quantum link models on NISQ Hardware with error-mitigation]
QEM research: Researchers used Mitiq to implement and benchmark error mitigation techniques, including Probabilistic Error Cancellation (PEC) and a novel optimization designed for noise-biased qubits. [Low bit-flip rate probabilistic error cancellation]
Machine learning: Researchers compare ML based approaches for QEM against Mitiq's ZNE. [Synergy between noisy quantum computers and scalable classical deep learning]
Benchmarking: Unitary Fund researchers benchmarked Mitiq (ZNE and PEC) across hardware platforms and vendors. Mitiq is currently the only tool available to facilitate such a study. [Testing platform-independent quantum error mitigation on noisy quantum computers]
Software: The Mitiq team faced a new challenge this year in porting ZNE functionality to Catalyst, an experimental compiler framework based on MLIR developed by Xanadu. Projects like this help us stay at the forefront of both cutting-edge research and advancements in quantum software.

By providing an easy-to-use interface for applying error mitigation techniques, Mitiq has significantly reduced the barrier to both use and study error mitigation protocols.

Education and Outreach

Mitiq has not only advanced research but also contributed to education and training in quantum computing. In January 2024 I had the pleasure to interview more than 50 people across the quantum computing industry to discuss the challenges they faced in using quantum computers. This was part of our homework after receiving an NSF POSE award in order to better understand Mitiq's positioning in the larger software/hardware ecosystem, and to identify gaps in tooling. One thing that was touched on by nearly all interviewees who had contributed to Mitiq at some point was how easy it was to get started. We pride ourselves on maintaining a well-documented project (even for developer workflows) and offering informal mentorship opportunities. Our industry needs talent, and Mitiq has played a key role in onboarding individuals with essential skills—such as software development, research, and technical writing—into the field. Some of the key ways that we work to encourage this include:

Documentation: Mitiq has over 100 pages of documentation for our QEM techniques, showing both the theory and practice of applying QEM on real devices. This includes 35 examples to base your next project on as well as a short video explainer of our latest technique.
Presentations: Since Mitiq's inception, Unitary Fund staff, alongside Mitiq contributors have delivered over 50 talks to the scientific and programming communities. This year we presented at the APS March meeting, IEEE QCE, and unitaryCON.
Mitiq workshop: This year we hosted a workshop dedicated solely to teaching people how to use, contribute to, and experiment with Mitiq in conjunction with the QNumerics summer school.
Project mentorship: We've continued to grow our connections with students by mentoring QEM projects through QRISE, the University of Washington's capstone course, and a new project coming soon in conjuction with the University of Amsterdam.

An encouraging indicator of our success in maintaining an easy-to-contribute-to project is Mitiq’s relatively high ratio of contributors to users. With nearly 200,000 downloads and 77 contributors, Mitiq stands out compared to other projects: QuTiP, for instance, has 167 contributors for 2 million downloads, and Qiskit has 592 contributors for 8.5 million downloads.

Looking Ahead

The space is growing... a lot! It's hard to get a sense of project usage from open-source software stats, but when many similar projects are seeing upticks in the number of downloads, it is a stronger signal that tools related to error mitigation/suppression/characterization are in high demand. Below you can see the download number from two other open-source projects, Qermit (error mitigation) and pyGSTi (tomography).

<div class="side-by-side"> <div> <img src="/images/2024-mitiq/qermit.png" alt="Bar chart of the Qermit downloads per year from 2021 to 2024."> <p>Qermit saw a 100% increase in downloads YoY!</p> </div> <div> <img src="/images/2024-mitiq/pygsti.png" alt="Bar chart of the pyGSTi downloads per year from 2016 to 2024."> <p>pyGSTi amassed over 120k downloads in a calendar year!</p> </div> </div>

Two takeaways from these plots are

QEM as a whole is growing, not just Mitiq, and
lots of people are running tomography experiments.

These two facts, taken together with the lack of tooling[^1] to take noise characterization data to inform QEM showcase a gap in our ecosystem. A gap that we hope to (at least start to) fill in the coming year.

[^1]: Unitary Fund staff, in collaboration with researchers at Yale and Iowa State, put forth a method to use noise characterization data to inform QEM with tooling available here. More recently, IBM recently released the a new API: NoiseLearner. These are both excellent examples of using noise characterization to inform runtime, with more work to ensure generality and usability across the quantum stack needed.

In addition to noise characterization making QEM more practical, we've seen two other needs from our community.

On the software side, tooling is needed for QEM technique comparison and combination, and
on the research side, the industry needs a better understanding of how QEM will interplay with QEC.

We hope to make progress on both of these in 2025, and we won't be able to without your help! We need fresh ideas, people writing code, doing research, giving talks, etc. If this sounds like something you're interested in, I encourage you to get involved.

Join the Mitiq Community

Whether you're a researcher, educator, or software engineer, or quantum tinkerer, there's a place for you in the Mitiq community.

Check out the mitiq GitHub repository and contribute by opening issues, asking questions, or making a pull request. If you have a QEM technique you'd like to use, let us know! Feature requests are always appreciated, and encouraged.
Join our Discord community to connect with me and all the other wonderful Mitiq developers and quantum enthusiasts.
Sign up to receive the Mitiq Newsletter to stay up to date with the latest happenings.

Happy holidays and happy new year! Here's to 2025—a year of fewer errors, and better tools.

Unitary Fund awarded EU grant in the QLASS consortium

Tue, 17 Dec 2024 00:00:00 GMT

We're glad to announce that Unitary Fund, through its EU subsidiary, Unitary Fund France, has been awarded a 3-year grant from the European Commission as one of the beneficiaries of the QLASS project.

The QLASS project will develop next generation quantum glass-based photonic integrated circuits, and related software, to explore them as a platforms for quantum computing.
The QLASS project has been awarded a 6M euro grant within the Horizon Europe program, with 680k euro awarded to Unitary Fund France to lead the software development efforts. We will adapt algorithms to run on the specific quantum photonics hardware developed by other partners, designing an end-to-end compilation stack. We will leverage UF expertise in quantum open-source software development to develop algorithms and software to run on QLASS-produced quantum photonics chips, optimizing the process from the algorithmic level down to the compilation, simulation and error mitigation tasks.

The project is coordinated by Dr. Giulia Acconcia from the Polytechnic University of Milan. The collaboration brings together many European players of research and development in quantum science and technology based in Italy, France, and Germany, from public ones (Politecnico di Milano, Fondazione Politecnico di Milano, University of Montpellier, CNRS, University of Rome La Sapienza) to private players (Ephos, Unitary Fund France, Pixel Photonics, Schott AG). More information can be found in the recent press release. The project matches competences and capabilities from academic partners, dynamic startups and SME environments and includes a large industry player, all with complementary roles in the project, from the glass fabrication of the photonics chips to their characterization and operation, including the development of specific software. The application that will be investigated and benchmarked in the QLASS project includes the design of algorithms to design next generation Lithium ion batteries.

UF will leverage its experience in building software projects such as Mitiq, the most widely used open-source toolkit for practical quantum error mitigation, and ongoing projects in the compiler space. Mitiq is a cross-platform error mitigation compiler, run on various quantum hardware from ion-trapped devices to superconducting circuit-based devices. In the past, Unitary Fund has also been involved in the development of software aimed at specific architectures, such as neutral-atom based quantum processing units in the Pulser and Aquapointer projects. The focus on photonics-based quantum processing units is a first for Unitary Fund.

You can keep up to date with the QLASS project by looking at its website news or following its LinkedIn account.

2024 Quantum Open Source Software Survey Results

Mon, 09 Dec 2024 00:00:00 GMT

Unitary Fund is thrilled to be publishing the results of this year's Quantum Open Source Survey! Now in its third iteration, we hope this screenshot of our community, who we are, what tools we use, where our strengths lie, and how the field is changing, will provide illuminating and actionable insights as we look to develop a quantum ecosystem that is the most useful to the most people.

Thank you to our open source community for their input, answers and participation! We continue to be amazed at the tools being developed all the time that push the science forward in ways both big and small. Thank you as well to our amazing donors, members and board, without which this would not be possible.

You can find the results at this link.

Introducing the Unitary Fund’s Advisory Board 2025

Mon, 25 Nov 2024 00:00:00 GMT

Each year, Unitary Fund’s advisory board, composed of experts from across the quantum technology community, works hand-in-hand with our staff to administer our microgrants. . This dedicated team plays a key role in sourcing and reviewing grant applications, mentoring groundbreaking projects, and providing invaluable technical guidance for the open source ecosystem. With expertise spanning the entire quantum technology stack—including hardware, programming languages, quantum machine learning, open quantum systems, quantum compilers, and beyond—they bring unparalleled knowledge and passion to every aspect of our mission.

We are thrilled to announce the members of the Advisory Board for 2025!

Meet the Advisors

Stephen DiAdamo Stephen DiAdamo completed his Ph.D. at the Technical University of Munich and has received two Unitary Fund grants for his work on software for quantum networks. Before co-founding Qoro Quantum, he worked as a research scientist at Cisco, focusing on network technology.

Sonika Johri Sonika Johri has worked in the quantum industry for over a decade and has authored > 30 publications in leading peer-reviewed journals. She was a Principal Researcher at IonQ, where she ran the quantum applications research group, and prior to that a Research Scientist at Intel. She holds a PhD in theoretical physics from Princeton University. Her work centers around translating the rapidly expanding capabilities of quantum hardware into measurable advantages for end users of quantum computing. She is currently founder of the startup Coherent Computing Inc which is building software to enable cutting-edge quantum applications.

Ryan LaRose Ryan LaRose is an Assistant Professor at MSU-Q (in CMSE, ECE, & PA), previously a postdoc in the Computational Quantum Science Lab at EPFL.

In 2022, he received a PhD in Computational Mathematics, Science, and Engineering from MSU along with an Engineering Distinguished Fellowship, Fitch H. Beach Award for Outstanding Graduate Research, and NASA Space Technology Graduate Research Fellowship.

In 2017, he received a BS with Distinction in Mathematics and Physics from the University of Michigan, Ann Arbor.

He does research in computational physics and quantum information science. He’s interested in both the physics of computation and the computation of physics - that is, what quantum physics can tell us about information and computer science, and how quantum computers can solve practical problems in physics and related fields.

Roger Luo Roger is a scientific software engineer at QuEra Computing Inc., where he leads open-source initiatives for quantum physics, compilation and tooling. He received his PhD from the University of Waterloo in 2024. A recipient of the 2020 Wittek Quantum Prize, he is one of the creators of Yao and several foundational packages in the Julia ecosystem, with significant contributions to the Julia, CUDA.jl and PyTorch. His theoretical research explores the application of modern programming paradigms and machine learning in quantum many-body physics.

Daniel Mills Dan Mills is a research scientist in the compiler team at Quantinuum, having previously completed a PhD in quantum computing at the University of Edinburgh. He is broadly interested in software driven techniques for extracting power from near term quantum devices, but is particularly active in circuit optimisation, error mitigation and characterisation, and distributed quantum computing.

Ryan Shaffer Ryan Shaffer is an applied science manager at Amazon Web Services, where he leads a team of scientists and engineers building tools for writing and running programs on quantum computers through Amazon Braket. He received a PhD in physics and quantum computation from UC Berkeley. He has previously worked at Microsoft, Meta, and Sandia National Labs.

Sukin (Dylan) Sim Sukin (Dylan) Sim is a Senior Quantum Applications Architect at PsiQuantum, where they develop techniques and software for compiling algorithms for fault-tolerant quantum computers. More generally, they are interested in developing ways, usually through simple toy-model simulations, to more easily explain and understand difficult concepts in quantum computing.

Christa Zoufal Dr. Christa Zoufal is a quantum applications researcher in the Quantum Technology group at Quantum. In 2021 she received her PhD in Physics from ETH Zurich for a thesis on Generative Quantum Machine Learning. In her current research she focuses on advancing algorithmic and verification methods for quantum machine learning and quantum simulation both from a theoretical and from an empirical point of view. Additionally, she has served as advisor to the Unitary Fund Microgrant program since 2020.

Teaching Learning, Teaching Science in High Schools

Mon, 25 Nov 2024 00:00:00 GMT

I start out every session with the question, “What does it mean to learn?”. I ask the students to raise their hands if they think they have a good grasp on what learning means. Oftentimes, students respond by timidly glancing over at their peers; perhaps in their minds, this should be an easy question. In the end, only a few tight-angled elbows eventually stretch hands into the air.

Thanks to the Unitary Fund’s financial support, I have been able to travel to high schools in Florida and Massachusetts over the past few years, giving workshops on the latest scientific developments in machine learning and quantum computing. As a researcher at the intersection of these areas, I enjoy sharing recent advances with young students. The objective of these workshops is to spark curiosity in the students. It’s not to teach them how to code up a machine learning algorithm or how to build a quantum computer; I only get 50 minutes with them - the goal is to get them excited to think about the science.

To achieve this, I ask questions that probe them to make a connection between their everyday experiences and the concepts I’m presenting on. The first concept I emphasize is data - something integral to both machine learning and quantum computing. When I ask them what they think data means, I usually get a textbook definition similar to “information about something that is useful.” That’s a pretty good general definition, but when I ask them to give me examples, there are many blank stares. I then ask, “How many of you select movies to watch on Netflix?”. Hands shoot up. “How many of you get your blood pressure checked when you go to the doctor?” I see all hands up. “How many of you… speak words to each other?” I get chuckles with raised hands. Data is all around them - it’s about helping them become more aware of that.

We spend time talking about some of the latest learning models from image generation to large-language chatbots, highlighting that these models are good at pattern recognition. I ask the students, “Who can tell me a pattern that exists within our language?” One girl raised her hand and said dubiously, “Every word has a vowel?” I smiled at her, “What a cool answer.” Other students identified patterns that ChatGPT does pick-up on, such as grammar rules and contextual inferences.

When I started giving these presentations in September of 2022, maybe one or two kids would raise their hands when I asked whether or not they’d heard of generative AI - now it's a common concept. Because of this, I get to probe their trust in ChatGPT and their general concerns about AI based on what they’ve previously learned. From my observations, students trust that ChatGPT’s accuracy is between 50%-75%. Some have personally witnessed ChatGPT’s hallucinations. For example, ChatGPT’s error in making up character names from Kurt Vonnegut’s short stories when generating an English essay. The student learned a powerful lesson with that one. On average, the students are concerned about how AI is going to impact their future - one student struck me with a really nerve-racking question: “Is there general regulation on how intelligent we make this technology?”

I always end by introducing the idea of a quantum computer - a device that we might be able to use to do better or faster machine learning. This was my PhD area of expertise. Most of the students I engage with are not familiar with a quantum computer, and this leads to some of the most interesting questions! “How do these computers copy data if it goes away when you measure it?” “How exactly do you get an atom to stay still?” “How does a particle store information?” When I show an image of a single atom, I’ve had students jump out of their seats in surprise!

From all of these visits, I’ve learned a lot about student’s current perception of science, and how this influences their curiosity.

The first is probably not a surprise anymore - students build their own conceptions of who scientists are based on examples in their everyday lives. I had more than one student tell me that they were just happy to meet a scientist who has a similar background to them (I am both first generation and identify as female) and is passionate about what they do; one girl told me that I was “real life Barbie”. I felt grateful that I could be that example for her.

The second is that generally students are curious about the world around them, but many don’t associate this curiosity with science. Groups of students informed me that they hate science because they associate it with boring worksheets and imposed science fair projects. Few students overall seemed to have the awareness that the intention of science is actually to describe how everything that exists around them (and inside of them) works.

Lastly, many students feel that science has been solved. They’ve grown up learning about the mechanics of trains and the forces of gravity, and they think there is nothing more to discover. I remind students that these are models, and while they are widely accepted for having lots of evidence, we may still find improvements. As scientists continue to ask questions and learn, our models improve. Our models are always learning too.

Some theorists are still working on older physics problems: time travel, integrating gravity with quantum mechanics, and the age of the universe. And now, we are teaching quantum particles to learn patterns and observing patterns of cultured neuron cells in the lab. With respect to all that humanity could understand, we right now understand very little. There’s a lot of work to be done.

If anything, I hope these experiences encourage other passionate scientists to visit local K-12 schools and spark some curiosity. Taking an hour to do this can make a huge, meaningful difference for both you and them. Also, I hope others will join me in considering my favorite question: What does it mean to learn? Perhaps in the end, our conclusions will be similar - that learning and doing science are actually one in the same.

Just in time for just-in-time error mitigation: Mitiq meets Catalyst

Mon, 18 Nov 2024 00:00:00 GMT

This blog post is a summary of a partnership between Unitary Fund and Xanadu to integrate quantum error mitigation techniques from Unitary Fund's Mitiq into Xanadu's PennyLane Catalyst compiler.

Just-in-time compilation

We all want faster computer programs. Just-in-time (JIT) compilation has been a key concept in classical compiler design to help achieve faster computer programs. The basic idea behind a JIT compiler is that it observes the program running and optimizes it based on those observations. Most modern programming languages and runtime environments nowadays support some kind of JIT optimization techniques. In fact, very recently, an experimental JIT compiler was added to Python in its latest 3.13 release.

We all want faster quantum computer programs. Just as JIT compilation accelerates classical programs, similar techniques can be applied to quantum computing for boosting performance. Catalyst is a JIT compiler framework developed by Xanadu to speed up quantum programs written with their PennyLane library. If you have a PennyLane program, you can easily decorate it with some simple Catalyst syntax and, in many cases, you have a faster quantum computer program.

What we also want is more accurate quantum computer programs – accurate enough to be useful for the application or the experiment we seek to run. Quantum error correction is making significant strides, but it still introduces substantial overhead that can be impractical for near-term applications. We look at the more practical techniques of quantum error mitigation to make our quantum programs more accurate. Unitary Fund's own Mitiq project provides a Python package for applying error mitigation techniques to quantum programs.

Just-in-time compiling error mitigation routines

Even though Mitiq can be used with PennyLane programs, there was no seamless integration of error mitigation routines into the Catalyst compiler (or into any quantum JIT framework, as far as we know.) In the last few months, Unitary Fund and Xanadu have partnered to port Mitiq's error mitigation techniques onto Catalyst. The natural starting point was Zero-Noise Extrapolation (ZNE), which is the most popular error mitigation technique in Mitiq, and arguably the simplest to implement, yet it can be very effective.

Romain Moyard and the Xanadu team had already implemented a basic version of ZNE in Catalyst. The Unitary Fund team took it from there, and extended it with additional options. The gist of ZNE is that it estimates the ideal result of a quantum program by

Stage 1: Executing the program at increased noise levels
Stage 2: Extrapolating back to the zero-noise regime.

If you want to know more about the theory behind ZNE, check out Mitiq documentation.

We worked on the full Catalyst stack and added the following options to the respective stages of ZNE:

Local folding – Instead of applying noise scaling globally to the entire circuit, noise level increments can now be applied to individual gates, providing finer control over the noise scaling process.
Exponential extrapolation – An exponential function is fitted to the execution results of the noise-scaled programs, whereas the previous option only allowed for polynomial extrapolation. Exponential extrapolation can be advantageous in certain noise models where the error compounds exponentially with noise scaling.

Why is this important? It turns out that, depending on the underlying noise models, some folding techniques and some fitting techniques may perform better than others. In complex noise environments, having the flexibility to choose the most effective folding and extrapolation methods can significantly improve error mitigation outcomes. The more complex the noise model is, the more impactful it is to have such a level of customization in ZNE. Should this blog post inspire you to become a better ZNE practitioner, check out this review paper for how to make the most out of all the ZNE options.

One crucial aspect of how ZNE is compiled in Catalyst is that all folding transformations take place while preserving the high-level structure of the original program, that is, conditionals and loops aren't unrolled. This allows the compiler to maintain a compact version of the program even after applying error mitigation.

Noisy simulation on Catalyst

After implementing these new folding and extrapolation options, it was time to test them. Catalyst programs can already be run on Amazon Braket, and error mitigation can be leveraged to attenuate the hardware noise there. Running on real hardware can be time- and money-expensive though. We needed a workflow to quickly smoke-test the new features, and for that, we turned into adding a simple depolarizing noise model to Unitary Fund's in-house simulator Qrack. If you missed Dan Strano's post on Qrack integration with Catalyst, go and check it out! Qrack is now the first quantum simulator implementing a noise model, as well as integrating with a JIT compiler framework.

Across the Catalyst MLIR stack

In order to implement all the new features, we touched across all layers of Catalyst's architectural stack, which is based on JAX and MLIR (Multi-Level Intermediate Representation) frameworks. Check out Catalyst's architecture guide for motivations behind the stack, and how it is arguably a great fit for implementing a JIT compiler for (hybrid) quantum programs, which also have support for things such as automatic differentiation. For those familiar with MLIR, an interesting note is that the error mitigation routines are organized in their own dialect in the Catalyst stack.

Did I tell you how much we learned? For the Unitary Fund team, this project was our first venture into the JIT world and the frameworks that come with implementing it. In fact, understanding MLIR gave us deeper insights into compiler design for quantum programs in general as well. I am not going to lie; it was all a bit daunting in the beginning, but it was incredibly rewarding!

Of course, there are always more options and more error mitigation techniques that we want to bring to Catalyst and to JIT compilation. We also want to expand Qrack with more sophisticated noise models. This is just the start, and stay tuned on this blog for updates.

If at this point, you are intrigued by just-in-time error mitigation and want to give it a try, read the documentation, run the tutorial, check out the Catalyst repository. Remember it's all open-source, and you are just in time to contribute!

What algorithms exist to emulate quantum computers?

Fri, 01 Nov 2024 00:00:00 GMT

If you have any interest in using quantum computers today, you might have considered what it takes to simulate one (on a laptop or desktop), since fault-tolerant quantum computers are currently a rare and expensive commodity, to say the least. "Simulation" of a quantum computer might include modeling noise and pulse-level control processes, in order to better understand prototype quantum computer hardware; "emulation" is anything that gets us closer to providing the utility of a quantum computer, without a quantum computer, with rather just a desktop, laptop, or even mobile (or any other) "classical" computer device on hand.

Many experts divide the existing set of "well-known" quantum computer simulation and emulation techniques into "Schrödinger picture" and "tensor networks" (descending in part from von Neumann's density matrices). As for what typifies "Schrödinger picture," it basically boils down to state vector simulation (according to many others). The truth is, state vector simulation is a very simple algorithm that relies on "Schrödinger picture" interpretation or approach to quantum theory, but it is far from exhausting the extent of possible useful algorithms in the category.

Say that I ask you to simulate a circuit that produces state |control> from |0>; you do this by any means you deem fit and give me state |experiment> as output; I check that |<control|experiment>|<sup>2</sup>=1`. Why does this specifically have to occur via only state vector simulation or (von Neumann's) tensor networks? It doesn't.

By the way, we could even relax the |<control|experiment>|<sup>2</sup>=1 condition. (That is "Schrödinger picture," to grant a fair point.) In cases, we could relax the condition to say, "Simulation (or emulation) provides a reusable function that accurately generates measurement shots (without bias) from the distribution of measurement in some arbitrary but user-selected basis, from a circuit definition that should produce |control> (according to my full knowledge of |control> and that |<control|experiment>|<sup>2</sup>=1, following the Born rules)."

While they are also "Schrödinger picture" (if we are limited in their modification and adaptation to our own purposes), at least "quantum binary decision diagrams" (QBDD) and "(near-)Clifford" families of simulation algorithms also exist, which can represent and compute on restricted or universal state spaces within a qubit Hilbert space. There are also other potential optimization approaches on Schrödinger picture that could constitute meaningful topics of study in themselves, I say as lead author of the Qrack simulation framework.

"Quantum binary decision diagrams" (QBDD) consider the quantum state to be the (multiplicative) product of “n” successive (superposed) decisions between |0> and |1> for n qubits. Each |0> and |1> possibility carries its own complex scale factor. It is possible to demand that each and every branch pair of |0> and |1> decision possibilites that share the same immediate parent node all locally normalize to 1.0 or 100% overall probability between these two options within each binary decision (but some additional complexity savings might be possible by relaxing this hypothetical condition and "telescoping" multiple levels of decision scale factors in local regions of the tree). The amplitude of a state {|0>, |1>}<sup>⊗n</sup> is given by the product of |0> or |1> scale factor at each and every level of the tree. If a scale factor is 0, we terminate the branch at that point (compressing the tree). If two subtrees are the same, we replace their root branches with a “pointer” to the same subtree, reusing memory (and compressing the tree). Additionally, there is a global normalization condition, that the |0>-most branch with nonzero scale always carries phase angle 0 (up to non-observable global phase offset).

"Near-Clifford" simulation expands stabilizer simulation to encompass universal quantum computation. As you might know, according to Gottesman-Knill theorem, stabilizer tableau (as per Scott Aaronson's CHP simulator) is efficient for Clifford algebra, which can represent superposition and entanglement but not general universal quantum states or computation. However, as near-Clifford simulation is done (rather uniquely) in the Qrack simulator framework, “magic” gates like T or RZ can be injected via “gadgets.” If a gadget ancilla is rotated to a specific basis and post-selected for |0> measurement outcome, no semi-classical correction is needed to complete the action of "magic state injection gadgets": post-selection can be deferred until immediately at logical measurement. As such, it becomes possible to represent general universal states entirely in terms of just stabilizer tableau, terminal single-qubit universal unitary buffers at the end of "circuit wires," and a guarantee that ancillary gadget qubits will collapse to |0> state when measured (which can be enforced without cost penalty in simulation). To calculate specific logical qubit amplitudes or generate logical qubit measurement samples, it becomes necessary to execute an auxiliary state vector simulation for which the qubit width grows like the number of "magic" RZ gates.

Other significant algorithms in emulation are not limited to state vector or ("conventional") tensor networks and can exhibit drastically different special-case behavior and implementation. (Feynman techniques, like path integrals, are another major category, though they are currently not implemented in my work with Qrack.) For example, Qrack uses "Schmidt decomposition" liberally, for an effect like "future light-cone" optimization. Think of a reset |0><sup> ⊗n</sup> state as a set of n 2-state systems for n qubits. Starting from that point, defer Kronecker products between separable subsystems until they become absolutely necessary to order to account for the effects of coupler gates like CNOT or CZ. We can further introspect that state for more separability, like if either |0> or |1> eigenstates occur as a control for CNOT. Say we have a |0> control state: then CNOT has no effect, so we can replace the coupler with "identity" or "no-operation." Say that we have a |1> control state: then CNOT has the same effect as just an X gate on the target qubit, so we don’t need to entangle.

Think of what you could do with this "zoo" of techniques that's beyond state vector simulation and out of easy reach of conventional tensor network approaches! For example, see Qrack's QBDD suite of example scripts. Through a combination of all of QBDD, near-Clifford, Schmidt decomposition for "future light-cone optimization," and another "tensor-network-like" simulation "layer" that locally optimizes circuit definitions and provides "past light-cone optimization" from point of measurement, Qrack is able to simulate 49-qubits-by-6-depth-layers on a nearest-neighbor topology, "orbifolded" to connect top-to-bottom and left-to-right sides of the virtual chip as a horn torus (or with comparable performance on the 2019 Google Sycamore "quantum supremacy" experiment chip topology and circuit generation protocol) to 2^(-20) empirically observed per-gate infidelity in about 43 minutes per measurement shot in just under 2 GB of memory with 1 vCPU thread (on an AWS EC2 c7g series virtual machine), for an overall cost of about (USD) $0.02(6) per shot. State vector would (naively) appear require 4-to-8 petabytes of memory to do the same (and I don't think I can fit that in my home PC), while tensor network contraction paths would likely require significant optimization or training to reproduce this performance, which instead comes "turn-key" or "push-button" from first principles of diverse and synergistic simulation techniques.

Get creative, and keep an open mind! Most of what I (personally) see as this "colloquial orthodoxy" of state vector versus tensor networks do is lead us to forget that QBDD and near-Clifford techniques (at least) exist as distinct algorithm types with potential for universal representation that are markedly different in operation and application from state vector, as another tool in the toolbox. Remember that the result of quantum computer simulation or emulation has tight quantitative bounds and specific statistical definition for what constitutes a correct simulation, but basically the only part of the potential simulation algorithms that's written in stone is recreating the I/O interface of a quantum computer. Maybe you'll be the next researcher to come up with a totally unique quantum computer simulation algorithm!

Welcoming two new members to the Open Quantum Benchmark Committee with Metriq

Thu, 24 Oct 2024 00:00:00 GMT

We are excited to welcome two new members Ed Younis and Peter Groszkowski to the Open Quantum Benchmark Committee with Metriq. The Committee was established earlier this year to provide the community with a comprehensive and reliable framework for evaluating quantum computing systems through Metriq (https://metriq.info/), a free and open-source platform to facilitate quantum computing benchmarking. Metriq gives researchers and developers a centralized hub to submit results, propose new benchmarking tasks, and have openly accessible data.

Ed Younis is a computer systems engineer at Lawrence Berkeley National Laboratory with extensive experience developing and implementing advanced algorithms for quantum compilation, such as QFAST and Qfactor. He is currently the principal engineer on the BQSKit project and has research interests in quantum synthesis, compilation, and software systems.

Peter Groszkowski is a researcher at the Oak Ridge National Laboratory working in various areas of physics, with emphasis on topics related to quantum computing and information. Beyond physics, he is also interested in all aspects of software development, ranging from numerical simulations to instrumentation control. Peter is a strong advocate of the open-source development model, supporting it whenever possible.

QCoder - A platform for quantum competitive programming

Mon, 21 Oct 2024 00:00:00 GMT

In recent years, quantum algorithms have attracted attention for their theoretical promise of significant efficiency gains. Shor's algorithm, for example, can factor integers with exponentially fewer queries than known classical algorithms. Learning about these algorithms is exciting, but staying motivated can be challenging, especially for those without an academic background who are learning for fun. Textbooks and academic papers are often too complex for beginners, making it hard to follow along. Even if you succeed in understanding and implementing an algorithm, running it on today’s quantum computers in scalable settings is typically impossible.

In response to these challenges, we have developed QCoder, a platform for quantum competitive programming. QCoder is the quantum counterpart to conventional competitive programming platforms such as Codeforces, Google Code Jam, and ICPC. Our platform simplifies complex quantum algorithms by breaking them down into manageable components, with each problem focusing on a specific concept. This progressive approach allows users to start with simpler tasks and gradually progress to more advanced challenges. Through competition, participants can gradually build their understanding of quantum algorithms and improve their quantum programming skills in an engaging and structured way.

Sample Problem

To give you a taste of what the platform offers, let's walk through an example problem. Please note that this is just one example, and we offer both easier and more challenging problems. You can explore and choose the one that suits your level by visiting QCoder.

Problem Statement

You are given an integer $n$, representing the number of qubits. Your task is to implement a quantum circuit with minimal circuit depth that prepares a GHZ state using $n$ qubits.

The GHZ state is defined as $$ \ket{\mathrm{GHZ}} = \frac{1}{\sqrt{2}} (\ket{0\cdots0}_n - \ket{1\cdots1}_n). $$

The submitted code should follow the format below:

from qiskit import QuantumCircuit
 
 
def solve(n: int) -> QuantumCircuit:
    qc = QuantumCircuit(n)
    # Write your code here:
 
    return qc

Solution 1

<details> <summary>Open</summary> The most straight forward solution can be described as follows:

First, apply the Hadamard gate to the first quantum bit. $$ \ket{000 \cdots 0} \xrightarrow{H(0)} \frac{1}{\sqrt{2}} \lparen \ket{000 \cdots 0} + \ket{100 \cdots 0} \rparen $$ Next, we transform the state $\ket{100 \cdots 0}$ to $\ket{110 \cdots 0}$. To achieve this, apply a controlled-X gate (CNOT gate) with the first quantum bit as the control bit and the second quantum bit as the target bit: $$ \frac{1}{\sqrt{2}} \lparen \ket{000 \cdots 0} + \ket{100 \cdots 0} \rparen \xrightarrow{CX(0,1)} \frac{1}{\sqrt{2}} \lparen \ket{000 \cdots 0} + \ket{110 \cdots 0} \rparen $$ By continuing to apply the controlled-X gate until the $n$-th qubit is the target bit, we can prepare the GHZ state. $$ \frac{1}{\sqrt{2}} \lparen \ket{000 \cdots 0} + \ket{110 \cdots 0} \rparen \xrightarrow{CX(0,2)} , \cdots \xrightarrow{CX(0,n-1)} \frac{1}{\sqrt{2}} (\ket{0...0} + \ket{1...1}) $$ Summarizing these operations, we obtain the following circuit when $n = 4$:

Below is a sample program:

from qiskit import QuantumCircuit
 
 
def solve(n: int) -> QuantumCircuit:
    qc = QuantumCircuit(n)
 
    qc.h(0)
 
    for i in range(1, n):
        qc.cx(0, i)
 
    return qc

</details>

Solution 2 [advanced]

In the solution 1, the depth of the quantum circuit is $n$. What kind of quantum circuit should be designed to further reduce the depth of the quantum circuit?

Let's examine the following example with 8 qubits.

In this case, the operations within each block, divided by the boundaries on the quantum circuit, act on different qubits, allowing them to be executed simultaneously. Therefore, the depth of each block is 1. Thus, the depth of the quantum circuit above is 4.

By generalizing this circuit, the depth of the quantum circuit becomes $\lceil \log_{2}{n} \rceil + 1$, which satisfies the constraint of reduced depth.

Below is a sample program:

import math

from qiskit import QuantumCircuit


def solve(n: int) -> QuantumCircuit:
    qc = QuantumCircuit(n)

    qc.h(0)

    for i in range(int(math.log2(n)) + 1):
        for j in range(2**i):
            if 2**i + j == n:
                break
            qc.cx(j, 2**i + j)

    return qc

</details>

Note

Almost the same problem was featured in the QCoder Programming Contest 002. In Problem A3, both solutions 1 and 2 are accepted. However, in Problem A5, only Solution 2 is accepted, as it meets the stricter depth constraints. If you're interested, feel free to submit your solution and see how you do! Can you find a shorter circuit?

Getting Started

If you're interested in exploring the platform, you can join by following the steps below:

Step 1: Environment Setup

We currently support Qiskit as the available quantum programming language. For the best coding experience, we recommend setting up a local Qiskit environment on your computer. This setup will provide useful features such as autocompletion and linting to improve productivity and code quality.

To get started, please refer to the official Qiskit documentation for detailed installation instructions and guidelines.

Step 2: User Registration

To participate in contests and submit your solutions, you need to sign up via the registration page.

Step 3: Dive In and Enjoy!

You now have access to all the content on QCoder. We suggest starting by participating in past contests. While you may find some parts difficult initially, you'll gain a deeper understanding as you solve problems and refer to the provided editorials. QCoder offers contests for everyone, from complete beginners to seasoned experts.

Conclusion

QCoder is a quantum competitive programming platform, offering opportunities to challenge and advance your skills in quantum computing. We are excited to announce that our 3rd contest, QCoder Programming Contest 003 (QPC003), will take place on November 3rd, from 8:00 AM to 11:00 AM (GMT+0). We look forward to your participation!

We would like to express our sincere gratitude to the Unitary Fund for supporting the internationalization of this project. We are actively seeking support to continue providing this platform to the quantum computing community. If you're interested in collaborating or offering support, please reach out to us through our contact page.

Aquapointer, a software package for quantum biology applications

Thu, 17 Oct 2024 00:00:00 GMT

Project overview

Aquapointer is an open source software library developed by the Unitary Fund team with consortium partners Pasqal and Qubit Pharmaceuticals as part of the AQUA project. The project was funded by Wellcome Leap through the Q4Bio program, a research program with the goal of accelerating the applications of quantum computing in human health. The Aquapointer library is a generalized, automated version of the framework developed over the course of the AQUA project, which is detailed in a recently published paper [^1]: Leveraging analog quantum computing with neutral atoms for solvent configuration prediction in drug discovery. Aquapointer is designed as a computational tool for use in the pharmaceutical discovery and development process, specifically for leveraging quantum computing resources in the prediction of the locations of water molecules in protein cavities.

Proteins are complex molecules with cavities that can be occupied by water molecules, particularly in living tissue. The presence of water molecules influences the binding of small molecules called ligands to specific protein sites, a problem of interest in drug discovery. Protein solvation effects can be studied either by modeling the interactions experimentally, which is generally a costly and relatively inefficient process, or by using numerical models. Classical numerical methods such as Monte Carlo or molecular dynamics can give some insight, but the computational complexity of these methods can be too large for certain hard cases.

Solving the protein cavity solvation problem

An alternative approach to finding the locations of water molecules is to perform classical simulations first to find the density distribution of water molecules, as represented in the image below on the left, through methods such as the 3D Reference Interactive Site Model (3D-RISM) [^2]. Using the 3D-RISM density function obtained in the previous step, we can define a discrete optimization problem whose solutions correspond to positions of water molecules, the combined results of which (3D-RISM and optimization) are depicted in the image below on the right. Image credit: AQUA project team

We found that the best formulation of the discrete optimization problem with solutions corresponding to positions of water molecules is a quadratic unconstrained binary optimization (QUBO) problem. The QUBO problem is a combinatorial optimization problem with numerous applications across a broad array of disciplines, including finance, economics, physics, and computer aided design [^3], as well as in the medical field, such as in diagnostic image classification [^4]. Furthermore, the close connection between the QUBO problem formulation and the Ising model make it a promising application for analog quantum computers. To find the locations of water molecules in the protein cavity, we solve the QUBO formulation of the Gaussian mixture problem, where the center of each Gaussian corresponds to a location around which a water molecule oscillates. In the image below, the QUBO formulation of the Gaussian mixture problem is illustrated by side-by-side plots of the same density distribution as color contours with each center marked by a red X, the one on the right overlaid with initial guesses for the centers of the Gaussians, each marked by a blue X.

Image credit: AQUA project team

Aquapointer automates the pipeline of 3D-RISM density distribution to water molecule locations

To find the locations of water molecules in a protein cavity of interest, Aquapointer generates 2D slices of an input 3D-RISM density function, maps the slices to a QUBO problem, translates the QUBO to an analog pulse sequence or a digital circuit, and then calls the backend API and processes the results. The analog workflow in Aquapointer uses Pulser for intermediate representations (IR) of the pulse sequences and for interfacing to supported backends, e.g. QuTiP. The digital workflow uses Qiskit for IR and simulated backends.

Image credit: AQUA project team

water_postions = find_water_positions(canvases, executor, MockDevice, pulse_settings)

Extending the library

Since we first introduced Aquapointer, we have upgraded it to include 3D-RISM density processing, in the form of the slicing and densitycanvas modules. The slicing module takes a 3D-RISM density file and transforms it into 2D slices along user-specified planes. The densitycanvas module contains classes and functions for transforming the 2D slices or generating them from a probability distribution and mapping the density distributions into a QUBO formulation.

Image credit: AQUA project team

canvases = canvases = density_slices_by_planes(grid, slicing_points)
for canvas in canvases:
    canvas.filter_density(filter_settings={"filter_function": filter_fn, "sigma": sigma})
    canvas.crop_canvas(center, size)

We have also created a template script for automating the workflow from 3D-RISM input file to positions of water molecules obtained from solving the QUBO. For more information, check out Aquapointer's documentation, and be sure to stay connected with Unitary Fund on our Discord, X, and LinkedIn.

[^1]: Mauro D'Arcangelo, Louis-Paul Henry, Loic Henriet, Daniele Loco, Nicolai Gouraud, Stanislas Angebault, Jules Sueiro, Jerome Foret, Pierre Monmarche, and Jean-Philip Piquemal. Leveraging analog quantum computing with neutral atoms for solvent configuration prediction in drug discovery. Phys. Rev. Res 6(4), (2024) online). [^2]: Daniel J Sindhikara and Fumio Hirata. Analysis of biomolecular solvation sites by 3D-RISM theory. J Phys Chem B Jun 6;117(22):6718-23 (2013) online. [^3]: Gary Kochenberger, Jin-Kao Hao, Fred Glover, Mark Lewis, Zhipeng Lü, Haibo Wang, and Yang Wang. The unconstrained binary quadratic programming problem: a survey. J Comb Optim 28, 58–81 (2014) online. [^4]: Amandine Le Maitre, Mathieu Hatt, Olivier Pradier, Catherine Cheze-le Rest, and Dimitris Visvikis. Impact of the accuracy of automatic tumour functional volume delineation on radiotherapy treatment planning. Phys Med Biol Sep 7;57(17), 5381-97 (2012) online.

Unitary Fund Q3 2024: QOSS Survey, unitaryCON, and Project Updates

Tue, 15 Oct 2024 00:00:00 GMT

Dear Unitary Fund community,

We had a busy Q3 in 2024 and we are excited to share our highlights! This quarter we launched the third annual 2024 QOSS Survey. The annual survey is a state of the community & industry snapshot. It is a chance for anyone in the quantum computing industry to share their voice in the development of our field. The survey covers information on demographics, experience, community, research, tech stacks and more.

If you are a user or developer of software for any kind of quantum technology, we kindly encourage you to take this survey and contribute your voice to the future of quantum computing. Please note the survey will be available through the end of October 31, 2024. Take the survey here.

This September we also wrapped up our second annual unitaryCON, a collaborative workshop for the extended Unitary Fund community. With the help of Dr. Alexandru Paler, unitaryCON 2024 was hosted at Aalto University in Espoo, Finland. UnitaryCON provided a unique opportunity for Unitary Fund advisors, grantees, staff, ambassadors and friends to gather, talk, learn, and share ideas about how to move the field forward. With an event rating of 9.36 out of 10, the event was a success in bringing the community together to learn and network. Read more about the event and find links to talk information and slides here.

We look forward to another exciting quarter to close out 2024, and thank you to all of our community members for the impactful contributions to the open source quantum ecosystem in Q3! Make sure to follow our Discord, X, LinkedIn, and our [email protected]">Community Calendar.

New from Unitary Fund

Unitary Fund Research: W. J. Zeng, F. Labib, V. Russo, Towards violations of Local Friendliness with quantum computers. arXiv preprint (2024), [2409.15302]

Mitiq

v0.39.0: updates to our documentation, beginning with the completion of the first section of the Pauli Twirling user guide, which offers a comprehensive introduction to this feature. Additionally, we've added a new tutorial on CDR (Clifford Data Regression) using Qrack as an efficient near-Clifford simulator.

Metriq

This quarter we added two new members to the Open Quantum Benchmark Committee, Ed Younis and Peter Groszkowski. Ed is a computer systems engineer at Lawrence Berkeley National Laboratory with extensive experience developing and implementing advanced algorithms for quantum compilation, such as QFAST and Qfactor. He is currently the principal engineer on the BQSKit project and has research interests in quantum synthesis, compilation, and software systems. Peter is a researcher at the Oak Ridge National Laboratory working in various areas of physics, with emphasis on topics related to quantum computing and information. Beyond physics, he is also interested in all aspects of software development, ranging from numerical simulations to instrumentation control. Peter is a strong advocate of the open-source development model, supporting it whenever possible.
Work is being done to create state of the art metrics for benchmarking: https://metriq.info/Sota

Catalyst

Unitary Fund and Xanadu have partnered to enhance the error mitigation features of Catalyst, a powerful package for just-in-time (JIT) compilation of PennyLane programs. With this collaboration, Catalyst now includes support for exponential fitting and local folding within its zero-noise extrapolation routines, further boosting its capabilities.

This marks Unitary Fund’s first venture into the domain of quantum just-in-time compilation and its initial exploration of the MLIR compiler framework. It was an exciting opportunity to tap into the potential of integrating error mitigation directly within the MLIR stack and to experiment with cutting-edge quantum compilation technologies. More about this in a dedicated blog post coming out soon.

IEEE Quantum Week in review

Unitary Fund had a great presence at IEEE Quantum Week in Montreal, Canada this year!

IEEE Quantum week workshop (Quantum Software 2.0) that was a collaboration between ORNL, Xanadu, Unitary Fund, and AWS

Pictured: Catalina Albornoz (Xanadu), Dan Strano (Unitary Fund), David Ittah (Xanadu), Elaine Wong (ORNL), Josh Izaac (Xanadu) Not in the photo we have Yunong Shi (Amazon) and Vicente Leyton-Ortega (ORNL), who also participated in co-organizing the workshop. Co-authored by Unitary Fund, IBM, and Quantinuum, Effective DEIA Requires Accountability was a panel discussion at IEEE Quantum Week to discuss strategies for accountability in building diversity in the quantum computing field.

Pictured: Aaliyah Fowler (co-author, IBM); Natasha Oughton (panelist, NQCC); Temitope (Odeyomi) Adeniyi (panelist, Cleveland State University); Jordan Sullivan (panelist, unitary Fund); Shawn Skelton, panelist, Leibniz University Hannover); Mira Wolf-Bauwens (panelist, IBM); Kallie Ferguson (co-author, Unitary Fund); Lauren Ryan (co-author, Quantinuum)

The full schedule of the Unitary Fund IEEE Quantum Week presence is below, with more information here.

New Award

A research team led by Johns Hopkins APL quantum information scientist Gregory Quiroz and partners at five institutions, including Unitary Fund, has earned a competitive quantum computing award from the U.S. Department of Energy (DOE) to engineer potentially game-changing open-source software systems to propel scientific discoveries. Read more here!

Other news:

ALF Project:

The Helmholtz Platform for Research Software Engineering (HiRSE) is backing the ALF Project. More details and their promoting slide can be found at: https://gitpages.physik.uni-wuerzburg.de/ALF/ALF_Webpage/news/2024-08-29-helmholtz-hirse/
Last July we held our first hybrid ALF Workshop. The week-long, hands-on event was a success with both in person and remote participants. Some of the contributions can be found in our YouTube channel and more details can be found at: https://gitpages.physik.uni-wuerzburg.de/ALF/ALF_Webpage/news/2024-08-17-alf-workshop-2024/

Microgrant Updates

Earlier this year, we celebrated awarding over 100 microgrants and this quarter we opened up an application to join the Microgrant Advisory Review Board. If you are interested in applying, please submit your application by Friday, October 18.

QCoder, a competitive quantum programming platform, now offers all its content, including problems and editorials, in English. Its second competition took place on 18 August and attracted 183 participants from 20 countries!

top page: https://www.qcoder.jp/

2nd contest page: https://www.qcoder.jp/contests/QPC002

Toqito is now a numfocus affiliated project.

GQuantum Education: Teaching an online quantum education course for students in Ghana. Participated in WiSTEM Ghana's Girls Camp 2024, introducing quantum computing to high school senior girls in Ghana.

Mqt-qudits: successfully ran quantum circuits generated with 𝗠𝗤𝗧 𝗤𝘂𝗱𝗶𝘁𝘀, the first open-source framework for mixed-dimensional quantum computing, on the state-of-the-art 𝗾𝘂𝗱𝗶𝘁 𝗾𝘂𝗮𝗻𝘁𝘂𝗺 𝗰𝗼𝗺𝗽𝘂𝘁𝗲𝗿 at the University of Innsbruck. Check out the tool and tutorial here.

Q3 Grants

To Alberto Mercurio, Yi-Te Huang, and Luca Gravina to further develop Documentation for QuantumToolbox.jl, a state-of-the-art Julia package designed for quantum physics simulations.
To Hana KimLee to further develop Comprehensive Quantum Tomography Library, a Julia library that includes standard algorithms such as state/process tomography and randomized benchmarking, as well as more sophisticated machine learning algorithms.
To Aidan Sims to further develop Python CVXQuad, a project translating the CVXQuad library to Python and integrating it with the existing Toqito library.
To Maxime Garnier and Thierry Martinez to further develop Graphix through a 2025 workshop in Paris to further accelerate development of Graphix.

Job Opportunities

toqito: Quantum Information Science Impact through Open Source

Tue, 08 Oct 2024 00:00:00 GMT

The Origins of toqito

In early 2020, the humble initial commit of the toqito project (repo|docs) made its way onto GitHub.

toqito began as a research tool, designed by Vincent Russo to accelerate his work in quantum information. In the years since, it has evolved into a robust, open-source Python library providing powerful tools for researchers and enthusiasts alike.

Expanding Quantum Research with toqito

toqito has grown significantly in the past four years. It allows users to study fundamental objects in quantum information: quantum states, quantum channels, and quantum measurements. With tools to tackle problems in entanglement theory, nonlocal games, and convex optimization, toqito has made strides in democratizing quantum research.

toqito's main focus is providing tools in Python, inspired by the QETLAB MATLAB library, but without the licensing restrictions of MATLAB. Researchers can work with quantum systems using Python’s widely used scientific ecosystem.

There have also been a number of academic publications that have made used of toqito to numerically define and analyze certain problems in quantum information. A collection of these can be seen here

Bandyopadhyay, Somshubhro and Russo, Vincent, Distinguishing a maximally entangled basis using LOCC and shared entanglement[^1]
Tavakoli, Armin and Pozas-Kerstjens, Alejandro and Brown, Peter and Araújo, Mateus, Semidefinite programming relaxations for quantum correlations[^2]
Johnston, Nathaniel and Russo, Vincent and Sikora, Jamie, Tight bounds for antidistinguishability and circulant sets of pure quantum states[^3]
Pelofske, Elijah and Bartschi, Andreas and Eidenbenz, Stephan and Garcia, Bryan and Kiefer, Boris, Probing Quantum Telecloning on Superconducting Quantum Processors[^4]
Philip, Aby and Rethinasamy, Soorya and Russo, Vincent and Wilde, Mark, Quantum Steering Algorithm for Estimating Fidelity of Separability[^5]
Miszczak, Jarosław Adam, Symbolic quantum programming for supporting applications of quantum computing technologies[^6]
Casalé, Balthazar and Di Molfetta, Giuseppe and Anthoine, Sandrine and Kadri, Hachem, Large-Scale Quantum Separability Through a Reproducible Machine Learning Lens[^7]
Russo, Vincent and Sikora, Jamie, Inner products of pure states and their antidistinguishability[^8]

Core Concepts: Quantum States, Channels, and Measurements

In quantum information science, quantum states represent the fundamental objects we manipulate, quantum channels describe the transformations applied to these states, and quantum measurements allow us to extract information from states.

Example: Defining and Analyzing a Quantum State

In this example, we calculate the fidelity between two quantum states—-a fundamental task in quantum state comparison.

For example, in the event where we calculate the fidelity between states that are identical, we should obtain the value of 1. This can be observed in toqito as follows.

>>> from toqito.state_metrics import fidelity
>>> import numpy as np
>>> rho = 1 / 2 * np.array(
...    [[1, 0, 0, 1],
...     [0, 0, 0, 0],
...     [0, 0, 0, 0],
...     [1, 0, 0, 1]]
... )
>> sigma = rho
>>> fidelity(rho, sigma)
1.0

Quantum State Discrimination

A more engaging example is quantum state discrimination, a widely applicable problem in cryptography and quantum computing. The goal is to distinguish between different quantum states in an optimal way. This is typically formulated as a convex optimization problem.

In toqito, this problem can be tackled efficiently using semidefinite programming (SDP). Below is an example of discriminating between two quantum states.

In the following example, we see that it is possible to perfectly distinguish (with minimum-error) amongst the four Bell states:

>>> import numpy as np
>>> from toqito.states import bell
>>> from toqito.state_opt import state_distinguishability

>>> states = [bell(0), bell(1), bell(2), bell(3)]
>>> probs = [1 / 4, 1 / 4, 1 / 4, 1 / 4]
>>> res, measurements = state_distinguishability(vectors=states, probs=probs, primal_dual="primal")
np.around(res, decimals=2)
np.float64(1.0)

Quantum distinguishability is a rich field of research and having the ability to pull "off the shelf" techniques to determine the probability of distinguishing a set of quantum states is a useful technique for rapidly iterating on research in this domain.

Unitary Fund accelerates toqito

In the early days of toqito, Vincent showed some basic functionality to co-workers with a quantum information background. One of them suggested the Unitary Fund’s microgrant program. To his delight, toqito was accepted as a microgrant recipient after making a short video for the application. Not only was the monetary reward a nice boost of encouragement, but the associated support from the UnitaryFund team pushed him to reach out to other scientists and researchers who may benefit from toqito and potentially guide its development.

One of the opportunities suggested by the Unitary Fund to promote toqito included a talk to the New York Quantum Computing Meetup group participants. Vincent recorded the subsequent first video on the UnitaryFund YouTube channel that outlined the basic premise of toqito at that time. To promote toqito to a broader audience, a short whitepaper was published in the Journal of Open Source Software.

Later that year, the first UnitaryHACK 2021 event took place. This hackathon allows maintainers of quantum open-source (QOSS) software repositories to participate by adding a set of bountied issues to improve the participating QOSS project. This hackathon also involved some of the earliest external contributors to toqito.

toqito has since continued to be a participating project at subsequent UnitaryHACKs (2022, 2023, and 2024) and has gained more users, contributors, and essential features that have been invaluable to the broader community.

As toqito continued to gain usage and traction, another UF microgrant to further develop the project was awarded to a prior contributor of UnitaryHACK 2023 (Purva Thakre). These funds allowed dedicated time to delve into some of the more in-depth feature requests and continue to improve additional aspects of the project, such as thorough testing, documentation, CI/CD, and tutorials.

In addition to being cited and used in peer-reviewed research papers on quantum information, toqito has also been recognized elsewhere. toqito was voted one of the top quantum simulators for 2024 by QuantumInsider. Recently, KaiCode awarded toqito the first place prize for being the best project of 400+ projects judged on clean code, good project structure, etc. Furthermore, as of September 2024, toqito is now an affiliated project of NumFOCUS.

The future of toqito

The toqito project continues to be used and contributed to by numerous researchers and software developers in the quantum ecosystem. For instance, another UF microgrant was recently awarded to Aidan Sims to port cvxquad functions written in MATLAB into toqito’s channels/ module.

There are many exciting plans for the future of toqito. If you feel that toqito may enhance your research workflow or the toqito roadmap lacks a particular feature, don’t hesitate to contact the developers through the Discord channel. If you want to contribute to the project, consult the contribution guide, open a PR, or add an issue to the board.

We look forward to seeing where toqito goes from here!

[^1]: Bandyopadhyay, Somshubhro and Russo, Vincent, Distinguishing a maximally entangled basis using LOCC and shared entanglement (2024) arXiv:2406.13430.

[^2]: Tavakoli, Armin and Pozas-Kerstjens, Alejandro and Brown, Peter and Araújo, Mateus. Semidefinite programming relaxations for quantum correlations (2023) arXiv:2307.02551.

[^3]: Johnston, Nathaniel and Russo, Vincent and Sikora, Jamie, Tight bounds for antidistinguishability and circulant sets of pure quantum states (2023) arXiv:2311.17047

[^4]: Pelofske, Elijah and Bartschi, Andreas and Eidenbenz, Stephan and Garcia, Bryan and Kiefer, Boris, Probing Quantum Telecloning on Superconducting Quantum Processors (2023) arXiv:2308.15579

[^5]: Philip, Aby and Rethinasamy, Soorya and Russo, Vincent and Wilde, Mark, Quantum Steering Algorithm for Estimating Fidelity of Separability (2023) arXiv:2303.07911

[^6]: Miszczak, Jarosław Adam, Symbolic quantum programming for supporting applications of quantum computing technologies (2023) arXiv:2302.09401

[^7]: Casalé, Balthazar and Di Molfetta, Giuseppe and Anthoine, Sandrine and Kadri, Hachem, Large-Scale Quantum Separability Through a Reproducible Machine Learning Lens (2023) arXiv:2306.09444

[^8]: Russo, Vincent and Sikora, Jamie, Inner products of pure states and their antidistinguishability (2023) arXiv:2206.08313

UnitaryCON 2024: Bringing together the open source quantum software community

Fri, 04 Oct 2024 00:00:00 GMT

This September we wrapped up our second annual unitaryCON, an invitation-only collaborative workshop for the extended Unitary Fund community. The workshop is an opportunity to share ongoing projects, connect with collaborators and supporters, and work with our community to advance the quantum open-source software ecosystem with the leading contributors from around the world.

With the help of Dr. Alexandru Paler, unitaryCON 2024 was hosted at Aalto University in Espoo, Finland. UnitaryCON provided a unique opportunity for Unitary Fund advisors, grantees, staff, ambassadors and friends to gather, talk, learn, and share ideas about how to move the field forward.

UnitaryCON featured talks and interactive activities revolving around various topics in open source software for quantum computing and quantum technologies, including compilers, error mitigation and error correction toolkits, platforms for quantum computing, SDKs, cloud platforms, and open hardware in quantum tech. More detailed information about the talks and slides can be found here.

Talks included sessions from companies engaged in the open source ecosystem such as IBM, Xanadu, NVIDIA, Pascal, and QBraid. This year’s unitaryCON also added sessions on open quantum hardware from Carnegie Mellon University, Open Quantum Design, and OpenQuantum. In addition, popular open source software packages such as BQSKit, QuTiP, Qibo, and QuEST were also featured.

On a scale of 1-10, participants gave unitaryCON an average rating of 9.36. The majority of participants found the interactions with other participants - an ongoing priority for this workshop - to be their favorite part of unitaryCON. UnitaryCON participants received advance access to the annual Quantum Open Source Software Survey, which is currently running through the end of October and is a chance for anyone in the quantum computing industry to share their voice in the development of our field.

Thank you to our members and event sponsors for making unitaryCON possible!

Core Members: IBM Quantum, DoraHacks, OQD, and Scientifica Supporting Members: AWS, Microsoft, Pasqal, QC Ware, SandboxAQ Event Sponsors: InstituteQ and Classiq

A special thank you to InstituteQ for their generous sponsorship to fund travel to participate in unitaryCON.

Thoughts from participants:

“I love the event! Thanks guys for the good work and organization in this year's event. I'm always happy to see you :)”

“Unitary Fund's place in the rest of the quantum ecosystem (as an open-source focused org) attracts a great set of folks for this conference.”

“[People] found this year's uCON very insightful and inspiring and that they are already excited for next year!”

“One of the most valuable aspects of unitaryCON was networking with like-minded individuals in quantum. I also thought the invite only nature and a small(ish) gathering made the event more fun.”

“Getting this many quantum software people in a room is awesome!”

“I feel it is a great initiative by unitary fund and the people here are amazing. I really like the informal nature of the conference without compromising on the quality of the content and presentations. I hope it stays like this in the future too.”

“Keep doing great work!”

We can’t wait to see you all next year for unitaryCON 2025!

Make sure to follow our Discord, X, LinkedIn, and our [email protected]">Community Calendar to stay up to date on upcoming events and news!

The 2024 QOSS Survey is open!

Mon, 16 Sep 2024 00:00:00 GMT

This annual survey is a state of the community & industry snapshot. It is a chance for anyone in the quantum computing industry to share their voice in the development of our field. The survey covers information on demographics, experience, community, research, tech stacks and more.

If you are a user or developer of software for any kind of quantum technology, we kindly encourage you to take this ~10 minute survey. Please note the survey will be available through the end of October 31, 2024. Thank you for your help in building a better quantum computing ecosystem!

Are you ready to take the survey? Click here to get started!

All anonymized results will be shared publicly later this year, so that the survey can be a resource for anyone who wants a better understanding of the quantum computing community’s needs. Unitary Fund will also analyze the data, report our filings and publish the aggregated results on our website.

A very large and heartfelt thank you to all the Unitary Fund community members, advisors, and partners who continue to help us provide this survey as a resource, including work in designing, testing and providing general feedback.

Fill out the QOSS Survey

An Introduction to Genetic Algorithms for Quantum Architecture Search

Wed, 11 Sep 2024 00:00:00 GMT

In various quantum optimization problems, choosing the right ansatz is a critical point that will affect the accuracy of the result. For example, in Variational Quantum Eigensolver, many template ansatzes have been proposed, such as Graph Ansatz and EffecientSU2, etc. An ansatz [1] is the structure of quantum gates, deciding how many and what type of gates will be used, for easier imagination, it's equivalent to the model's architecture in a deep learning model.

Yet the above example ansatzes can be limited in their applicability. Hence, we've created a search engine called GA-QAS (Genetic Algorithm for Quantum Architecture Search) to aid in the discovery of the right ansatz. In this post, we will guide you on how to use it efficiently.

Now, let’s start!

Step 0. Setup the environment

Make sure that you installed Python 3 and the following packages:

qiskit 1.0+
matplotlib
tdqm

We will use a Python package named <a href="https://github.com/vutuanhai237/qoop">$\langle \mathrm{qo}|\mathrm{op} \rangle$</a>, which is a core package for developing quantum circuit optimization frameworks. You can download it via git as:

git clone https://github.com/vutuanhai237/qoop.git

Note: You should put the repo on the same level as your Python/Jupyter Notebook file.

folder_name
│   your_python_file.py
|   your_jupyter_file.ipynb
└───qoop
│   └───evolution
│       │   environment.py
│       │   cross_over.py
│       │   ...

Step 1. Define problem (W state preparation)

<figure> <img src='/images/ga-qas/ga-qas_scheme.png' width="600" style="margin: auto" alt='' /> <figcaption> Fig 1. (a) State preparation scheme based on quantum compilation technique, where U, V are ansatz and state that need to prepare[2][3]. (b) Some default ansatz, such as hyper-graph. </figcaption> </figure>

Quantum state preparation (QSP) is a process that uses a trainable unitary operator to transform the initial state into a desired target state. This process is crucial for quantum computation and information processing. For example in a quantum machine learning applications when you want to work with images, you must flatten the image as a vector and then use QSP to encode the image into a quantum state!

In this example we will show how to prepare a Werner state, also known as a W state. For 3-qubits, the W state is defined as:

$$ |W_3\rangle = \frac{1}{\sqrt{3}}(|001\rangle + |010\rangle + |100\rangle) = V|000\rangle $$

To prepare the W state, we will need a unitary operator $V$. In general, $V$ requires large resources such as a large depth or number of total gates. Therefore, we look to find another unitary $U(\theta)$ that is trainable and that approximates $V$, but requires fewer resources than $V$.

The problem comes from here: the structure of $U$, affects how "hard" and "large" this optimization process is. Then, we need to find the "best" $U$ automatically. This is known as the "quantum architecture search" problem.

<figure> <img src='/images/ga-qas/ga-qas_example_plot_preparew.png' style="margin: auto" alt='' /> <figcaption>Fig 2. Metrics of W-state preparation process versus iteration when running the example code. Note that loss_fubini_study is overlapped by trace distances. loss_fubini_study should be near 0 as much as possible.</figcaption> </figure>

import qiskit
from qoop.compilation.qsp import QuantumStatePreparation
from qoop.core import state

def fitnessW(qc: qiskit.QuantumCircuit):
    # Create a quantum state preparation optimizer based on a given trainable unitary (u) and target unitary.
    qsp = QuantumStatePreparation(
        u = qc,
        target_state = state.w(num_qubits = 3).inverse()
    ).fit() # Begin to optimize trainable unitary
    # qsp.plot() # Plot optimization process as Fig. 2.
    return 1 - qsp.compiler.metrics['loss_fubini_study'][-1] # Fitness value

Make sure that you can run the above code. We wrap the quantum state preparation problem into a function $f: \mathsf{U}(n) \rightarrow \mathbb{R}$, the return value of this function is $(1 - \text{last loss value})$, which means a value near 1 is desired.

Step 2. Configuration for genetic algorithm

<figure> <img src='/images/ga-qas/ga-qas_pipeline.png' style="margin: auto" alt='' /> <figcaption>Fig 3. The general pipeline of GA-QAS</figcaption> </figure>

A genetic algorithm (GA) is a heuristic algorithm based on a genetic combination process. GA processes include Fitness evaluation, Selection, Cross-over, and Mutation. We treat ansatz as an individual in the population (where gates are its genes). The overall process can be viewed in Fig. 3.

Process	Method
Population generation	A $n$ ansatz is initialized from a pool gate (Clifford$+R_i+CR_i, i\in{x,y,z}$) with certain provided metadata
Fitness evaluation	Evaluate each ansatz by calling `fitness_func(ansatz)`
Selection	Get fitness value from the fitness evaluation; simply sort from high to low and take the first half part
Cross-over	Divide two ansatz $qc_1$ and $qc_2$ into four parts ${qc_{11}, qc_{12}, qc_{21}, qc_{22}}$, then combine each two parts into two new ansatz $qc_1^=qc_{11}\vert qc_{22}$ and $qc_2^{}=qc_{12}\vert qc_{21}$
Mutation	Each gate on ansatz has a small probability of mutating to another gate (with the same number of qubits) in the pool

Tab 1. Detail of each operation in GA-QAS.

In the GA, some hyper-parameters need to be considered and defined before you run GA-QAS. Then, you need to create an EEnvironment object. The important parameter is fitness_func which is the function we defined above.

from qoop.evolution.environment import EEnvironmentMetadata
env_metadata = EEnvironmentMetadata(
        num_qubits, # As its name
        depth, # Ansatz depth you want
        num_circuit, # Number of ansatz per generation
        num_generation, # Number of generation/iteration for GA
        prob_mutate # Mutation probability, usually as small as 0.01 (1%)
)
from qoop.evolution.environment import EEnvironment
env = EEnvironment(
     metadata = env_metadata,
     fitness_func = fitnessW,
)
env.set_filename('GAQASPrepareW')

Default folder result will be set as {num_qubit}+{fitness function}+{datetime}, if you want shorter name, use set_filename method.

Step 3. Run GA-QAS

You can call the method evol() to start running GA-QAS.

env.evol()

<!-- ```py env.evol( verbose = 1, auto_save = True )


<!-- There are only two parameters: the first is verbose in running process (1 means print process bar, 0 means no print anything), and the second is the saving option.
The saving result's folder is detailed on [GA-QAS: folder result](https://github.com/vutuanhai237/qoop/wiki/GA%E2%80%90QAS:-folder-result). -->

# Step 4. Plot result

Currently, we support plotting fitness values against a number of generations. In the future, we will develop more presentation plots.

```py
env.plot()

<figure> <img src='/images/ga-qas/ga-qas_example_plot_evolution.png' style="margin: auto" alt='' /> <figcaption>Fig 4. Fitness values versus number of generations</figcaption> </figure>

The result is saved in a folder; the default folder name is based on the fitness function name. We care about a file named best_circuit.qpy, which is our final solution. Then, we can load it by $\langle \mathrm{qo}|\mathrm{op} \rangle$ and put it into fitness again to test:

from qoop.backend import utilities
best_circuit = utilities.load_circuit("./GAQASPrepareW/best_circuit.qpy")
fitness_value = fitnessW(best_circuit)

Conclusion

In this post, we have demonstrated how to use GA-QAS. Simply define your own problem (fitness function) and the package will help you find the best ansatz automatically. For more information and documentation, explore the following links.

$\langle \mathrm{qo}|\mathrm{op} \rangle$: core package for GA-QAS.
- Github
- Wiki
- Paper
GA-QAS:
- Wiki: Load folder result and continue to evol()
- Wiki: Full pipeline
- Paper

Thanks for reading! Please do not hesitate to ask us any questions via e-mail at [email protected]">[email protected] or LinkedIn.

References

[1] https://pennylane.ai/qml/glossary/circuit_ansatz/

[2] Hai, V. T., Viet, N. T., & Ho, L. B. (2023). Variational preparation of entangled states on quantum computers. arXiv preprint arXiv:2306.17422.

[3] Khatri, S., LaRose, R., Poremba, A., Cincio, L., Sornborger, A. T., & Coles, P. J. (2019). Quantum-assisted quantum compiling. Quantum, 3, 140.

Appendix: Full code

The Jupyter notebook which contains the above code can be found here

import qiskit
from qoop.core import state
from qoop.compilation.qsp import QuantumStatePreparation
from qoop.evolution.environment import EEnvironmentMetadata
from qoop.evolution.environment import EEnvironment

def fitnessW(qc: qiskit.QuantumCircuit):
    qsp = QuantumStatePreparation(
        u = qc,
        target_state = state.w(num_qubits = 3).inverse()
    ).fit(num_steps = 100)
    return 1 - qsp.compiler.metrics['loss_fubini_study'][-1] # Fitness value

env_metadata = EEnvironmentMetadata(
    num_qubits = 3, # As its name
    depth = 4, # Ansatz depth you want
    num_circuit = 4, # Number of ansatz per generation
    num_generation = 10, # Number of generation/iteration for GA
    prob_mutate = 0.01 # Mutation probability, usually as small as 0.01 (1%)
)

env = EEnvironment(
    metadata = env_metadata,
    fitness_func = fitnessW,
).evol()

The first in-person Mitiq Workshop at the 2024 QNumerics Summer School

Wed, 28 Aug 2024 00:00:00 GMT

Unitary Fund held the first in-person workshop for the Mitiq project on August 17.

The workshop was part of the first Numerical Methods in Quantum Information Science (QIS) Summer School at the Mount Ida campus of University of Massachusetts Amherst. The program took place August 12-18, 2024, with a full day dedicated to Mitiq and quantum error mitigation.

Over 40 students attended the summer school, most at the graduate or postdoc level, with a few advanced undergraduates and other motivated community members. The program focused on practical, experiential learning with an emphasis on programming skills and open source tooling. This focus, combined with an openness in accepting applicants with various backgrounds and career stages, made it a natural fit for hosting the Mitiq workshop.

Topics covered in the days leading up to the Mitiq workshop included general software engineering practices and cluster computing tools, advanced general scientific programming, GPU programming, fast general purpose wavefunction simulation, tensor networks for faster approximate quantum simulations, stabilizer formalism for quantum error correction, discrete event simulations, quantum chemistry, symbolic computer algebra basics, optimal control of quantum hardware, APIs for control of commercial quantum hardware. After the full-day interactive sessions, the students participated in focused hackathons, applying concepts and skills covered in the program. Unitary Fund CTO Nathan Shammah also presented on the quantum open technology ecosystem and Unitary Fund's activities to grow and support it. Unitary Fund Technical Staff Member Misty Wahl presented a survey of hybrid quantum error mitigation, including her recent work "Zero noise extrapolation on logical qubits by scaling the error correction code distance".

Workshop topics

On the day of the workshop, we began by presenting quantum error mitigation (QEM) core concepts and techniques, Mitiq's structure and interface, and a deep dive into the techniques of Zero Noise Extrapolation (ZNE) and Digital Dynamical Decoupling (DDD). We then challenged the students to complete a guided Jupyter notebook activity applying ZNE and DDD to standard benchmarking problems on simulated noisy backends. The workshop concluded in the evening with a pizza social and informal Mitiq coding session. Throughout the workshop the participants asked thoughtful questions and gave insightful feedback, which will we will use to inform future Mitiq development and outreach. We look forward to seeing the participants continue to engage with the open quantum tech community and spread the word about Mitiq.

Growing the Mitiq community

This workshop marked an important achievement for the growth of Mitiq, moving from virtual collaboration to an in-person focused session with new and existing users of the software. Mitiq is the open source quantum error mitigation compiler developed by the Unitary Fund technical team with a global community. To date, Mitiq has over 140k downloads on PyPI and over 70 contributors worldwide on Github. The Mitiq documentation and tutorials contains more information about error mitigation and supported techniques. Mitiq's open source ecosystem growth is accelerated by the National Science Foundation (NSF) POSE program (Phase II) awarded to Unitary Fund.

Our thanks to the organizers Stefan Krastanov (U. Mass. Amherst), Katharine Hyatt (AWS Quantum) and Roger Luo (QuEra) for enthusiastically including us and producing an excellent program, and to the sponsors of the school.

To learn about future events and exciting developments at Unitary Fund, make sure to follow our Discord, X, LinkedIn, and our [email protected]">Community Calendar.

Unitary Fund Q2 2024 Update: unitaryHACK, Qrack integration, new grants and upcoming events

Mon, 29 Jul 2024 00:00:00 GMT

Dear Unitary Fund community,

We are excited to share our 2024 Q2 quarterly update! In Q2 we wrapped up UnitaryHACK 2024, held from May 29th to June 12th, which was our most successful and largest hackathon to date! We were thrilled to see 873 people registered from 71 different countries, making this truly a global event. UnitaryHACK also saw a significant increase in the number of participating projects, from 33 last year to 49 this year, reflecting the growing interest and involvement in our community.

We were excited to host in-person hackdays at various locations, fostering community engagement and collaboration at Aalto University in Helsinki, UNAM in Mexico City, and University of Washington in Seattle. These events provided an excellent opportunity for participants to meet face-to-face, share ideas, and work together in real-time.

We couldn't have achieved this without the generous support of our sponsors and core members:

Event Sponsors: Quantinuum, NVIDIA, Classiq, QuEra
Core Members: IBM Quantum, DoraHacks, OQD, and Scientifica.
Supporting Members: AWS, Microsoft, Pasqal, QC Ware, SandboxAQ

The enthusiasm, creativity, and hard work demonstrated by all participants have set a high bar, and we are excited to see how we can continue to grow and improve. Thank you to everyone who participated, supported, and contributed to making UnitaryHACK 2024 a resounding success. Let's keep the momentum going and continue to make impactful contributions to the open source quantum ecosystem!

Make sure to follow our Discord, X, LinkedIn, and our [email protected]">Community Calendar.

New from Unitary Fund

Unitary Fund co-authored “Quantum amplitude estimation from classical signal processing.” [2405.14697]

QRack

Qrack is now fully integrated as a plugin of PennyLane and Catalyst with just in time compilation with the new PennyLane v0.37 and Catalyst v0.7 release.

Mitiq

Sign up for the Mitiq Newsletter! PhD students Ella Carlander, Ruhee Nirodi, and Alexandros Peltekis at the University of Washington completed a capstone course working on the resource requirement pipeline for quantum error mitigation using Mitiq. Read more about their work here!

New Releases: v0.36.0, v0.37.0, v0.38.0

v0.38.0: 🚀 As of this release, thanks to @natestemen, we are officially supporting Python 3.12 and dropping Python 3.9. 🌉 As part of UnitaryHack 2024, new contributor @NnguyenHTommy fixed a Qiskit to Cirq gate conversion error by implementing a fallback mechanism to decompose and transpile the Qiskit circuit into native Cirq gates. 🌀 Another Unitary Hacker, @EmilianoG-byte added functionality to simulate noise specifically on CNOT and CZ gates when using the Pauli Twirling technique to symmetrize errors. 🔉 As hinted in last release's spoilers, @purva-thakre has implemented the noise scaling functionality required for the Layerwise Richardson Extrapolation (LRE) technique, which allows a more fine-grained control over the amount of noise in circuits compared to the standard unitary folding method.
v0.37.0: ✨ Stacking quantum error mitigation techniques is a primary area of focus in Mitiq. In this release, @jordandsullivan introduced a Tutorial on composing Digital Dynamical Decoupling (DDD) and Zero Noise Extrapolation (ZNE). Users also now have the option to download tutorials in Jupyter .ipynb format directly from our documentation. We hope this will encourage experimentation with existing tutorials.
v0.36.0: Support for Qiskit 1.0: Mitiq now fully supports programs written in Qiskit 1.0, thanks to the contributions of André Alves!

Metriq

The progress chart has been updated with new data points and controls to separate out classically intractable and practically or industrially useful data subsets. The Open Quantum Benchmark Committee had its second plenary meeting to discuss state-of-the-art metrics forwarded by topic-specific subcommittee members and plan objectives for the committee for the next quarter.

Conferences we attended in Q2

JuliaCon
WQS PLDI
Teratec Quantum Benchmarks

Microgrant updates

Qlasskit: this quarter qlasskit received contributions from hackers of UnitaryHack 2024, and reached version 0.1.29! These are the highlights from the git log:

Implement ast.Pow Operator Rewriting Rule in AstRewriter by @tomv42 in #49
Add py2bexp and py2qasm CLI tools by @tomv42 in #56 and #59
Bernstein Vazirani algorithm by @divshacker in #60
int and float cast functions by @dakk in #25
Shift and Add multiplication by @dakk in #41
Improvements and refactoring of the compilers
Qfixed type by @dakk in #20

QWorld: The first global virtual class, QClass23/24, by QWorld was completed successfully in June 2024. We hosted 1.3K+ students from all around the world. More than 10 quantum courses, self-study modules, or challenges were offered, and in total 831 certificates were handed out.

toqito: v1.0.9 of toqito was released earlier this week. A full update on what improvements, new features, and changes went in can be found on the release page. The toqito project also won first place out of more than 400 open-source projects at the KaiCode 2024 competition—a huge thanks to the community who have continued to improve and use toqito. The monetary rewards will be recycled back into continuing to improve the toqito project and to incentivize further contributions from members.

Integration of Zero-Noise Extrapolation from Mitiq into OpenQAOA: Congratulations to Unitary Fund grantee recipients Adriano Lusso and Victor Onofre for their poster acceptance at QPL 2024! Their work on "Simulating unknown qubit-unitary inversion with zero-noise extrapolation" utilizes noise models and the Mitiq toolkit to implement ZNE and analyzes deviations from theoretical results.

Congratulations to Gerald E. Fux on the version 0.5 release of OQuPy! Gerald received a microgrant from Unitary Fund in 2021 for developing an open source python package for simulating non-Markovian open quantum systems using tensor network techniques.

Q2 Grants

To Markus Heinrich, Jonas Helsen and Ingo Roth to further develop Error-agnostic shadow estimation, to show that logarithmic-depth random circuits are sufficient to estimate expectation values of a large class of global observables.
To Carter M. Gustin to further develop OpenParticle, providing specialized tools for people studying quantum field theory(QFT).
To Dorcas Attuabea Addo, Henry Martin, Peter Nimbe to further develop GQuantum Education, a quantum education initiative based in Ghana.
To Kevin Mato to further develop MQT Qudits, a quantum open-source software framework for mixed-dimensional quantum computing.
To Aaron Trowbridge to further develop Piccolo.jl, releasing a 1.0 version that will further segment the code base, separating the backend solver interface code into a QuantumCollocationCore.jl package as well as make it easy for python users to use the quantum optimal control method.
To Timothy King and Ella Meyer to further develop Quantum Arcade, creating a landing page and currating existing quantum games as well as developing resources for new games to help teach quantum computing globally.
To Oxana Shaya and Konstantin Golovkin to further develop Lie algebraic properties of quantum circuits, an implementation of functionalities that help with the understanding of the Lie algebra of a quantum circuit.
To Ella Carlander and Ruhee Nirodi to further develop Overhead and Performance Analysis for Mitiq’s Quantum Error Mitigation Implementations, a tool that can characterize overhead for different QEM methods and compare them.

Coming up

August 12-18: This summer we will be hosting a Mitiq workshop as part of the summer school on Numerical Methods in Quantum Information Science.
September 9-10: Find Unitary Fund at Finnish Quantum Days in Helsinki, Finland!
September 11: Unitary Fund will be participating in Quantum Resource Estimation for Neutral Atom Computers (QRE2024) in Helsinki, Finland.
September 12-14: Unitary Fund will be hosting the second annual UnitaryCON. Interested in attending? Send us an email at [email protected].
September 15-20: Find Unitary Fund at IEEE Quantum Week!
- Misty Wahl is a panelist in the workshop for “Academic and Professional Training in Quantum Computing: The Importance of Open-source as a co-author on the panel” taking place on Friday, September 20.
- Dan Strano is co-presenting the workshop “Quantum Software 2.0: Enabling Large-scale and Performant Quantum Computing” on Thursday, Sept 19.
- Kallie Ferguson is co-author with IBM Quantum and Quantinuum for the panel “Effective DEIA Requires Accountability.”

QJIT compilation with Qrack and (Xanadu PennyLane) Catalyst

Wed, 10 Jul 2024 00:00:00 GMT

Unitary Fund and Qrack are proud to partner with the Xanadu PennyLane Catalyst team to release an open-source plugin for PennyLane that supports quantum just-in-time (QJIT) compilation! The plugin supports all constructor options available in the PyQrack QrackSimulator class, including so-called hybrid stabilizer, quantum binary decision diagrams (QBDD), just-in-time local circuit simplification with a novel tensor network technique and representation based directly on quantum circuit diagrams, and single-and-multi-GPU state vector simulation, with our without our Schmidt decomposition techniques. Remember the Qrack device back end for PennyLane if you’d like to leverage GPU acceleration but don’t want to complicate your choice of devices or device initialization, to handle a mixture of wide and narrow qubit registers in your subroutines without manually switching between GPU-based and CPU-based back ends.

Read the documentation, run the first official tutorial and demonstration, check out the repository on the Unitary Fund GitHub organization, star and share, and get Qrackin’! You rock!

Announcing the Mitiq Workshop at the QNumerics Summer School

Fri, 05 Jul 2024 00:00:00 GMT

We are pleased to announce the first in-person workshop for the Mitiq project.

The workshop will be held as part of the Numerical Methods in Quantum Information Science (QIS) Summer School at the Mount Ida campus of University of Massachusetts Amherst.

About the QNumerics Summer School

The School spans through August 12-18, 2024, with Saturday, August 17, 2024 fully dedicated to Mitiq and quantum error mitigation.

The Summer school program is designed for community members "with QIS expertise and baseline programming skills searching to significantly expand them," including graduate students, postdocs and professionals, as well as exceptional undergraduates and "hackers" - builders who are passionate about open quantum technology. This openness in accepting applicants with various backgrounds and professional career is important for removing barriers towards an accelerated workforce development and a broader impact on continuous learning.

The program's focus on practical, experiential learning with an emphasis on programming skills and hackathon-style sessions each evening made it a natural fit for hosting the Mitiq workshop. Other topics covered in the Summer school include general software engineering practices and cluster computing tools, advanced general scientific programming, GPU programming, fast general purpose wavefunction simulation, tensor networks for faster approximate quantum simulations, stabilizer formalism for quantum error correction, discrete event simulations, quantum chemistry, symbolic computer algebra basics, optimal control of quantum hardware, APIs for control of commercial quantum hardware.

A focus on open-source scientific tools for quantum programming

A focus of the QNumerics School is placed on Julia as a transparent and efficient programming language designed for science. At Unitary Fund we're proud to support several Julia projects (and sponsor this JuliaCon 2024).

We look forward to presenting topics including quantum error mitigation (QEM) core concepts and techniques, Mitiq structure and interface, and deep dive into the techniques of Zero Noise Extrapolation and Digital Dynamical Decoupling. In the later part of the session, we will explore QEM on simulated noisy backends with benchmarks and calibration. The workshop will conclude in the evening with a Mitiq hackathon. The Summer School is supported by a number of organizations.

The Qnumerics Summer school lecturers include Stefan Krastanov (U. Mass. Amherst), Katharine Hyatt (AWS Quantum), Roger Luo (QuEra), Miles Stoudenmire (Flatiron Institute) and Unitary Fund's Nathan Shammah and Misty Wahl. Prof. Stefan Krastanov, one of the organizers commented:

At JuliaCon 2023 Katharine and I were discussing how much of the opensource tooling created in the field is still underutilized and thought why not do something about it. The NSF Center for Quantum Networks (and now also the Unitary Fund) seemed to have agreed with us and were eager to sponsor a hacker-oriented summer school rife with late-night hackathons. We are all particularly excited that what we teach the students will be a force multiplier for their domain-specific skills, leading to rapid research progress into the many low-hanging fruits still present in the field of quantum information science. We are hopeful that quite a few research papers will start at our hackathons.

A milestone for the Mitiq community

This workshop marks an important milestone for the growth of Mitiq, the open source quantum error mitigation compiler developed by the Unitary Fund technical team with a global community. To date, Mitiq has over 140k downloads on PyPI and over 70 contributors worldwide on Github. To learn more about error mitigation, you can read the Mitiq documentation and tutorials. Mitiq's open source ecosystem growth is accelerated by the National Science Foundation (NSF) POSE program (Phase II) awarded to Unitary Fund.

Introducing the Open Quantum Benchmark Committee with Metriq

Fri, 14 Jun 2024 00:00:00 GMT

The quantum computing landscape is rapidly evolving, with breakthroughs and advancements occurring regularly. However, amidst this progress, one challenge persists: how can researchers, developers, and enthusiasts effectively benchmark and compare different quantum computing platforms and technologies? To address this challenge head-on, Unitary Fund is excited to announce the establishment of the Open Quantum Benchmark Committee. This committee will play a crucial role in furthering the development and adoption of quantum benchmarks to provide the community with a comprehensive and reliable framework for evaluating quantum computing systems.

The motivation behind the Open Quantum Benchmark Committee stems from the need to foster collaboration and standardization within the quantum computing community. By bringing together experts from various domains, including applications, compilers, error correction, hardware, and simulators, we aim to increase the size and improve the quality of the taxonomy captured by Metriq (https://metriq.info/), our community-driven quantum benchmarks platform, and empower researchers and developers with the tools they need to navigate the complex landscape of quantum computing benchmarks.

Metriq (https://metriq.info/) is a free and open-source platform to facilitate quantum computing benchmarking. It gives researchers and developers a centralized hub to submit results, propose new benchmarking tasks, and access openly accessible data. By making benchmarking data explorable and live-updated, Metriq accelerates research and development in quantum technology. As a community member, you can go to https://metriq.info/ and contribute metrics from your own papers to increase the robustness of benchmarking data.

Committee members will serve for one year, volunteering their time and expertise to attend quarterly meetings and support open-source and open-access quantum benchmarks. This is an open application process available to anyone in the public. To start, the committee will evaluate and decide on two metrics per topic found on the State of the Art Quantum Benchmarks page.

We also acknowledge the invaluable contributions from other initiatives in this space, such as IEEE Quantum Benchmarks, QED-C STAC on Standards, BACQ, and events like the TQCI Seminar on Benchmarks for Quantum Computing, which collectively enrich the goals of standardized benchmarking across the field. The establishment of the Open Quantum Benchmark Committee represents a significant step towards advancing the field of quantum computing through collaboration and standardization. By leveraging the community's collective expertise and harnessing the power of platforms like Metriq, we can accelerate progress and unlock the full potential of quantum technology.

Meet the Committee

AJ Rasmusson AJ Rasmusson is a graduate student at Indiana University doing trapped-ion research under Phil Richerme. This Summer, he’ll start a postdoc at the NIST Ion Storage Group, doing more ion trap experiments. In high school, his grandpa gifted him an audio lecture on quantum physics, and he’s been hooked ever since. He enjoys—and has greatly benefited from—open science endeavors, and he believe this philosophy is important for a vibrant scientific community. Outside of work, he enjoys wrangling his three kids, eating delicious food, 3D printing, and wandering the great outdoors.

Amit Gangapuram Amit received his Ph.D. in Physics from Leibniz University Hannover in 2021, focusing on developing computational methods for extracting properties associated with quantum many-body states, mainly topologically ordered states. After being a postdoctoral fellow at Leibniz University, he moved to the Paul Scherrer Institute (PSI), Switzerland, where he focused on developing a containerized toolchain that allows for rapid deployment and benchmarking of various quantum simulators on HPC systems. His research interests include integrating multiple machine-learning techniques to study the properties of quantum many-body systems and developing and investigating system and application benchmarks for various quantum software and hardware architectures. He is currently a researcher at Leibniz Supercomputing Centre, exploring the integration of HPC and quantum computing.

Andrea Giachero Andrea Giachero is an Associate Professor at the University of Milano-Bicocca, a member of the Bicocca Quantum Technologies Centre, and the Principal Investigator (PI) of several activities in the field of quantum technologies. In 2021, the European Union honored him as a talented researcher with a Marie Skłodowska-Curie Individual Fellowship (MSCA-IF) Global Fellow (GF). Since October 2021, he has held an MSCA fellowship. From January 2022 to September 2023, he was a visiting faculty member at the University of Colorado Boulder (USA) and an international research associate at the National Institute of Standards and Technology Boulder (USA) in the Quantum Sensor Division. Although his visiting period ended in September 2023, he continued collaborating with both institutions as an external collaborator.

Andrea Giachero has more than 20 years of experience developing hardware and software for data acquisition systems in fundamental physics. Previously, his work focused on particle physics and rare events (such as neutrinos, double beta decay, and dark matter), and he is currently working in the realm of hardware and software quantum information science. He is presently coordinating projects and working packages to develop broadband quantum limited readout chains for qubit multiplexing exploiting open-source software and hardware. With an unwavering dedication to transparency and collaboration, Andrea epitomizes the principles of open science, cultivating an inclusive atmosphere conducive to idea exchange and advancing cutting-edge technologies.

Ed Younis (Added from Oct 16, 2024) Ed is a computer systems engineer at Lawrence Berkeley National Laboratory with extensive experience developing and implementing advanced algorithms for quantum compilation, such as QFAST and QFactor. He is currently the principal engineer on the BQSKit project and has research interests in quantum synthesis, compilation, and software systems.

Eduardo Maschio Eduardo Maschio builds quantum software tools and libraries for researchers and developers at Pasqal. He has also been involved in open source initiatives such as Quantum Open Source Foundation as a mentor and UnitaryFund as a grantee, developing a quantum programming language and algorithms for quantum computers and networks.

Frederic Barbaresco Frédéric Barbaresco is the leader of the “quantum algorithms and computers” segment for the THALES Corporate technical department within the KTD PCC (Key Technology Domain “Processing, Control & Cognition”). He coordinates the THALES R&T activity on Quantum Algorithms between the THALES Business Lines and the TRTs (Thales Research & Technology). He is also responsible for developing partnerships with Deeptech Start-ups and academic laboratories on this theme. In this context, he is in charge of the maturation of more than 20 THALES use cases linked to structuring market segments. For THALES, he is piloting the BACQ (Application-oriented Benchmarks for Quantum Computing) project of the LNE national MetriQs program with partners CEA, Eviden, CNRS, and TERATEC. In May 2023, he organized a TERATEC TQCI seminar at THALES TRT with LNE, which was the 1st international workshop on “Benchmarking of quantum computers”, bringing together more than 200 experts from Europe (Tu Delft, TNO, Fraunhofer, etc... ), the USA (IBM, MetriQ, etc.), Japan and Singapore. He will organize the 2nd TQCI seminar on this topic that will take place in Reims in June 2024. He organized with QuantX in 2023 the largest International Corporate Quantum Hackathon, involving more than 80 people in 5 countries (FR, GE, UK, CAN, SG) on 10 THALES use cases with nine quantum computer suppliers or emulators. He coordinated the GIFAS subgroup on “Quantum computing” with a report delivered in March 2024. He is a member of the IEEE “Quantum Computing Benchmarking” standardization working group. He represented THALES on the France pavilion at the 1st Quantum World Congress in Washington. He received the 2014 Aymée Poirson Prize from the French Academy of Sciences for applying science to industry. Ampère Medal, Emeritus Member of the SEE, and President of the SEE ISIC “Information and Communication Systems Engineering” club. He graduated from Centrale-Supelec in 1991.

Justin Gage Lietz Justin Gage Lietz, PhD, is a senior quantum software architect at NVIDIA, where he works on CUDA Quantum, an open-source programming model for building quantum-classical applications. Before NVIDIA, he worked at Oak Ridge National Laboratory, researching high-performance computing and quantum computing algorithms for physics applications.

Luke Govia Luke Govia is a research scientist at IBM Quantum, where he works on benchmarking quantum hardware with a focus on quantum error correction and mitigation. Previously, he was a scientist at Raytheon BBN and held postdoctoral researcher appointments at the University of Chicago and McGill University. He obtained his PhD from Saarland University and an MSc and BSc from the University of Waterloo. Aside from characterization and benchmarking, his research expertise lies in superconducting qubit device theory, open quantum systems, and neuromorphic quantum computing.

Olivia Di Matteo Olivia Di Matteo is an Assistant Professor in UBC's Electrical and Computer Engineering department and the Tier 2 Canada Research Chair in Quantum Software and Algorithms. She obtained her PhD at the University of Waterloo and Institute for Quantum Computing in 2019 in Physics (Quantum Information). Following her PhD she worked as a Quantum Information Science Associate at TRIUMF and as a Quantum Computing Educator and Researcher at the Toronto-based quantum startup Xanadu. At UBC, she leads the Quantum Software and Algorithms Research Lab, which focuses on designing and implementing open-source software for quantum compiler tools and physics applications.

Paul Nation Paul Nation received his Ph.D in Physics from Dartmouth College in 2010. Since then, he has focused primarily on numerical methods for quantum systems and has worked on multiple open-source projects (e.g., Qiskit and QuTiP) along that line. He is currently a principal research scientist at IBM, and he is focused on benchmarking quantum software and hardware.

Peter Groszkowski (Added from Oct 16, 2024) Peter is a researcher at the Oak Ridge National Laboratory working in various areas of physics, with emphasis on topics related to quantum computing and information. Beyond physics, he is also interested in all aspects of software development, ranging from numerical simulations to instrumentation control. Peter is a strong advocate of the open-source development model, supporting it whenever possible.

Ryan Hill Ryan is a physicist, software developer, and engineering team leader passionate about quantum computing and cloud HPC. He received his Master's in engineering physics at Cornell University, where his research focused on quantum machine learning, specifically quantum neural networks. He currently serves as CTO at qBraid, a quantum computing startup based in Chicago, Illinois. In addition to his executive role at qBraid, Ryan is a mentor at the Quantum Open Source Foundation and actively maintains and contributes to several open-source quantum software projects focusing on runtime, transpilers, and compilers.

Shannon Whitlock Shannon Whitlock is a professor of experimental quantum physics at the European Center for Quantum Sciences and the University of Strasbourg, France, and cofounder of the quantum computing startup QPerfect. Shannon completed his PhD at Swinburne University of Technology in Melbourne in 2007, followed by a Marie Curie postdoctoral fellowship at the University of Amsterdam. In 2010, he moved to the University of Heidelberg in Germany, where he started his research group and advanced quantum physics laboratory thanks to a prestigious Emmy Noether grant from the German Research Foundation (DFG). He is the coordinator of the French national public infrastructure for quantum computing aQCess and is strongly involved in major research and training programs at the European level.

Yi-Ting (Tim) Chen Yi-Ting (Tim) Chen is an Applied Scientist at Amazon Braket. His current role focuses on quantum programming experience and accessing quantum hardware. His past research focused on applying atom manipulation to study atomic physics and condensed matter physics, as well as on simulating quantum systems. He studied at Stanford University, where he received his PhD in Applied Physics, and at National Taiwan University, where he received his BS in Physics.

Metriq team at Unitary Fund Also part of the committee are Unitary Fund staff members working on the Metriq project: Dan Strano, Vincent Russo, Kallie Ferguson, Ben Castanon, and Nathan Shammah.

Resource Requirement Pipeline for Quantum Error Mitigation Capstone

Wed, 12 Jun 2024 00:00:00 GMT

We are a group of graduate students at the University of Washington (UW) who spent the last ten weeks working with Unitary Fund as participants in UW’s Accelerating Quantum-Enabled Technologies (AQET) capstone course. AQET is an interdisciplinary traineeship program involving a unique curriculum in quantum information science and engineering, including the capstone course which pairs students with industry professionals and academic mentors for a quarter-long project. We worked with Unitary Fund to create a benchmarking pipeline and GUI using the Mitiq library, with the hopes of providing users a streamlined tool to compare overhead requirements and the effectiveness of various quantum error mitigation methods in Mitiq.

About Us

Ella Carlander

I am a second year PhD student in the Physics Department at UW, where I work in Armita Nourmohammad’s lab. Our group is broadly interested in statistical biophysics, and my research is focused on using machine learning models to investigate predictors of function in immune system proteins. My interest in quantum information is very tangential to this work, so I am grateful for the opportunity to participate in AQET and further develop that interest.

Ruhee Nirodi

I’m a second year PhD student in the physics department at UW, working with Professor David Cobden. Our focus is probing and measuring fundamental quantum phenomena in 2D materials such as graphene and recently, WTe2. I have been interested in quantum information since college, and was super excited to work with the Unitary Fund to learn more about the field.

Alexandros Peltekis

I'm a first-year PhD student in Chemistry at the UW and am researching with the Xiaosong Li Group. The group focuses on electrionic structure theory. I research how "freezing" certain aspects of detailed molecular models affects the balance between computational speed and accuracy. I also am supporting the development of Chronus Quantum, our group’s open-source software. This project with the Unitary Fund provided a great opportunity to apply my skills i've learned from the AQET program to a practical problem in the world of error mitigation.

Project Background

Quantum error mitigation (QEM) is an active field of research seeking to reduce the effects of noise when performing computation on contemporary quantum devices. Several QEM techniques have been developed that vary in performance and overhead, many of which are implemented in Mitiq. However, individuals seeking to perform mitigation may have different priorities regarding the consumption of resources and performance improvement, and Mitiq does not currently address how various techniques vary in this regard. This motivates the need for a tool that can characterize and compare the overhead of these techniques, providing insight into which method may best suit one’s interests.

General Timeline:

Week 1-2: Diving into Mitiq and quantum computing: We started by familiarizing ourselves with Mitiq’s architecture and functionalities by reading documentation, playing around with some of the error mitigation tutorials, and asking many questions.

Week 3-5: Executors, metadata, and the GUI: These weeks we became accustomed with Mitiq’s executor functions, and established our analysis pipeline by first focusing on Mitiq’s Zero-Noise Extrapolation (ZNE) implementation. We also set up metadata extraction, and got started building GUI to access some of our data.

Week 6-8: Testing and Refining: With the core components in place, we extended our analysis to with other Quantum Error Mitigation methods: Probabilistic Error Cancellation (PEC), Digital Dynamical Decoupling (DDD), and Readout Error Mitigation (REM).

Week 9-10: Finalizing and Presentation: In the final weeks, we added finishing touches to the pipeline and GUI and prepared for their presentations. We participated in Unitary Fund’s Quantum Wednesday (our presentation) and presented at a couple of our university’s poster sessions (our poster).

Results

In order to directly compare certain overhead parameters for each QEM technique, we ran a standardized experiment using each technique. We generated 10 mirror circuits---a type of quantum benchmarking circuit---each with fixed depth and number of shots, increasing the numbers of qubits. We used two tailored noise models run on simulators---a thermal relaxation model with an added readout error, and a depolarizing noise model with single and two-qubit errors. Prior to running any sweeps involving mitigation, we ensured that our pre-mitigated expectation values were comparable using both noise models, thus ensuring our initial results were standardized. We then ran sweeps over the circuit qubit number with error mitigation and recorded various measures of overhead required when using the mitigation. Overhead measurements included the additional number of single and two-qubit gates required, the total added circuit depth, the number of additional unique circuits needed to be run, and the additional time required to run each technique. The "no error mitigation" comparison was run on our thermal noise model. The results for the time requirements are are shown in the graphs below.

We see that the time required for implementing each technique varies greatly between the different methods, as does the way those time requirements scale with the size of the input circuit. The behavior displayed by each method can be qualitatively explained by the theory behind how the mitigation is performed. For instance, DDD works by simply modifying vacant parts of the input circuit, not requiring any additional circuits to be run. This explains why we see very low additional time costs for that method. On the other hand, ZNE requires the execution of several circuits, each with a number of operations that scales linearly in the number of qubits N. Each operation has a standard runtime, so the total time cost scales linearly, which is roughly what we see. REM requires inverting a 2N×2N matrix, explaining its steep increase in time cost for large N. Lastly, PEC’s behavior is explained by the fact that it requires running many versions of the input circuit, which takes more and more time as the complexity of that input increases.

This analysis is one demonstration of how important it is to characterize the overhead of QEM techniques, as time is almost always an important consideration for quantum researchers. We performed a similar analysis for the other measures of overhead that we considered, which also exhibit variation between techniques. Being able to see this type of information is helpful to someone unsure about which error mitigation technique fits their individual constraints.

Closing notes

A Tool for Comparison

In our project, we aimed to create a comprehensive tool that makes it easier for users to compare QEM methods. We developed:

A Pipeline for QEM Comparison: Our pipeline evaluates the performance and computational overhead of different QEM techniques, providing a structured framework for comparison.
A User-Friendly GUI: We designed an intuitive graphical user interface that simplifies the process of visualizing and comparing the results of different QEM techniques.

Working on this project has been an extremely rewarding experience for all three of us, and we are proud of what we have accomplished as a group. Throughout this process, we learned valuable information about quantum error mitigation and open-source quantum software while strengthening important skills in effective communication, software development, and time management. We would like to thank Nate Stemen for mentorship throughout this project, Boris Blinov and Brant Bowers at UW for advising, and the Unitary Fund community and AQET program for supporting us.

Celebrating a Milestone: Over 100 Microgrants Awarded by Unitary Fund

Tue, 11 Jun 2024 00:00:00 GMT

The Unitary Fund's microgrant program recently marked an incredible milestone: over 100 microgrants awarded! This achievement highlights the program's pivotal role in advancing open source quantum technology projects globally. Through grants and open-source ecosystem development, Unitary Fund fosters a flourishing, multiplying effect within the broader quantum ecosystem. These small but impactful investments drive accessible and transparent progress, essential for unlocking the full potential of quantum technology.

Thank you to our sponsors for making these microgrants possible! Core Members: IBM Quantum, DoraHacks, OQD, and Scientifica; Supporting Members: AWS, Microsoft, Pasqal, QC Ware, IonQ and SandboxAQ.

To commemorate this event, we spoke with our current and former grant recipients to gauge the impact and reach of their supported projects. Here’s what we found.

This impressive impact was obtained for less than the cost for a U.S. university to provide two fully funded PhD studentships from enrollment to graduation.

Impact to the Community: Growing the Ecosystem

The survey highlighted significant contributions to the broader quantum technology community. Many projects have inspired collaborations and integrations with other tools and platforms. Shinichi Sunami’s graphix project, for example, has integrated with Perceval, fostering interoperability and expanding its utility. Xiuzhe (Roger) Luo’s grant project Yao.jl was the start of QuEra’s software development kit Bloqade. The pyZX project by Aleks Kissinger and John van de Wetering led to additional projects QuiZX, a speedy rust port of pyzx, and Quantomatic zxlive, a GUI frontend.

With over 400+ contributors across projects, Unitary Fund microgrants are useful spaces to grow our open source tooling. They represent a vibrant community of individuals contributing code to open source tools and citing microgrant work in papers over the last 6 years, creating more than 40 different libraries.

Projects such as QWorld, Iteration One, and <Quantum|Chamitas> have facilitated educational opportunities and professional networking, reaching thousands of unique individuals globally. The microgrants have also led to the creation of 3 separate startups and 1 non-profit.

Notably, there are more than 420 papers that cite research coming directly from Unitary Fund’s microgrants, supporting thousands of researchers globally in their own research and papers, providing a significant contribution to the quantum ecosystem. Some notable papers include the PyZX whitepaper (a compiler that maps quantum circuits to graphs using ZX calculus) or the QuNetSim simulator white paper (a quantum internet simulator built on top of QuTiP).

Impact to the People: Beyond the Project

The microgrant recipients reported substantial personal and professional growth as a direct benefit of the program. Here are some key takeaways: 87% of microgrants resulted in additional resources to the micrograntee, including additional financial funding, hardware access, new collaborators or contributors, or new professional networks.

87% of microgrants resulted in career advancements, from academia, industry, or helping them to pivot their careers. 51%+ of microgrants have gone to individuals belonging to a historically underrepresented group in STEM, highlighting the program's commitment to diversity and inclusion in the quantum computing field.

Hear the impact from Microgrant recipients

“You are one of the best things that happened to quantum software. Please continue the no nonsense approach.” - Fred Jendrzejewski

“I would like to express my sincere gratitude to UF for their invaluable support. I truly appreciative of UF's commitment to fostering innovation and collaboration in the field of quantum computing.” - Dafne Carolina Arias Perdomo

"I am so thankful for this opportunity and truly appreciate your commitment to open quantum science!" - Mattias Fitzpatrick

“The visibility at unitaryhack prompted a discussion and then a collaboration with INRIA-Paris team and U of Edinburgh team working on blind quantum computing.” - Shinichi Sunami

“As a young student from a low income country I had no means to work on academic projects since they were always unpaid. But with the help of Unitary Fund's grant during COVID, I was able to work on my first proper theoretical project. This project was the first step towards building my foundations in theoretical research and I believe I wouldn't have worked on any other research projects without it.” - Muhammad Usman Farooq

Looking Forward

As we celebrate this milestone, the Unitary Fund remains committed to supporting innovative quantum computing projects. The feedback from our grant recipients will guide future iterations of the program, ensuring that we continue to foster innovation, collaboration, and growth in the quantum computing space.

The success of these projects is a testament to the creativity, dedication, and hard work of the quantum computing community. We look forward to the next 100 microgrants!

Join Us: Whether you’re a researcher, developer, or enthusiast, get involved with the Unitary Fund’s initiatives and be part of the growing ecosystem. Together, we can achieve more!

Apply here for a microgrant and make sure to follow our Discord, X, LinkedIn, and our [email protected]">Community Calendar for all the latest updates!

unitaryHACK 2024 is Live: Contribute to Quantum Open-Source!

Thu, 30 May 2024 00:00:00 GMT

The Unitary Fund hackathon supporting quantum open source projects is happening now! unitaryHACK is a virtual event encouraging people to make contributions to the open source quantum ecosystem. The event will run May 29-June 12, 2024, and hackers have the opportunity to win cash bounties! unitaryHACK is unique to many quantum hackathon-style events for two big reasons:

Hackers support existing quantum computing projects.
Hackers get paid for their work while building professional skills such as working on open source projects, and contributing to create a more functional, and featured, quantum computing stack.

unitaryHACK 2024 is the largest edition yet, hosting 50 amazing open-source projects: AI-inspired Classification of Quantum Computers, Amazon Braket Default Simulator, Amazon Braket SDK, AutoQASM, Azure Quantum Development Kit, bloqade-python, BQSKit, Braket.jl, BraketAHS.jl, BraketSimulator.jl, Cirq, Cirq Classiq Library, CUDA-Q, Fusion Blossom, graphix, HierarQcal, Ion(Q) Thruster, KQCircuits, lambeq, Metriq, Mitiq, OpenQAOA, OpenQASM 3 Parser, PennyLane, PennyLane Plugin for Amazon Braket, Perceval, Piccolo.jl, PyClifford, Qadence, qBraid-QIR, qBraid-SDK, Qiskit, Qiskit Aer, Qiskit Provider for Amazon Braket, qlasskit, Qrack, Quantum Machines QUA-to-Qiskit compiler and simulator, Quantum Open Source Foundation (QOSF), Quantum Universal Education, QuantumToolbox.jl, Qublitz, QuTiP Tutorials, rustworkx, scqubits, Tangelo TensorCircuit toqito TorchQuantum

For more information, read our hacker guide and check out what happened in unitaryHACK 2023 and get connected on our Discord server!

Make sure you register to be eligible to claim your bounties!

Ready to get hacking? Check out all of our live bounties!

Hacking IRL

This is the first year our amazing global community is hosting in-person meetups at various locations, so if you're somewhere near, you can attend:

May 31: Aalto University CS in Helsinki, Finland, starting at 18:00 for 24 hours. Pizza available!
May 31: Auditorio Raúl J. Marsal, Ciudad Universitaria, UNAM in Mexico City, Mexico, at 16 HRS UTC-6!
June 11: University of Washington HUB 145, Seattle, WA, USA, from 9 am to 5 pm, food will be available!

If you'd like to host an event at your university, drop us a line at [email protected], and we'll spread the word!

Thank you to our supporters and maintainers who make this event possible!

Core Members: IBM Quantum, DoraHacks, OQD, and Scientifica;

Supporting Members: AWS, Microsoft, Pasqal, QC Ware;

Event Sponsors: NVIDIA, QBraid, Classiq, and QuEra

A huge thank you to all of our project maintainers volunteering time to review pull requests and engage with the community!

Meet the UF interns - Srila Palanikumar

Tue, 28 May 2024 00:00:00 GMT

As part of Qubit by Qubit’s Early Quantum Career Immersion program, I was placed as a summer 2023 intern with Unitary Fund. This program was created to give students who are underrepresented in quantum computing opportunities to advance their careers, as well as to amplify their voices and support them. The first three weeks of this program were rigorous training in concepts in quantum computing and mechanics, and the next seven were a full-time internship with UF.

About me

I’m a third-year student at UT Austin studying computational biology and mathematics. I’m also pursuing a minor in computer science. I’m interested in biophysics and quantum chemistry, and I enjoy working out and reading in my free time. At UT, I’ve worked on research projects involving ecological data mining and QML for linear algebra.

My internship

The internship started on June 26th, 2023, after the training period with QxQ. The first big task I was assigned by my primary supervisors, Dan Strano and Vincent Russo, was to get the development environment set up locally on my computer. This required me to understand a lot of the basics of software development that I had never learned in my classes. For example, I started using virtual environments and managing packages. Around the same time, I was assigned to add research papers to Metriq. This helped me learn a lot of basic concepts in quantum computing, since I had to parse through the papers to determine their findings.

Within the first two weeks of the internship, I also had lots of great one-on-one chats with UF team members, including Misty, Nate, and Will. Everyone was so nice and welcoming to the community, and I’m really glad I got to get to know the people I was working with on a closer level. They gave me lots of great advice I’ve been using regularly in this internship and my other work.

On the week of July 6th, I was also assigned to convert content on the old site, which was in pure HTML, to markdown for the new website. While this work wasn’t as software intensive, I learned a lot about how to use GitHub. This includes figuring out how to use pull requests, branches, and Git on the command line. I believe this will be a valuable skill as I continue to work in tech.

After I made some headway on this assignment, Dan suggested to me that I do a Quantum Wednesday talk so that I could get more involved with the community. I was interested in Google Quantum AI’s paper, Suppressing quantum errors by scaling a surface code logical qubit. I spent about two weeks preparing for this talk by reading and rereading the paper many times, watching videos about it, and having my materials reviewed by Dan and Nathan. The talk itself was on July 26th, and although it was a huge challenge to present for about 30 minutes straight, I think it went well! This was the highlight of my internship since it pushed me so far out of my comfort zone.

After the talk, I worked on two major projects: continuing content conversion for the new website, and working on enhancing the Metriq client. The first task I took on was updating naming conventions across the client’s functions and making sure that these were consistent across Metriq. Some other open issues I worked on include creating a new function to get the number of paper submissions per platform and updating the README to showcase more of Metriq’s capabilities. I worked on these and this blog post until my last formal day with Unitary Fund, August 11th, 2023.

Closing notes

I’m extremely grateful to Unitary Fund and Qubit by Qubit for this amazing experience. I learned so much about software engineering and quantum computing. This is my first formal internship, so I’m glad it went smoothly. Shoutout to Dan, Vincent, and Nathan for being amazing mentors for the last seven weeks, and shoutout to the Unitary Fund community as a whole for being a warm, welcoming community. I plan to continue contributing to open-source projects in the future!

Stay up to date on my work by connecting with me on LinkedIn.

Unitary Fund Q1 2024 Update: 100 microgrants, unitaryHACK, new research and project updates

Thu, 25 Apr 2024 00:00:00 GMT

Dear Unitary Fund community,

We are excited to share our 2024 Q1 quarterly update! We reached a huge milestone, surpassing 100 microgrants given to the community to support quantum open source projects. These microgrants have been awarded to people in 30 countries, resulting in 25+ papers, 40+ libraries, 100+ contributors and about 6k commits (excluding QuTip), 2 startups and 1 non-profit. A huge thank you to our members who make this work possible!

We awarded 7 new grants in Q1, including integration of Mitiq into OpenQAOA, building quantum programming content platforms, a quantum education initiative for girls in France and Venezuela, an entanglement toolbox for t-doped stabilizer states, and more! Additional details on each grant are available below.

We have also been hard at work preparing for our 4th edition of unitaryHACK, an international virtual open-source hackathon where we give quantum projects cash to distribute to contributors by means of bounties. Last year, unitaryHACK had 700 participants and 72 hackers claimed 99 bounties, with more than $11k awarded. With over 30 registered projects and more to come, this year’s unitaryHACK is shaping up to be the largest one yet. If you would like to host an in-person meetup in your city to give your local community a space to gather, form teams, and work on unitaryHACK bounties, email [email protected]">[email protected]. to let us know! And make sure to register to participate for your cash prize!

This summer we will be hosting a Mitiq workshop as part of the summer school on Numerical Methods in Quantum Information Science, taking place in Boston. The school will cover best practices in software engineering, as well as the fundamentals of high-performance modeling techniques including state vector master equations, tensor networks, and the stabilizer formalism and its generalizations -- crucial tools in modeling quantum hardware and error correction. Multiple hackathons will be executed where instructors will be able to help you with your own research projects. To register for the school and to see more details, please go to qnumerics.org.

Thank you all for your continued support of the open-source quantum ecosystem!

Make sure to follow our Discord, X, LinkedIn, and our [email protected]">Community Calendar.

New From Unitary Fund

Research

Unitary Fund Staff contributed to the “Report for the ASCR Workshop on Basic Research Needs in Quantum Computing and Networking”, which is now published online.
Vincent Russo and Andrea Mari from Unitary Fund and University of Camerino introduce in [2402.04000] layerwise Richardson extrapolation, a new quantum error mitigation protocol generalizing zero-noise extrapolation, in which the noise of different individual layers (or larger chunks of the circuit) is amplified and the associated expectation values are linearly combined to estimate the zero-noise limit.
The review on open hardware in quantum technology, co-authored by UF staff Nathan Shammah, Andrea Mari, Will Zeng, and many UF community members got published in the first issue APL Quantum, getting the journal cover!
Will Zeng co-authored with UF board member Travis L. Scholten and other co-authors a white paper “Assessing the Benefits and Risks of Quantum Computers” [2401.16317] reporting on the fact that “there is a credible expectation that quantum computers will be capable of performing computations which are economically-impactful before they will be capable of performing ones which are cryptographically-relevant”.

Metriq

Metriq has added a feature view on variational quantum algorithms (VQAs) from the work of Joan Étude Arrow (member of the QED-C Standards Committee) and her collaborators, collected with other VQA results.

Metriq launched an Open Quantum Benchmark Committee composed of a representative pool of experts in the field of quantum computing and quantum technology with domain expertise relevant to quantum benchmarks. More details to come soon!

Mitiq

New Releases: v0.34.0, v0.35.0

v0.35.0: In this milestone, we've continued our work to support Qibo by providing a new tutorial, adding related Qibo-conversion functionality to the API-doc, and adding Qibo to our main list of supported frontends. We've also added the capability to use rotated randomized benchmarking circuits as part of the calibrator.
v0.34.0: Announcing support for Qibo, a newly integrated frontend in Mitiq! 📣

Qibo is an "end-to-end open source platform for quantum simulation, self-hosted quantum hardware control, calibration and characterization". Read more about this Mitiq release in Francesc Sabater’s blog.

Aquapointer

We have completed another key milestone in our Q4Bio collaboration with Pasqal and Qubit Pharmaceuticals with new features added to our OSS package aquapointer. The new features are for processing density files representing the structures of protein cavities of interest. We also continue to refine the digital algorithm and resource estimates on benchmark protein hydration problems.

Events:

Where can you find Unitary Hack this summer? Look for us at these places!

May 29-June 12: unitaryHACK
June 24 2024: Workshop on Quantum Software 2024, which will take place in Copenhagen
July 9-12: JuliaCon 2024, where Nathan Shammah will be giving a talk on “Nurturing a quantum open-source ecosystem.”
August 12-18: Summer School on Numerical Methods in Quantum Information Science: This summer we will be hosting a Mitiq workshop as part of the summer school on Numerical Methods in Quantum Information Science, taking place in Boston.

Microgrant Updates:

QuTiP: The second QuTiP Developer Workshop was held at RIKEN, in Japan, March 24th-29th, 2024, bringing together over 25 contributors and project maintainers from all over the world. The project is lively, with updates on optimal control, GPU and HPC acceleration, QPU access and even a Julia package. During the workshop, QuTiP 5.0 was released, the first major release in 7 years!

Toqito: toqito-v1.0.8 was released earlier this year.

If you are a Python developer and are interested in contributing to the toqito project or a researcher who wishes to use toqtio in your workflow, feel free to reach out on GitHub or Discord!

TQEC: Development of the Topological Quantum Error Correction (TQEC) circuit editor MVP is underway.

You can specify a 2D grid of qubits, and add plaquettes representing X and Z stabilizers to build a surface code. If you would like to contribute, checkout our GitHub repo.

OpenQAOA: Micrograntee winner Alejandro Montañez-Barrera recently co-authored Transfer learning of optimal QAOA parameters in combinatorial optimization [2402.0554]. The paper discusses how evidence shows that fixed parameters give similar performance to exhaustive classical optimization search for MaxCut in QAOA. In this work, they extend this study and show the transfer learning (TL) capabilities of QAOA between different combinatorial optimization problems (COP) for up to 42 qubits. They experimentally evaluated these TL QAOA protocols on IonQ Harmony and Aria, IBM Brisbane, and Rigetti Aspen, finding that information can be recovered to some extent. They go a step further and demonstrate that TL is also possible between platforms, modifying the D-Wave Advantage quantum annealing schedule with that obtained in QAOA. They found an improvement in performance on instances of maximal independent set up to 170 qubits.

Alejandro Montañez-Barrera created a demo tutorial on pennylane about encoding combinatorial optimization problems.

Qlasskit: The second stable release of qlasskit tagged as version v0.1.17. It includes:

Exporter for binary quadractic models (QUBO, BQM and ISING)
Support for parameterizable qlassf functions.
Exporters for Sympy, Qutip, Pennylane and qasm2
Quantum circuit experimental decompiler and optimizer
Bugfixing and performance improvements

HierarQcal: Check out the new blog with updates!

QWorld: The autumn semester of QClass23/24 successfully concluded, and 485 certificates have been handed out

QCourse101 "Fundamentals of Quantum Computing & Programming": 175
QCourse501 "Elements of Quantum Computing and Programming": 227
QKD self-study module: 55
QJam2024 "Making Quantum Games": 28

New Grants:

To Kein Yukiyoshi, Adam Siegel and Tyson Jones to further develop Global Expansion of QCoder, a quantum programming contest platform.
To Marin Girard to further develop Holistic ACL model + decoherence notebooks using Qutip, to complement the current implementation of the ACL model in Qutip by making it holistic, including all the necessary tools to explore it as well as making it freely accessible on GitHub.
To Marco Venere, Adriano Lusso, Alberto Maldonado and Victor Onofre to develop Integration of Zero-Noise Extrapolation from Mitiq into OpenQAOA, which will integrate Mitiq into OpenQAOA to allow error mitigation techniques to take place during the execution of the QAOA algorithm.
To Andi Gu, Lorenzo Leone, & Salvatore F.E. Oliviero to further develop An entanglement toolbox for t-doped stabilizer states beyond the classical simulability barrier, a toolbox to equip researchers with theoretical tools and a Python framework to study t-doped states' entanglement efficiently
To Sam Burdick to further develop Topological Quantum Error Correction (TQEC), expanding an existing open-source TQEC service.
To Mattias Fitzpatrick to further develop Qubit-Pulse: An educational qubit pulse engineering game, a pulse simulator game that takes in drive amplitudes as a function of time and produces the qubit state in the Bloch sphere to allow users to simulate different Hamiltonians and controls.
To Dafne Carolina Arias Perdomo to further develop <Quantum|Chamitas>, a pioneering initiative focusing on accessible, high-quality quantum education in both Venezuela and France for girls in STEM.

Other News:

We've expanded our board!
2023 Annual Report was released, check it out!
Qiskit 1.0 has gone live!

Qiskit-Qulacs - Execute Qiskit programs using Qulacs backend

Thu, 04 Apr 2024 00:00:00 GMT

Qiskit is a popular choice among developers and researchers working in the field of quantum computing. It offers a wide range of functionalities and has useful extensions for algorithms, chemistry etc. On the other hand, Qulacs is known for its efficient quantum circuit simulation. Qiskit-Qulacs aims to act as a bridge between these two libraries. In this article, we'll explore how the Qiskit-Qulacs offers users the best of both worlds.

The library is designed to make use of Qulacs' fast simulation while abstracting it within Qiskit's familiar environment. This allows users to create quantum circuits using Qiskit and execute them using Qulacs as the backend, resulting in faster circuit execution times for tasks like state vector simulations, calculating expectation values, and circuit gradient computations.

Getting Started

Let's see how easy it is to use the Qiskit-Qulacs with a simple example. We create and run a 3-qubit GHZ state using Qiskit-Qulacs:

import matplotlib.pyplot as plt
from qiskit import QuantumCircuit
from qiskit.visualization import plot_histogram, plot_state_city

from qiskit_qulacs import QulacsProvider

# Create a bell state
qc = QuantumCircuit(3)
qc.h(0)
qc.cx(0, 1)
qc.cx(0, 2)

# Use Qiskit-Qulacs to run the circuit
backend = QulacsProvider().get_backend("qulacs_simulator")
result = backend.run(qc, shots=1024, seed_simulator=42).result()
counts = result.get_counts()

# Visualization
plot_histogram(counts)
plt.show()

If we remove the shots parameter, we can obtain the statevector

result = backend.run(qc).result()
statevector = result.get_statevector()

# Visualization
plot_state_city(statevector, title="3 qubit GHZ state")
plt.show()

Primitives examples

The current release v0.1.0 introduces several interfaces:

QulacsEstimator allows users to quickly compute the expectation values of observables using Qulacs' get_expectation_value.
QulacsSampler is useful for sampling purposes and uses Qulacs' QuantumState.

Defining these primitives makes it easy to integrate Qiskit-Qulacs with Qiskit and its extensions. Let's see an example demonstrating the usage of QulacsEstimator and QulacsSampler. Also, check out the tutorial on the same in Qiskit-Qulacs documentation.

import matplotlib.pyplot as plt
import numpy as np
from qiskit.circuit.library import RealAmplitudes
from qiskit.quantum_info import SparsePauliOp
from qiskit.visualization import plot_histogram

from qiskit_qulacs.qulacs_estimator import QulacsEstimator
from qiskit_qulacs.qulacs_sampler import QulacsSampler

np.random.seed(0)

# Create a circuit, an observable and parameters
num_qubits = 3
qc = RealAmplitudes(num_qubits).decompose()
obs = SparsePauliOp.from_list([("Z" * num_qubits, 1)])
params = np.random.uniform(low=-np.pi, high=np.pi, size=qc.num_parameters)

# Initialize Qulacs Estimator
qulacs_estimator = QulacsEstimator()

# Compute expectation value
result = qulacs_estimator.run([qc], [obs], [params]).result()
print(f"Expectation value: {result.values[0]:.4f}")  # Output: 0.7954

# Obtain Quasi distribution
qc.measure_all()
qulacs_sampler = QulacsSampler()
result = qulacs_sampler.run([qc], [params]).result()

plot_histogram(result.quasi_dists[0])
plt.show()

Circuit Visualization

Due to abstraction, the converted circuits are not directly available but are stored as the class's non-public attribute. We can use qulacs-visualizer to draw the qulacs circuit.

from qulacsvis import circuit_drawer

qc = qulacs_estimator._circuits[0]
qulacs_circuit, _ = qc(params)

circuit_drawer(qulacs_circuit, "mpl")
plt.show()

Gradients

The class QulacsEstimatorGradient uses efficiently Qulacs' backprop method to compute gradients efficiently. It is enhanced with sympy to support Qiskit's ParameterExpression which is not natively supported in Qulacs. The below example uses $\theta^2 + \cos\theta$ an in input to the $R_x$ gate.

import numpy as np
from qiskit import QuantumCircuit
from qiskit.circuit import Parameter
from qiskit.quantum_info import SparsePauliOp

from qiskit_qulacs.qulacs_estimator_gradient import QulacsEstimatorGradient

np.random.seed(0)

# Create a circuit, an observable and parameters
theta = Parameter("θ")
theta_val = [0.4]

qc = QuantumCircuit(1)
qc.rx(theta**2 + np.cos(theta), 0)

obs = SparsePauliOp.from_list([("Z", 1)])

# Compute gradients
qulacs_gradient = QulacsEstimatorGradient()
result = qulacs_gradient.run([qc], [obs], [theta_val]).result()
print(f"Gradient: {result.gradients[0][0]:.4f}")  # Output: -0.3623

VQE with Qiskit-Qulacs

We will use the Qiskit-Qulacs primitives and gradients to compute the electronic ground state energy of $H_2$ molecule. Instead of implementing VQE from scratch, we use the VQE class from qiskit-algorithms and demonstrate the capabilities of Qiskit-Qulacs.

from qiskit import transpile
from qiskit_algorithms.minimum_eigensolvers import VQE
from qiskit_algorithms.optimizers import L_BFGS_B
from qiskit_algorithms.utils import algorithm_globals
from qiskit_nature.second_q.algorithms import GroundStateEigensolver
from qiskit_nature.second_q.circuit.library import UCCSD, HartreeFock
from qiskit_nature.second_q.drivers import PySCFDriver
from qiskit_nature.second_q.mappers import JordanWignerMapper

from qiskit_qulacs.qulacs_backend import QulacsBackend
from qiskit_qulacs.qulacs_estimator import QulacsEstimator
from qiskit_qulacs.qulacs_estimator_gradient import QulacsEstimatorGradient

algorithm_globals.random_seed = 42

# Define the molecular system
driver = PySCFDriver(atom="H 0 0 0; H 0 0 0.735", basis="sto3g")
problem = driver.run()
mapper = JordanWignerMapper()  # Qubit Mapper

# Variational form
ansatz = UCCSD(
    problem.num_spatial_orbitals,
    problem.num_particles,
    mapper,
    initial_state=HartreeFock(
        problem.num_spatial_orbitals,
        problem.num_particles,
        mapper,
    ),
)

# Transpile for simulator
transpiled_ansatz = transpile(ansatz, QulacsBackend())

# We set the global phase to zero as qulacs does not supports
# computing its hermitian conjugate which is needed
# during gradient compuatation.
transpiled_ansatz.global_phase = 0.0

# The solver
vqe_solver = VQE(
    QulacsEstimator(),
    transpiled_ansatz,
    L_BFGS_B(),
    gradient=QulacsEstimatorGradient(),
)

# The calculation and results
calc = GroundStateEigensolver(mapper, vqe_solver)
res = calc.solve(problem)

print(f"Electronic ground state energy (Ha): {res.eigenvalues[0]:.4f}")  # -1.8573

Conclusion

Qiskit-Qulacs integrates the Qulacs' simulator with Qiskit quantum computing framework. Additionally, the library includes source code for benchmarking the execution time with varying qubits. The plots can be found in the documentation and the corresponding code in the benchmarks directory.

For more information, tutorials, and documentation, explore the following links:

Repository.
Documentation.
PyPi.
Progress documented in the microgrant duration for Phase I and II.

We extend our gratitude to the Unitary Fund for supporting this project with the microgrant program, and we're excited to be part of the Qiskit Ecosystem. Feel free to reach out to me on LinkedIn if you have any questions or comments.

Unitary Fund 2023 Annual Report

Mon, 11 Mar 2024 00:00:00 GMT

To the Unitary Fund community,

Last fall, we hosted our inaugural unitaryCon, bringing together our microgrant recipients and community members for the first time in person. This event underscored the importance of our shared vision for a better future through technology and the vital role of our growing, diverse community in realizing this vision. People build quantum technology. And our focus is on nurturing that emerging community of people.

This community now spans the 100+ microgrant winners from 25+ countries, the unitaryHack participants, the thousands online on Discords, youtube, and social media, the maintainers and bug fixers on github, the unpaid and constructive peer reviewers, the graduate students going the extra mile to upload tutorial code along with their arXiv papers, and the many supporters from often competing companies who understand where and why we need to all work together. Your contributions are invaluable and recognized.

This year we have grown and expanded our programs:

Mitiq, our quantum error mitigation compiler, surpassed 100k downloads, with contributions from 67 individuals
unitaryHack grew to 700 participants from 80+ countries, awarding 99 bounties across 33 projects
Our second Quantum Open Source Software Survey tracked developments in the developer ecosystem
Metriq introduced new tools for tracking state-of-the-art metrics and resource estimates in quantum technology
We awarded a record 23 microgrants for projects ranging from quantum error correction tools to Open Quantum Hardware, a field surveyed in our whitepaper

And much more that you will read about in the full 2023 annual report.

Our whitepaper on quantum computing's risks and benefits highlights the field's potential for economically impactful computations before cryptographically relevant ones. Let us work together towards that future.

Thanks to all of you who have joined us in this mission.

We are just getting started,

William Zeng, PhD

President, Unitary Fund

Open Hardware Solutions in Quantum Technology

Thu, 07 Mar 2024 00:00:00 GMT

The software stack in quantum computing is widely open source. Now tools and frameworks related to quantum hardware are progressively getting open.

We have recently reviewed the status of open hardware solutions in quantum technology in the first review article[^1] on the field, published in the first issue of APL Quantum. The paper provides a of open hardware today, lists several examples of existing tools and provides recommendations for the field development. Among co-authors of this study, are researchers from several institutions and organizations across academia, industry and government[^2], based in several continents, witnessing the wide effort underway.

Open quantum hardware today

The phases for opening hardware in quantum technology projects can be split as: 1. Design phase; 2. Fabrication step; 3. Installation and bring-up; 4) Sustained operation. For all these phases and steps, there exist already several projects and frameworks. As software tools are ubiquitious, e.g., in the modern design phase of processors, instead of simple blueprints, "open hardware" often involves software packages and frameworks developed to standardize, automate and process specific actions.
Notable examples of software tools for design include pyEPR, KQCircuits and Qiskit Metal. For control and data acquisition from quantum processing units, projects such as ARTIQ, QICK and QubiC leverage FPGAs and pulse-level radio-frequency signals for faster operation.

Photomask layout and chip design with KQCircuits for superconducting circuit-based processors.

As detailed in the review article, the number of projects and open hardware solutions varies broadly depending on the qubit architecture: The most represented one is superconducting circuits.

Ecosystem growth

At Unitary Fund we're committed to the growth of this ecosystem, as we did co-organizing the first workshop on the subject back in 2021 at IEEE Quantum Week, helping organize the first pyEPR online meetup, and hosting the QICK project weekly community calls on the UF Discord server (every Friday at 1pm PT). The first Unitary Fund grants for open hardware projects have been awarded to further develop labscript-qc and sqooler ( sqooler such that it allows experimentalists and theorists a common remote SDK) and OpenQuantum, a blueprint for a magneto-optical trap that open-sources high-quality CAD files, electronic schematics, control firmware and assembly instructions along with teaching materials to create a much-needed educational platform for quantum science and engineering. We welcome the establishment of a growing number of facilities such as foundries, testbeds and centers for cloud-based open access, such as Sandia's QSCOUT or the Open Quantum Design.

If you'd like to learn more about the open-hardware ecosystem, join an upcoming Quantum Wednesday talk on the Unitary Fund Discord server, on April 10, 2024 at 9:30 am PT / 12:30 pm ET/ 6:30p m CET.

[^1]: N. Shammah et al., "Open hardware solutions in quantum technology", APL Quantum 1 011501 (2024). [^2]: Unitary Fund, Qruise GmbH, Technical University of Valencia, M-Labs Limited, Lawrence Berkeley National Laboratory, Fermi National Accelerator Laboratory, Sandia National Laboratories, IQM Quantum Computers, PASQAL, Quantonation, Michigan State University, Università di Camerino, Microsoft Quantum, University of California at Berkeley.

HierarQcal - Quantum circuit generation and general compute graph design

Wed, 06 Mar 2024 00:00:00 GMT

We've made some improvements to Hierarqcal since its initial release last year. I hope to summarise the notable ones in this post and give some examples. The biggest change of all being a new logo:

<div style="display: flex; justify-content: space-around; align-items: center;"> <div style="display: flex; flex-direction: column; align-items: center;"> <img src="/images/2024_hierarqcal_1.png" alt="" style="width: 250px;border: 2px solid black;" /> <span style="font-size: 0.6em;">A cute robot building itself with artificial intelligence, pencil drawing - DALL·E 2 </span> </div> <span style="font-size: 24px; margin: 0 10px;">→</span> <div style="display: flex; flex-direction: column; align-items: center;"> <img src="/images/2024_hierarqcal_2.png" alt="" style="width: 250px;border: 2px solid black;" /> <span style="font-size: 0.6em;">A cute robot building itself with artificial intelligence, pencil drawing - DALL·E 3 </span> </div> </div>

But, there are other changes too, we have:

New Tutorials
- Grover's Algorithm, thanks to @AmyRouillard
- The Quantum Fourier Transform, thanks to @AmyRouillard
- VQE of Hydrogen Molecule, thanks to @Gopal-Dahale
Core Functionality Improvements
- General compute graph generation
- A new Qpivot primitive thanks to @AmyRouillard
- Reworked the Qmask primitive
- Functionality to parametrise gates based on functional relationships
User Interface Improvements
- A new plot_circuit function to visualise abstract circuits
- New plotting functions for visualising hypergraphs thanks to @metalcyanide
- The ability to generate qiskit circuits with strings thanks to @khnikhil
Research
- Overview of the representation and application to Quantum Phase Recognition
- Application in generating circuits for pulsar classification

For a quick overview, I'll share these interactive slides which was presented at unitaryCON and QTML 2023. It showcases a lot of the new functionality and provides some step by step examples (select the frame and use up, down, left and right arrows). If you're interested, you can find the full set of slides online. <div style="display:flex; align-items: center;justify-content: space-around;"> <iframe src="https://matt-lourens.github.io/talk_2023_hierarqcal?slides=16,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,68,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,97,98,99,100,101" width="100%" height="600" frameborder="0" allowfullscreen, style="border:1px solid black"></iframe> </div>

A brief walk through the new stuff

At its core HierarQcal is a tool to generate compute graphs. It leverages a hierarchical representation to enable both user and machine to design these graphs in a modular and (unsurprisingly) hierarchical way. For example, when "designing" an algorithm for multiplication we use "units" of addition repeated in some pattern. That unit of addition consists of "units" of adders which themselves consists of "units" of logic gates, such as "and" or "or". HierarQcal provides an interface to work on these different levels, so that a machine for example, can create their own units and use them to build higher level units (motifs). The highest level unit is then the algorithm it designed.

For example, hierarqcal may be used to generate ansatzes for quantum algorithms, such as the Variational Quantum Eigensolver (VQE). It is also possible to generate Quantum Convolutional Neural Networks (QCNNs) for Quantum Phase Recognition (QPR) as demonstrated in our recent paper. There we utilise an evolutionary algorithm to apply the above ideas for classifying quantum phases of matter. The modular and hierarchical nature of the representation compliments evolutionary algorithms, where your units are "genotypes" that mutate and combine to form more complicated units. Below we show a simple example of such an algorithm, it consists of the following steps:

Initialise a population of random circuits (primitive cells)
Select a subset of the population (tournament selection)
From the subset, gather the top two performing circuits
Mutate each of the top two performing circuits to create two new circuits
Combine (join) the top two performing circuits to create one new circuit
Throw the 3 new circuits into the population, along with the original two
Repeat step 1-6 until some stopping condition is met

To facilitate more general compute graph generation we've added the ability to provide any python function as a mapping for motifs. These functions are of the form:

def generic_f(bits, symbols=None, state=None):
    pass

where state corresponds to some arbitrary object that gets passed around and is manipulated in the function, symbolscorrespond to any parameters that might be used to determine how the state changes and bits correspond to the specific indices of the state that is getting changed. In the case of a quantum circuit, bits would be the qubit labels, state would be the current state vector of the system and symbols could correspond to a list of angles which parametrise some rotational gates in the circuit. Calling a hierarchical motif i.e. my_motif(), executes these functions in order, the state gets changed and passed around until all operations are finished, then the state is returned at the end. For example, if for whatever reason you have a list of letters and want to concatenate all other letters to the first element, you could do:

from hierarqcal import Qpivot, Qinit, Qunitary

def concat(bits, symbols=None, state=None):
    state[bits[0]] += state[bits[1]]
    return state

first_8_letters = ["a", "b", "c", "d", "e", "f", "g", "h"]
give_0_more_letters = Qinit(8, state=first_8_letters) \
                    + Qpivot("1*", mapping=Qunitary(concat, 0, 2))
give_0_more_letters()
# output
['abcdefgh', 'b', 'c', 'd', 'e', 'f', 'g', 'h']

Note that the "algorithm" above is independent of list size, for larger lists only Qinit is changed accordingly (this just sets initial conditions) the abstract structure of the algorithm is captured in what follows after it, i.e. the Qpivot.Plotting the compute graph might help to see what's going on:

from hierarqcal import plot_circuit
plot_circuit(give_0_more_letters)

Here we are "pivoting" on the first bit, as was specified with the string "1*" in the Qpivot primitive. Within this pivot pattern 1*, the * character is shorthand for "fill the rest with zeroes". Alternatively, we could have provided the explicit pivot pattern "10000000". Similarly, the "!" character is used as shorthand for "fill the rest with ones". Each index in the string corresponds to each bit in order (i.e. pivot_str[0] -> bits[0]). Each 1 in the string indicates a pivot on its corresponding bit. Each 0 indicates non-pivots, each of these gets paired with a pivot. Here are some examples of how changing the pivot pattern changes the output:

['a', 'b', 'c', 'd', 'e', 'f', 'g', 'habcdefg'] # *1
['a', 'b', 'c', 'd', 'ea', 'fb', 'gc', 'hd'] # *!
['a', 'b', 'c', 'dacg', 'ebfh', 'f', 'g', 'h'] # *11*

This example showcases the new Qpivot primitive and the abstract circuit plot_function. The Qpivot primitive splits the bits into two sets according to the ones and zeros in the pivot pattern. The elements of the first set, associated with "0", are cycled through to pivot on the second set, associated with "1". The digraph below shows this motif from another perspective:

Building your own quantum simulator for qubits, qutrits, qudits and so on, is then made easy since any python function can be provided to a motif. There's multiple ways to achieve this, you can write functions that corresponds to gate operations and keep track of a tensor product that represents that state of the system. Another way would be to view the circuit as a tensor network and perform the correct tensor contractions. We've provided some functionality to facilitate this approach, for example below we show how to quickly see what a cycle of hadamards (one hadamard applied to each qubit) does to the |0...0> state.

import numpy as np
from hierarqcal import get_tensor_as_f, Qcycle, Qinit

n = 3
H_m = (1 / np.sqrt(2)) * np.array([[1, 1], [1, -1]])
H = Qunitary(get_tensor_as_f(H_m), 0, 1)

tensors = [np.array([1, 0], dtype=np.complex256)] * n
hierq = Qinit(n, tensors=tensors) + Qcycle(mapping=H)

print(hierq().flatten())
# Output
# [0.35355339+0.j 0.35355339+0.j 0.35355339+0.j 0.35355339+0.j
#  0.35355339+0.j 0.35355339+0.j 0.35355339+0.j 0.35355339+0.j]

The variable n can be increased to see the effect on more qubits (the use of Qcycle stays the same because it is independent of the number of qubits). The get_tensor_as_f helper function takes in a matrix and turns it into that generic function form. In the backend, tensor contraction is performed to compute the final state vector.

There is more, such as the rework of Qmask and its new relative Qunmask but for that I'll refer you to the core functionality tutorial. Be sure to check it and the other tutorials out!

Future Directions

Currently, we're working on extending the tensor network contraction functionality to include more general tensor networks, and to allow control over the contraction order. So far this representation has been useful in generating ansatzes for VQE, so there will be a focus on adding features to facilitate this. There is also work being done on symbolic manipulation of expressions with the aid of sympy. These expressions are represented as trees, and manipulating them corresponds to traversing parts of the tree and applying operations to its terms. With hierarqcal, it is convenient to specify bulk operations to specific parts of this tree. For example, applying commutation relations to a subset of fermionic/bosonic operators in a Hamiltonian of some quantum system. The way in which these operations are applied lend themselves to being captured by patterns similar to those seen in the Qpivot example.

That's it for now!

Expanding our board: Anastasia Gamick and Liz Durst

Mon, 04 Mar 2024 00:00:00 GMT

As the quantum technology ecosystem grows, Unitary Fund’s mission becomes more and more important. I am excited to announce that we are growing our own support with two new additions to our board: Anastasia Gamick and Liz Durst.

Anastasia is Co-founder and Chief Operating Officer at Convergent Research, where she builds and incubates new kinds of transformative research institutions. I have a huge amount of respect for the work that she and Convergent are doing and for the ambition that they have. We are thrilled to have her expertise and support as we grow Unitary Fund. Unitary Fund is in many ways a unique institution in a new field and Anastasia is someone I turn to when we have a one-of-one challenge.

"I'm honored to join Unitary Fund's Board. With experience in nonprofit governance and operations, including scaling nonprofits for greater impact, I look forward to supporting Unitary Fund's mission of an equitable quantum future.” - Anastasia Gamick

Liz built and ran the IBM Quantum and Qiskit ecosystem to the huge open community success that they are today. That community and approach has had the kind of beneficial impact on quantum technology that we strive for at Unitary Fund. She has been a partner of our work at Unitary Fund for several years now and is a global leader in the open quantum ecosystem. We’re excited to learn from her and to have her support as we take our community and ecosystem to the next level.

“I’m excited to continue supporting the Unitary Fund in building the open quantum technology ecosystem. The next several years will be critical for driving better benchmarking transparency, stability, and performance standards as we learn from our diverse global community of quantum computing users.” - Liz Durst

We are glad to have their leadership and guidance as part of the Unitary Fund community as we continue to build a greater platform in open quantum technology.

Liz and Anastasia join Unitary Fund's existing board members Christophe Jurczak, Travis Scholten and Nathan Shammah, to whom I am so grateful for their ongoing work and advocacy.

Adding Qibo as a new supported frontend for Mitiq

Thu, 29 Feb 2024 00:00:00 GMT

In the latest Mitiq release, v0.34.0, support for Qibo has been announced as a newly integrated frontend.

This addition expands Mitiq's list of supported frontends, formerly consisting of Cirq, Qiskit, pyQuil, Braket, and PennyLane, to now include Qibo.

Qibo, the newest frontend supported by Mitiq

Qibo is an end-to-end open source platform for quantum simulation, self-hosted quantum hardware control, calibration and characterization. Some of the key features of Qibo, as higlighted in its GitHub page, include:

Definition of a standard language for the construction and execution of quantum circuits with device agnostic approach to simulation and quantum hardware control based on plug and play backend drivers.
A continuously growing code-base of quantum algorithms applications presented with examples and tutorials.
Efficient simulation backends with GPU, multi-GPU and CPU with multi-threading support.
Simple mechanism for the implementation of new simulation and hardware backend drivers.

Additionally, Qibo is a fully collaborative and open-source project, as anyone can contribute to its development. Qibo is actively utilized on real quantum computers; for example, it serves as the frontend for the recently deployed quantum computer at the Barcelona Supercomputing Center BSC-CNS. More detailed information regarding the features and performance of Qibo can be found in the Qibo white paper [^1].

Adding Qibo to Mitiq

To carry out the contribution and make it possible for Qibo circuits to be used in Mitiq, I've had to define two main functions:

The first one is from_qibo, which takes a Qibo-type circuit and converts it into a Cirq-type circuit, the type of circuit internally used by Mitiq. Converting from a Qibo circuit to a Cirq one is, in principle, quite straightforward by first converting the Qibo-type circuit to QASM, and from QASM defining the Cirq-type circuit. However, there are gates known by both Qibo and QASM that are not defined in Cirq. To deal with these gates, I've had to define an auxiliary function for each of them, where these problematic gates are decomposed into gates that are defined in Cirq. An example of this type of gate is the CRX gate.
The other main function I've had to define is to_qibo. This function performs the opposite action of the previous one, converting a Cirq-type circuit into a Qibo-type circuit.

Contributing to Mitiq has truly been a rewarding journey. It has provided me with a profound understanding of the processes involved in quantum computing development and open-source contribution. I would encorage anyone who has an idea that might improve Mitiq to try and contribute. Before any contribution is made, rigorous testing ensures that every aspect functions seamlessly, so there is no reason to be afraid of messing up. Encountering failures during these tests is not uncommon; in my case some tests failed not only on the first try but also on subsequent attempts. However, these failing tests served as a great opportunity to learn new coding techinques and work alongside the Mitiq team to resolve them. The unwavering support and guidance from the Mitiq team has been instrumental in navigating through these challenges, ensuring that the contribution succedeed.

A quick tutorial on using Qibo alongside Mitiq

Setup: Defining a circuit using Qibo

For simplicity, we will use a single-qubit circuit with ten Pauli X gates that compiles to the identity, defined below.

from qibo import Circuit,gates

c = Circuit(1) 
for _ in range(10): 
    c.add(gates.X(0))
c.add(gates.M(0))

In this example, we will use the probability of obtaining the |0⟩ state as our observable to mitigate, the expectation value of which should evaluate to one in the noiseless setting.

Setup: Defining the executor

We define the executor function in the following code block. In the executor, we create a noise map and apply it to the circuit. Finally we simulate the noisy circuit and obtain the desired observable as output of the executor function. For more detailed information about the noise map features see Qibo noisy simulation.

def executor(circuit, shots = 1000):
    """Returns the expectation value to be mitigated. 
    In this case the expectation value is the probability to get the |0> state. 

    Args:
        circuit: Circuit to run.
        shots: Number of times to execute the circuit to compute the expectation value.
    """
    # Apply noisy map (simulate noisy backend)
    noise_map = {0: list(zip(["X", "Z"], [0.03, 0.03]))}
    noisy_c = circuit.with_pauli_noise(noise_map)
    
    result = noisy_c(nshots=shots)
    result_freq = result.frequencies(binary=True)
    counts_0 = result_freq.get('0')
    if counts_0 is None:
        expectation_value = 0.
    else:
        expectation_value = counts_0 / shots  
    return expectation_value

Applying Zero Noise Extrapolation

We can now test the mitigated version of the circuit against the unmitigated one to ensure it is working as expected.

from mitiq import zne

unmitigated = executor(c) 
print(f"Unmitigated result {unmitigated:.3f}")
mitigated = zne.execute_with_zne(c, executor)
print(f"Mitigated result {mitigated:.3f}")

Output:

Unmitigated result 0.788
Mitigated result 0.967

The mitigated result is noticeably closer to the noiseless result compared to the result without mitigation. You can find a tutorial with more details in the Mitiq documentation.

About the contribution

This contribution to Mitiq is the outcome of my internship at the Barcelona Supercomputing Center, conducted from October 2023 to February 2024, under the guidance of Alba Cervera-Lierta. This intership was part of the master's program in Quantum Science and Technology based in Barcelona.

[^1]: S. Efthymiou, S. Ramos-Calderer, C. Bravo-Prieto, A. Pérez-Salinas, D. Garcı́a-Martı́n, A. Garcia-Saez, J. I. Latorre, S. Carrazza, Qibo: a framework for quantum simulation with hardware acceleration, Quantum Science and Technology 7 (1) (2021) 015018. doi:10.1088/2058-9565/ac39f5, arXiv:2009.01845.

Unitary Fund Q4 2023 Update - UnitaryCON, 2023 QOSS Survey results, new grants and project updates

Thu, 01 Feb 2024 00:00:00 GMT

Dear Unitary Fund community,

We are excited to share our 2023 Q4 quarterly update!

In November in Rome, Italy we wrapped up our first unitaryCON, an invitation-only collaborative workshop for the extended Unitary Fund community. The workshop was an opportunity to share ongoing projects, connect with collaborators and supporters, and work with our community to advance the quantum open-source software ecosystem with the leading contributors from around the world. A huge thank you to our core member Scientifica Venture Capital, whose collaboration and support via Quantum Italia made unitaryCON possible.

In Q4 we also released the results of our second annual Quantum Open Source Survey to help the many diverse stakeholders of quantum technologies get a holistic understanding of the users, tools, needs and strengths of the ecosystem today. As it was the second survey, we were also excited to provide certain comparative metrics to view how things evolved since 2022. The purpose of this survey is to gather a dataset that is inclusive and representative of current and prospective open-source software coders, for and with quantum technologies in order to better serve users of the quantum computing ecosystem. Read the full details in our blog and explore the survey results in depth.

We awarded 4 new grants, ranging from a new library for financial assets, to a new project supporting and building open source hardware design, from a library implementing a genetic approach to quantum compilation, to a new Julia library for quantum optimal control. The full details of the grantees and projects can be found below.

Scientific research using open source tools has continued in Q4, with two new papers uploaded to arXiv. Andrea Mari authored Counting collisions in random circuit sampling for benchmarking quantum computers, 2312.04222, whose core aspects are explained in this blog post. Vincent Russo co-authored Tight bounds for antidistinguishability and circulant sets of pure quantum states, 2311.17047.

Mitiq also had several important updates in Q4. Four new releases were made (v0.30-v0.33), with help from new contributors: Farzad Kianvash and Yash Prabhat. The documentation for the Quantum Subspace Expansion method is now live! Additionally, there are new benchmarking circuits (mitiq.benchmarks.generate_random_clifford_t_circuit) and new calibrator logging for easier discovery of performant quantum error mitigation techniques. Read more in the Mitiq section below!

Thank you all for your continued support of the open-source quantum ecosystem!

Make sure to follow our Discord, X, LinkedIn, and our [email protected]">Community Calendar.

New From Unitary Fund

Aquapointer

With support by Wellcome Leap, as part of the Quantum for Bio Program, we have completed a key milestone in our collaboration with Pasqal and Qubit Pharmaceuticals with the release of aquapointer v0.0.1! Aquapointer is an open source software package applying quantum algorithms to find locations of water molecules in a protein cavity.

v0.0.1 of aquapointer is available on Github and on PyPI. We encourage you to download and test out the package via PIP or download from GitHub. The repo includes a notebook directory with a demo notebook to help you get started.

Please send us your feedback via GitHub issues on the aquapointer repo (preferred) or via email at [email protected].

Qrack

In Q4, Qrack launched an Ubuntu PPA (ppa:wrathfulspatula/vm6502q) with support for every standard architecture in (Canonical) Launchpad, for Ubuntu 18.04, 20.04, and 22.04 LTS versions. You can read more about simulating 54 qubits with Qrack – on a single GPU, in this blog post by Dan Strano.

Mitiq

New Releases: v0.30.0, v0.31.0, v0.32.0, v0.33.0

v0.30.0: This release contains several documentation improvements and some new additions. The classical shadows documentation has been improved (including a tutorial!) by @Min-Li. The Pauli Twirling method is added to the user guide (thanks @Aaron-Robertson and @purva-thakre). There is a new tutorial applying both zero-noise extrapolation (ZNE) and Clifford Data Regression (CDR) to quantum simulation, for the 1D Ising chain, in Cirq, by @farzadkianvash, a new contributor! The documentation has been further improved and unified by @Misty-W and @natestemen. In terms of additions, a new type of benchmark quantum circuits, "rotated" randomized benchmarking (RB) quantum circuits have been added by @Misty-W, for more general benchmarks.
v0.31.0: This release contains several documentation improvements and some new additions. Quantum subspace expansion (QSE) is added to the user guide (thanks @bubakazouba). Thanks to our first time contributors @dubeyPraY for a new tutorial on using PennyLane and Mitiq in calculating the energy landscape of a simple variational circuit and @kozhukalov for adding the PEC noise level and calculated error to the calibration logs. We also removed support for python 3.8.
v0.32.0: The calibrator logs have been revamped for to support result discovery and analysis. The Calibrator.run method now support two options: flat and cartesian to display the experiment results in either a linear fashion, or grid-like. Results here have been truncated for brevity.
v0.33.0: Minor update from 0.32.0 to fix a bug 🐛 in the mitiq.shadows module where an incorrect index was being used.

Metriq

In Q4, Metriq added a “Landscape chart” to show the difference between the current technology-readiness level and useful quantum computing scales, a State-of-the-Art page for key performance metrics curated by the Unitary Fund team, and a major redesign of the presentation of taxonomical “platforms.”

Unitary Fund & Metriq.info are very pleased to announce the formation of a new Open Quantum Benchmark committee!

As our community-led benchmarking platform Metriq continues to grow, we are looking for community members who are interested in a governance role, bringing their knowledge and background to help experts and curious beginners alike better navigate the state of quantum computing benchmarks. Applications to join the committee for a 1-year term are now open through Feb 18.

Join us! Apply today here: https://bit.ly/3Oo6K9Z

Questions? Get in touch on the ⁠metriq channel or at [email protected].

Other Events

In addition to UnitaryCON, you would have found us participating in Q2B Silicon Valley and co-hosting the NYC Quantum Summit. We also hosted 7 Quantum Wednesday events discussing cut edge quantum research, including one guest talk from IBM discussing Machine Learning for Practical Quantum Error Mitigation. Make sure to join us for our upcoming Quantum Wednesday talks at 9:30 am PT / 6:30 pm CET in discord.

February 7: Discussion on Piccolo.jl with Aaron Trowbridge
February 14: Improving Zero-noise Extrapolation for Quantum-gate Error Mitigation using a Noise-aware Folding Method with Nathan Shammah

Interested in presenting a talk at one of Quantum Wednesday events? Sign up here.

Curious about where we’ll be next? Mark your calendars for these events we’ll be at in Q1 2024:

iQuHACK: On February 2-4, 2024 you will find Dan Strano mentoring and speaking at iQuHACK, MIT's annual quantum hackathon. Students from a diverse set of backgrounds will explore improvements and applications of near-term quantum devices.
QHack: Hosted between February 8-22, 2024, you will find Misty Wahl giving a talk! At QHack, participants can upskill their knowledge and fast-track coding skills.
APS March Meeting: The annual meeting of the American Physical Society will take place March 3-8, 2024, in Minneapolis, MN. Misty Wahl will give an invited talk on March 6th in Session M52: Quantum Error Mitigation at Scale.
QuTiP: Hosted on March 25-29, 2024, the QuTiP admin team is organizing the 2024 QuTiP developers workshop, which will be held at RIKEN, Wako, Japan. Dive into talks, hackathons, and laid-back discussion panels all about the QuTiP v5 release and what's on the horizon for QuTiP. This event is aimed at the active QuTiP developers, but if you're eager to be part of the action and contribute to QuTiP's future, drop a line to the local organizers at [email protected] and [email protected].

Updates from UF Microgrant Projects

We are excited about several new updates to microgrant projects.

Labscipt-qc: The developers of labscipt-qc, a software framework for cold atom research groups to make their experiments more accessible, have published version 0.3.0 of the package sqooler. A template for remote access should now make it possible for experimental research groups that control their systems with lab script to have fairly secure remote access. This new project, awarded a microgrant in Q3, would now greatly benefit from interested beta users.

Quantify: The recent updates to Quantify, a data acquisition framework for quantum computing and solid-state physics experiments, focus on improving quantum circuit design and experimentation. The software now supports more complex quantum circuits, including nested ones, and has significantly reduced compilation times by 30-75%. Users can save and reload complete experimental setups using JSON files, enhancing the ease of experiment replication. Additionally, new operations such as the Gaussian pulse and complex-valued square pulse have been introduced. New schedules are available for two-qubit CZ tune-up and CPMG decoupling experiments, extending qubit coherence time. Finally, Quanitfy introduced a new debugging tool that allows the user to the export the entire experiment with detailed debug information.

Qworld: Qworld, a microgrant award winner from Q2 2023, has continued their work to bring quantum computing to a global audience. They hosted their first virtual class "QClass23/24,” which started in September of 2023 with over 1000 students from all around the world. During the Autumn semester they offered (i) QCourse101-1: Fundamentals of Quantum Computing & Programming, (ii) Self-study module “Quantum Key Distribution”, and (iii) QJam2024 “Making Quantum Games”. The Autumn semester will conclude at the end of January 2024. Additionally, Qworld conducted their first Quantum Software Development course with Classiq "QCourse551-1". 30 geographically diverse students completed 13 projects under the mentorship of Classiq researchers.

Two new QCousins joined the QWorld family: QUAE & QSouthAfrica.

Qlasskit: The first stable release v0.1.7 of the qlasskit library has been released on github and pypi. Read more about qlasskit.

New Grants:

To Michael Hellman to further develop Qasper, a library that includes both common quantum representations of standard financial notation and classical assets.
To Aaron Trowbridge & Aditya Bhardwaj to further develop Piccolo.jl, a quantum optimal control (QOC) method called Pade Integrator Collocation (PICO) that is a direct trajectory optimization method that treats both the states and controls of the system as decision variables.
To Max Shirokawa Aalto to further develop OpenQuantum, a blueprint for a magneto-optical trap that open-sources high-quality CAD files, electronic schematics, control firmware and assembly instructions along with teaching materials to create a much-needed educational platform for quantum science and engineering.
To Viet Tan Nguyen, Hai Tuan Vu, Viet Tan Nguyen, Le Bin Ho & Tran Lan to further develop GA-QAS: a genetic approach to quantum compilation, to solve the manual finding of a suitable trainable unitary by automatically finding a near-optimal ansatz given the target quantum objective functions.

Unitary Fund Announces Brian Goldsmith as Newest Ambassador

Mon, 22 Jan 2024 00:00:00 GMT

We're excited to host in this interview Brian Goldsmith, who is awarded a UF Ambassadorship for his active role in the Unitary Fund community.

Meet Brian

Q: How did you learn about Unitary Fund?

Brian: During a series of workshops put on by Zapata Computing, error mitigation was explored in which we used Mitiq for zero-noise extrapolation (ZNE). Later when looking to engage in an open source project, I looked closer into Mitiq and found the Unitary Fund.

Q: Tell the community a bit about yourself. For example, how you got into quantum and your current interests.

Brian: After 14 years as a software support engineer at IBM, I went back to school to get a Master's in Computer Science from Vanderbilt University. During my studies, I took an Introduction to Quantum Computing course which sparked my interest in the field. I have enjoyed each aspect of quantum computing that I have been exposed to including error mitigation, simulation, and resource estimation. Outside of quantum computing, I am married to a high school science teacher and we have two boys and a dog.

Q: What's the first thing you did within the Unitary Fund community? What's the thing you're most proud of that you've been involved in?

Brian: After lurking for some time, I opened and worked on a pull request (PR) related to installing Mitiq with z-shell. Since the PR consisted of adding quotes to a single line of documentation, it was a gentle introduction to contributing. I am quite proud of recent work done simplifying the expectation_estimation_shadow function in the classical shadows protocol in Mitiq. The protocol is based on the idea of shadow tomography, which is a technique for reconstructing a quantum state from a small number of measurements. Though there were some complications, I enjoyed the challenge and appreciated the assistance and guidance from the team (including Andrea, Min, and Nate.)

Q: What do you like most about Unitary Fund? What suggestions do you have for folks to get involved?

Brian: While the work by the Unitary Fund is fantastic, it is the people and community that make it unique. From Nate, Misty, and Dan hanging out and talking with me at QCE23, to Andrea reviewing PRs and providing valuable suggestions, to Farrokh taking time to go over his Wednesday talk in more detail, to Nathan asking my opinion on the community calls, it is the people of Unitary Fund that make it special.

About the Ambassadors Program

The Unitary Fund Quantum Ambassadors program recognizes individuals that are directly addressing the challenges of the growing quantum community. Unitary Fund Quantum Ambassadors bring together their peers to learn new skills, develop open source tools, and build the open quantum community all over the world.

Anyone is eligible to become an ambassador, and winners are nominated by the Unitary Fund team on a rolling basis. We expect that ambassadors exemplify Unitary Fund values and conduct themselves with respect whenever they engage with others within and outside the open quantum community.

Join our newsletter to get updates about this blog in your inbox, follow us on Linkedin or X, or join our Discord to hang out with the open quantum community.

Looking back at unitaryCON

Tue, 02 Jan 2024 00:00:00 GMT

Looking back at unitaryCON

Last November in Rome, Italy we wrapped up our first unitaryCON, an invitation-only collaborative workshop for the extended Unitary Fund community. The workshop was an opportunity to share ongoing projects, connect with collaborators and supporters, and work with our community to advance the quantum open-source software ecosystem with the leading contributors from around the world. A huge thank you to our core member Scientifica Venture Capital, whose collaboration and support made unitaryCON possible.

The unitaryCON program included talks from Oak Ridge National Lab, Amazon Braket, Qiskit, Xanadu, Pasqal, Perimeter Institute, Stellenbosch University and more. Many of the invited talk slides can be found here. Microgrant award winners spoke about their on-going project work and had a chance to hold more in-depth project office hours to meet to get feedback and ideas. Spencer Churchill, a Unitary Fund micrograntee, debuted the first printed version of Quantum Tales. Another micrograntee winner, Roger Luo, gave a great talk on the Julia programming language in the quantum community.

In addition to technical talks, the unitaryCON program included a panel discussion on the quantum ecosystem and feedback sessions for Mitiq and Metriq. Time was also dedicated to pitches, which was a lively and interactive session of free-flowing ideas to improve the open-course quantum computing ecosystem.

Attendees had the chance to get an early preview of Unitary Fund’s 2023 Quantum Open Source Survey before the results were released publicly. This preview allowed for a robust discussion on the current state of the ecosystem, identifying gaps and areas for improvement as well as where the quantum computing ecosystem is excelling.

On a scale of 1-10, participants gave unitaryCON an average rating of 9.3, finding the experience to be valuable and informative. The majority of participants found the interactions with other participants to be their favorite part of unitaryCON, in addition to helping them understand trends and roadmaps in open source quantum computing. Below are quotes from feedback received about the event:

“These days were really inspiring to continue contributing to open source initiatives!”

“I loved hearing about the different open source projects and ideas people have around abstracted quantum languages. I had a wonderful experience and wish we had more time to work together.”

“I have a much clearer sense of the state of the quantum open source ecosystem as a whole, as well as near term developments and goals for the community.”

We can’t wait to see everyone again at the next unitaryCON! If you want to get involved or support our future events, please email [email protected].

Qlasskit - A bridge between Python and quantum algorithms

Wed, 13 Dec 2023 00:00:00 GMT

Traditionally, creating quantum circuits requires specialized knowledge in quantum programming. This requirement holds true when encoding a classical algorithm inside a quantum circuit, for instance, for an oracle or a black-box component of a quantum algorithm. This often becomes a time wasting job, since we almost always already have a classical implementation in a traditional high level language.

Qlasskit, an open-source Python library developed with the support of a Unitary Fund microgrant, addresses this challenge head-on by allowing direct translation of standard Python code into invertible quantum circuits without any modification to the original code. Furthermore, qlasskit implements some well-known quantum algorithms and offers a comprehensive interface for implementing new ones.

Qlasskit adopts a distinctive method where it constructs a single boolean expression for each output qubit of the entire function, rather than translating individual operations into quantum circuits and then combining them. This approach enables advanced optimization by leveraging boolean algebraic properties.

For instance, let assume we have the following function:

from qlasskit import qlassf, Qint2, Qint4
from qiskit import QuantumCircuit

@qlassf
def f_comp(b: bool, n: Qint2) -> Qint2:
      for i in range(3):
            n += (1 if b else 2)
      return n

The first things you can notice in this code are:

the qlassf decorators, indicating that the function will be translated to a quantum circuit.
special bit-sized types Qint4, and Qint2. These are required as qubits are a precious resource, and we want to use as few as possible.
it all reads as normal Python code.

If we decompose the algorithm in 3 separate additions and we compile them separately, we obtain the following circuit:

@qlassf
def f1(b: bool, n: Qint2) -> Qint2:
    return n + (1 if b else 2)

qc = QuantumCircuit(f_comp.num_qubits * 2 - 1)

for i in range(3):
    qc.append(f1.gate(), [0] + list(range(1 + i * 2, 5 + i * 2)))

While if we compile the whole function to a quantum circuit using qlasskit, we obtain the following quantum circuit:

As we can see from the circuit drawings, qlasskit approach needs half the number of qubits and half the number of gates.

An use-case: pre-image attack on a cryptographic function

To further illustrate qlasskit's capabilities, we will demonstrate its use in performing a pre-image attack on a cryptographic hash function using Grover's search algorithm, obtaining a quadratic speedup compared to classical approaches. The beauty of qlasskit lies in its simplicity – you can write the entire software without needing to understand any concept of quantum computing.

A pre-image attack, in cryptography, targets a hash function h(m) with the aim to discover an original message m that corresponds to a specific hash value. On a traditional computer, to perform this attack without any hints, we must run h(m) with every possible input (N=2**n).

Thanks to the Grover search algorithm, we are able to find a pre-image with only pi/2 * sqrt(N) iterations, obtaining the quadratic speedup I mentioned before.

We write a toy hash function hash_simp which operates on messages composed of two 4 bit values and uses bitwise xor to create an 8 bit hash value.

from qlasskit import qlassf, Qint4, Qint8, Qlist

@qlassf
def hash_simp(m: Qlist[Qint4, 2]) -> Qint8:
    hv = 0
    for i in m:
        hv = ((hv << 4) ^ (hv >> 1) ^ i) & 0xff

    return hv

To see the resulting quantum circuit we can export and draw in qiskit:

hash_simp.export('qiskit').draw('mpl')

And this is the resulting circuit, produced by the qlasskit internal compiler:

Thanks to the fact that qlasskit functions are standard Python functions, we can call the original_f to perform some kind of analysis and test on the hash function. Since the input space is tiny (it is a toy hash function), we can check if the hash function is uniform (if it maps equally to the output space).

from collections import Counter

d = Counter(hex(hash_simp.original_f((x, y))) for x in range(2**4) for y in range(2**4))

print('Hash function output space:', len(d))

We got that hash_simp is following an uniform distribution.

Now we use our quantum function as an oracle for a Grover search, in order to find which input maps to the value 0xca.

from qlasskit.algorithms import Grover

q_algo = Grover(hash_simp, Qint8(0xca))

Then we use our preferred framework and simulator for sampling the result; this is an example using qiskit with aer_simulator.

from qiskit import Aer, QuantumCircuit, transpile
from qiskit.visualization import plot_histogram

qc = q_algo.export('qiskit')
qc.measure_all()
simulator = Aer.get_backend("aer_simulator")
circ = transpile(qc, simulator)
result = simulator.run(circ).result()
counts = result.get_counts(circ)

counts_readable = q_algo.decode_counts(counts, discard_lower=5)
plot_histogram(counts_readable)

And this is the result of the simulation, where we can see that the pre-image that leads to h(x) = 0xca is the list [12,12].

Using QlassF.original_f we can double check the result without invoking a quantum simulator; calling it with the list [12,12] must result in the hash value 0xca.

print(hex(hash_simp.original_f((12,12))))

A special thanks to the Unitary Fund that funded this idea. If you have any questions or comments, feel free to reach out to me on twitter dagide, linkedin Davide Gessa and medium @dakk.

Useful Links:

A new simple benchmark for quantum computers

Fri, 08 Dec 2023 00:00:00 GMT

Run and measure a random quantum circuit many times and count the number of repeated outcomes. That's it.

This blog post is an introduction to the recent arXiv preprint[^1]: Counting collisions in random circuit sampling for benchmarking quantum computers, arXiv:2312.04222. In this paper we introduce a new method to measure the performance of current quantum computers that may be quite useful for monitoring and tracking the ongoing progress in quantum technologies.

Random circuit sampling

Random circuit sampling is a particular quantum computing protocol in which a given random quantum circuit C is applied to n qubits initialized in the |0⟩ state and a final measurement is performed in the computational basis (if you are not familiar with a quantum circuit, you can imagine it as the simplest program for a quantum computer, similar to a list of instructions). The result is a bitstring which looks quite random. For example, for 16 qubits, a possible result could be something like this:

0101100100010010.

</div>

If we repeat the procedure N times, we'll get N measurement shots and therefore N classical bitstrings. Something like:

b<sub>1</sub> = 0110110110001100,

b<sub>2</sub> = 1100010100111110,

...

b<sub>N</sub> = 1101001101010001.

</div>

The measured bitstrings look quite random, as if they were sampled from the uniform distribution over all the D=2<sup>n</sup> possible outcomes. However, this is actually not true! In fact, if the quantum circuit is sufficiently random, i.e., if it prepares some pure state |ψ⟩ which does not have any preferred orientation in the Hilbert space (Haar-random), the probability distribution of the possible measurement outcomes is not uniform. In practice, for a typical random state |ψ⟩, some bitstrings are slightly more likely than other bitstrings. This is a statistical property of random quantum states[^2].

This effect is true for a "good" quantum computer having a sufficiently low level of noise. The more the computer is noisy, the more the distribution of the measurement outcomes becomes uniform. In the high-noise limit, the outcomes become uniformly distributed and the quantum computer behaves as a trivial classical random number generator. This fact can be turned into rigorous operational benchmarks such as the cross-entropy benchmark [^2] [^3] or the quantum volume[^4]. Unfortunately, these methods require the classical computation of the ideal noiseless probabilities of all the possible bitstrings or, at least, of all the measured samples. In other words, it is possible to quantitatively distinguish quantum samples from uniform samples, but you have to pay a classical computing cost which scales exponentially in n.

A quantum-only approach based on collisions

Is it possible to distinguish quantum samples from trivial uniform samples without using any classical computing? In our recent work[^1], we show that counting the number of repeated bitstrings (also called collisions in statistics) can be a very straightforward way of doing it. Indeed, it turns out that samples obtained from a pure random state tend to have more collisions with respect to samples drawn from the uniform distribution.

Basically, all we need to do to verify that a quantum computer is behaving in a "quantum" way is running a random quantum circuit many times and checking if the number of re-sampled bitstrings is larger than the expected number of collisions for the uniform distribution.

For example, when measuring a random state of n=16 qubits with N=10<sup>4</sup> shots, the expected number of collisions is ≃1324. For the uniform distribution over 2<sup>16</sup> bitstrings instead, the expected number of collisions in N samples is ≃726. The below figure, extracted from the paper, is a numerical simulation of the number of observed collisions for different values of N.

This phenomenon is not very surprising: if for a pure random state some bitstrings are more likely than others, it means that they tend to get re-sampled more frequently. This effect can be easily turned into a quantitative benchmark for the performance of a quantum computer, via a simple function of the number of collisions observed when sampling a random circuit. Specifically, in our work we introduce two quantitative benchmarks: the collision anomaly and the quantum collision volume. Moreover we also propose a method to cross-validate two different quantum computers by counting the number of cross-collisions in their measurement outcomes. More technical details can be found in the paper[^1].

Sampling cost and the birthday paradox

The new bechmarks based on the number of collisions have basically zero classical computing cost. Unfortunately, they have a large quantum sampling cost. In fact, in order to observe some collision events, one needs to collect at least N= 𝓞(2<sup>n/2</sup>)= 𝓞(√D) samples. This is an exponential scaling with respect to the number of qubits. In other words, the exponential classical cost, typical of the cross-entropy and quantum volume benchmarks, is now transformed into an exponential sampling cost.

We note however that, thanks to the square root scaling in D, the number 2<sup>n/2</sup> =√D is much smaller than the dimension of the Hilbert space (D=2<sup>n</sup>). For the uniform distribution, such square root reduction of the sampling cost is also known as the birthday paradox: even if there are 365 days in a year, a small group of just 23 random people is enough to have a 50% probability of a shared birthday. It is interesting to note that the same kind of "apparent" paradox is what makes our collision-based benchmarks practically feasible for near-term quantum computers, despite the asymptotic exponential scaling in n.

[^1]: Andrea Mari, Counting collisions in random circuit sampling for benchmarking quantum computers, arXiv preprint (2023) arXiv:2312.04222.

[^2]: Sergio Boixo, Sergei V Isakov, Vadim N Smelyanskiy, Ryan Babbush, Nan Ding, Zhang Jiang, Michael J Bremner, John M Martinis, and Hartmut Neven. Characterizing quantum supremacy in near-term devices. Nature Physics, 14(6):595–600, (2018), arXiv:1608.00263.

[^3]: Scott Aaronson and Sam Gunn. On the classical hardness of spoofing linear cross-entropy benchmarking, arXiv preprint (2019), arXiv:1910.12085.

[^4]: Andrew W Cross, Lev S Bishop, Sarah Sheldon, Paul D Nation, and Jay M Gambetta. Validating quantum computers using randomized model circuits. Physical Review A, 100(3):032328, (2019), arXiv:1811.12926.

The State of Quantum Open Source Software 2023: Survey Results

Mon, 04 Dec 2023 00:00:00 GMT

We are excited to share the results for the 2023 Quantum Open Source Survey organized by Unitary Fund! A giant thanks to our supporting and core members, as well as our board and advisors for their guidance and feedback. Thank you as well to our outstanding open source community for their input, ideas and passion!

We hope this snapshot of our field can help the many diverse stakeholders of quantum technologies to get a holistic understanding of the users, tools, needs and strengths of the ecosystem today. As the second annual survey we are also excited to provide certain comparative metrics to view how things may have evolved since last year.

You can find the results at this link.

Demographics [link]

Demographics: As in 2022, the majority of quantum OSS users are researchers (53.8%), however, sizable communities identify themselves as developers (39%), students (27.5%), hobbyists (16%) and educators (12%). This data speaks for the balanced heterogeneity of interests and sub-communities among quantum OSS users and developers. Almost 45% of respondents do not have a background in quantum research.

Most have selected their main reason for involvement as advancing quantum science and knowledge. The respondents are also mainly associated with an academic institution (43%), enterprise organization (32%) or a startup (25%).

The most represented country continues to be the United States (25%), with the UK making the largest leap, up to 13% from 9% last year. India (10%), Canada (7), and Germany (4.5%) round out the top five. EU countries sum up roughly 18. In all, 56 countries are represented in the survey, speaking to the continued spread of access and enthusiasm for the field.

The majority of respondents either work full time (53.6%) or part time (9.2%) in the quantum industry, and among those, about 27% work fully remote, about 36% employ a hybrid format, and only 15% are fully in-person. Fully remote work featured the only large change (7%) YoY, with the others holding at similar percentages to last year.

Experience [link]

About 91% of respondents use quantum software, of which about 47%are solely users, and 53% are either OSS project contributors, maintainers, or owners.

Cloud services [link]

The most popular service remainsIBM Quantum (70% of respondents are current users), though this represents a 10% decline over last year. IBM is followed by AWS Braket (19% are current users, and 19% would be interested in trying it out in the next 12 months). Quantinuum took the largest leap forward in current users into third place, moving from 8% to 17.9%. Xanadu (16.8%) and Google (16%) round out the top five, with Microsoft Azure Quantum (12.3%), qBraid (9.2%) and IonQ (6.6%) also popular. Respondents voiced interest across the board in trying new services within the next 12 months, a possible sign they have yet to find a service that fits their needs. Over the past two years it does not yet seem that there has been an increase in consolidation among the offerings. Ease of use, Performance and Documentation are the most important factors for users in making their decision, a shift from last year where maintenance, documentation and price were the most important.

With regards to Full-stack development platforms, respondents have continued to indicate that that IBM's Qiskit (including Qiskit Aer) is their most popular library (68.8%), though its popularity fell by 10% YoY. This loss looks to be taken mostly by small increases in uses of SDKs outside the top five. This is followed by Xanadu’s PennyLane (29%) and Google's Cirq at (22.8%), with tket rounding out the top 5 at 19.8%, a 4% increase YoY. As last year, there is particular interest in starting to use the AWS Braket SDK within the next 12 months. Joining AWS in libraries with more than 10% of users there is also QuTiP-QIP (an affiliated project of Unitary Fund and the only project of these not directly backed by a startup or corporate), as well as cuQuantum (Nvidia).Other popular libraries include Strawberry Fields, cudaQuantum, Q# (Microsoft) and Dwave's Ocean SDK.Documentation remains the most important factor respondents weigh when choosing an SDK, with Performance listed as the second most important factor.

With regards to tools for applications, Qiskit packages such as qiskit-optimization, qiskit-machine-learningremainamong the most popular, though their lead has lessened over the last year by about 10%., PennyLane's QML repo remains popular, and OpenQASM saw a 4% increase in use over 2022. Other popular projects include qiskit-nature, qiskit-finance, tensorflow-quantum, Unitary Fund's Mitiq for quantum error mitigation, and OpenFermion. There remains widespread interest in exploring other tools in the future, such as torchquantum, bskit, stim for quantum error correction, the PyZX compiler, Covalent, Superstaq and more. For these tools, documentation is well ahead as the most important factor, followed by performance and ease of use.

In terms of main blockers that have caused respondents to not adopt technologies they would otherwise want to use, poor documentation and price remain the most common factors. The largest YoY change came with Tool Does Not Exist as a factor, which fell by 10%.

OSS Development & Research [Link]

With regards to OSS development and research, over 47% of respondents performing research define themselves as algorithm development and 45% as applications developers, with over a third involved in circuit development & optimization, software engineering, or quantum simulation/Physics. A sizable percentage are involved in quantum information theory (26%) as well. Other interests include quantum error mitigation (18%), and error correction (16.2%), both increasing YoY. While 13% or less selected fundamental physics, qubit characterization, and hardware development. Algorithm development remains the highest in terms of most promising area of future research (55.9%), followed by error correction (49.5%), with application development, quantum simulation/physics, hardware development, circuit development and optimization, and error mitigation all ranking above 30%.

The most popular programming language is Python, which like last year remains at 94%. The second most popular framework remains C/C++ at 24%, with Julia, MATLAB and Rust rounding out the top 5. Julia featured the largest YoY growth up 4.6% to 14.6%. Respondents also rated Python as the most promising language, with Rust, C/C++, Julia and Q# following. Notably Python’s lead in this category is definitely smaller than in the current programming language question. Jupyter Notebooks and notebooks in general remain very popular as tools for software development (used by 75.8% of respondents), with 67% of respondents using an integrated development environment (IDE) and 49% using the command line or terminal.

Community [Link]

With respect to the quantum software community, 85% find it very welcoming or somewhat welcoming, and 11% neither welcoming nor unwelcoming or worse. 95% of respondents have a positive view of OSS in the quantum software community, with 75% finding it has a very positive impact and 20% a somewhat positive impact. This overall perception remains relatively constant since 2022.

Project documentation or project websites remain the most sought after sources of answers or information when developing quantum software (84%), with project repos (77%), a close second. Quantum Computing Stack Exchange, Stack Overflow, Slack, Discord, and YouTube, remain popular platforms, while less popular are standard forums (7%) and Reddit (6%). Among the types of resources most helpful for learning or contributing to quantum open source projects, video resources continue to rank highest, though lower this year by 6% (61%), followed very closely by digital education text resources (60%), as well as hackathons (53%), and participative courses, mentorship programs and certificate or degrees (all above 40%).

Community: Diversity & Inclusion

About 43% of respondents are in the 25-34 age range, with 23% of respondents below 25 (but less than1% under 18 years old).

With regards to ethnicity, about a 44% of respondents identifies as White or of European descent, 18% as South Asian, 9.4% as Hispanic or Latino/a/x, 6.8% as East Asian, and as Black or of African descent, and 4% or below as Black or African Descent, Multiracial, Middle Eastern, Other. Notably, 10% prefered not to say. 76% of the respondents identify as a man, 15.4% as a woman, 1.6% as non-binary, genderqueer, or gender non-conforming, 0.8% self describe and 6% prefer not to say.

With respect to educational background, the largest group holds a PhD (34%) or multiple ones (2.6%), 33% have Masters or other non-doctoral post-graduate degree, 23% have a university degree and 4% high school/secondary school degree, other degrees, or prefer not to say.

Open-ended Feedback

We highlight just a few responses giving feedback on the quantum OSS ecosystem below, that emphasize the work needed and requested to support quantum open source software:

“I think the community channels (e.g. discord) and GitHub discussions can be super useful. Especially for the libraries that are not yet so big, it is fantastic how much help you can get directly from the developers.”

“We need strong policies that keep the technology open to every human being, regardless of their ethnicity, belief, country, etc.”

“This is the most inviting and friendly community out there. Folks are extremely helpful and resourceful. People want to improve this field and want to help others to make it happen. Making the resources open source is the best move by researchers in the field. To those wondering, get involved and start contributing.”

“Thank you. Keep doing what you are doing right now. If not for the quantum OSS community, I would not be doing research in quantum right now.”

“We've made progress in growing the community and making it more welcoming, but there is still much work to be done in inclusion and retention of underrepresented groups.”

Acknowledgements

We are excited to repeat the survey in coming years and track the changes and trends in responses and in the field. This is possible thanks to UF Members (IBM Quantum, Scientifica Venture Capital, Agnostiq, AWS, Cisco, DoraHacks, Pasqal, Quandela, Qyber) and other supporters, including the National Science Foundation. Thank you to all that have participated and that will help share these findings.

Simulating 54 qubits with Qrack – on a single GPU

Wed, 25 Oct 2023 00:00:00 GMT

As lead developer of the Qrack project, I recently flew to Bellevue, WA, to present the first formal report ([arXiv:2304.14969]) on comparative benchmarks of quantum computer simulator software, with unitaryfoundation/qrack and unitaryfoundation/pyqrack, to IEEE Quantum Week '23, on behalf of authors on the Qrack and Unitary Fund teams. We were thrilled to get the opportunity to subject Qrack to peer review and criticism, and to introduce the open source project to a wider professional and academic community! Get started with Qrack from the docs here, or dive right into its support for a simple but powerful Python API here.

Qrack was founded 6 years ago by me (now technical staff member of Unitary Fund) and Benn Bollay (CTO of Fusebit) in 2017 with a relatively simple (but surprisingly overlooked) vision: create world's best open-source quantum computer gate model simulator software for the specific use case of running "quantum" workloads (by logical programming paradigm) as quickly and efficiently as possible on any "classical" computer. Released under the "permissive copyleft" LGPL-3.0 license, Qrack has built out support to virtually all major operating systems and processor instruction sets, to ensure that the floor of global, public, "free" access to quantum workload throughput utility is never lower than the Qrack team's best efforts, shared openly.

Before I joined Unitary Fund as a technical staff member, Qrack was awarded a Unitary Fund microgrant, and the software is now affiliated with Unitary Fund. As of the publication date of this blog post, PyQrack has over 685,000 total downloads, with 4-to-5 thousand downloads per week.

"Universally" compatible, and a "team player"

PyQrack is Qrack’s dependency-free Python ctypes wrapper, to expose Qrack shared library binaries directly for just-in-time (JIT) execution via a Python interpreter. (If you prefer the Rust language, the equivalent wrapper is Qook.) Plugins and providers are available for Qiskit, Cirq, and even the Unity video game engine, with plans to continue to expand plugin support to virtually every major quantum open source framework in the global ecosystem, as they arise. Supported platforms include all available Original Electronic Manufacturer combinations of x86_64, x86, ARMv7, and ARM64 instruction sets with Linux, Windows, Mac, iOS, and Android operating systems, as well as WebAssembly (Wasm). If users prefer to offload parts of work to conventional tensor network software, the QrackCircuit class of PyQrack can aggressively locally simplify structured and general quantum circuits, then convert to-and-from Quimb, Tensorcircuit, or (NVIDIA) cuTensorNet representations, as shown in this notebook showcasing the use of Qrack with cuQuantum as a backend.

As easy as quantum gets

Qrack has been praised for its "transparent" design to serve ease-of-use when programmers might know nothing of the specifics of the simulation methods employed and "hybridized" in Qrack: maximum theoretical performance is achieved in many or most cases by simply importing the PyQrack QrackSimulator class and instantiating it with no arguments or configuration beyond a single constructor argument that indicates qubit width of the simulator instance. When a user does this, automatically, Qrack is combining on-the-fly circuit siimplification, CPU, GPU, multi-GPU, stabilizer, and original "state factorization" simulation methods as appropriate to achieve maximum throughput and minimum memory footprint, with virtually no configuration effort by users. Should a user have reason to want Qrack's alternative "quantum binary decision diagram" back end, or to excise any "layer" from the default stack, or to deploy Qrack in true "high performance computing" ("HPC") applications, powerful configuration features are simple to control with a minimal set of QrackSimulator constructor arguments and environment variables, as shown in this PyQrack Jupyter notebook.

Performance

Performance details have been subjected to peer review, in the IEEE Quantum Week '23 conference proceedings, in a report titled "Exact and approximate simulation of large quantum circuits on a single GPU". As the title indicates, this report focuses on benchmarks with a single GPU, specifically an NVIDIA RTX 3080 Laptop GPU for exact benchmarks and an NVIDIA A100 for approximate benchmarks, though proof-of-concept has already been demonstrated with scaling Qrack to at least 8 GPUs simultaneously.

For "ideal" (vs. "approximate") simulation benchmarks, the report focuses on comparing a set of popular GPU-accelerated quantum computer simulators, as well as a classical discrete Fourier transform solver, on the task of the "quantum" (or "discrete") Fourier transform (QFT). Qrack exhibits unique special-case performance on permutation basis eigenstates as inputs to the QFT, carrying them out in linear complexity, while we forward a Greenberger–Horne–Zeilinger state (GHZ) input as likely Qrack's hardest case. Comparing GHZ input across all candidates, Qrack leads over all candidates except the classical DFT solver for speed at low qubit widths, while it leads over all candidates except cuQuantum-based Qiskit Aer by less than a factor of 2 at high qubit widths.

It is worth remembering, as regards any trade-off for this very modest performance advantage of (cuStateVec-based) "cusvaer" in a relatively specific case, that the PyQrack wheels for most operating systems transfer from PyPi in about 4 to 5 MB and have no dependencies at all (besides packaging, technically made part of Python language standard by PEP); cusvaer is currently only available packaged in the cuQuantum Appliance (Docker container) with GBs of dependencies.

We show that Qrack can simulate a quantum circuit with 54 qubits on a single GPU with fidelities close to the state-of-the-art of quantum supremacy experiments. As reported in the article, while an attainable average fidelity of about ~4% on 7 depth layers of a 54-qubit "nearest-neighbor" coupler circuit might be modest, this is with less than 80 GB of total memory footprint, on a single GPU. Employing a virtualization framework to connect nodes, it should already be possible to scale Qrack to an arbitrarily high number of GPUs, increasing this fidelity figure as a function of available (GPU) memory. We are eager to explore such true "HPC" regimes. It is worth noting how far the Qrack capabilities have come, as the project started as an unfunded hobbyist project. We do not take for granted that any user has ready access and financial resources to run on 64 GPUs for over a dozen hours, for example, potentially costing tens or hundreds of thousands of US dollars, but this is exactly why the Qrack developers have focused their efforts for years on hardware available to virtually any "consumer," including first-class support for integrated graphics accelerators and CPU-only systems as low-cost alternatives to GPUs.

At a high level, Qrack can make many of the same kinds of general performance claims as conventional tensor network approaches: for special cases of low-entanglement or "near-Clifford" simulation, it can often support hundreds or thousands of qubits in a single quantum circuit. Since Qrack robustly supports interoperability with major conventional tensor network software, it's also incredibly easy to combine techniques in Qrack with use of those more popular back ends. However, we think many users would be surprised at how much equivalent functionality, compared to tensor networks, is already covered by Qrack, whether through relatively "novel" simulation techniques. You can learn more about Qrack's simulation methods in the recent report, to appear in the Proceedings of IEEE QCE 2023.

Check out the repositories on the Unitary Fund GitHub organization, star and share, and get Qrackin’! You rock!

Unitary Fund Q3 2023 Update: NSF and Wellcome Leap awards, 2023 QOSS Survey, open hardware, and 7 new grants

Mon, 16 Oct 2023 00:00:00 GMT

Dear Unitary Fund community,

We are excited to share our 2023 Q3 quarterly update!

The Quantum Open Source Software Survey 2023 is ongoing! Please take a couple of minutes to take it here.

We have some exciting news on the research side: Unitary Fund has been awarded a grant by the National Science Foundation to grow the open-source ecosystem for Mitiq and enable a global community to adopt quantum error mitigation out of the box. Unitary Fund has been selected to participate in the Quantum for Bio program by the Wellcome Leap to explore, with quantum startups PASQAL and Qubit Pharmaceuticals, biology-relevant applications with quantum computing. We have multiple open positions.

Further on the research side, UF led the drafting of the first review on open hardware in quantum technology, with global collaborators. The UF tech staff attended multiple events, including IEEE Quantum Week in Bellevue, WA, the NYC Quantum Summit, and the GE Climate, Sustainability and Quantum workshop in Albany, NY.

We launched our new Unitary Fund website: We have a new blog post on how Mitiq can be used to lower the bounds of quantum error correction (QEC), using Stim as a frontend.

We awarded 7 new grants this quarter to fund new projects and enrich existing projects of useful tooling for the quantum open source ecosystem, ranging from open APIs to provide cloud access to atom-based QPUs to expanding existing projects like Toqito.

Mitiq continues to grow, with new quantum error mitigation techniques supported: quantum subspace expansion, Pauli Twirling, and classical shadows -- and more tutorials.

Join the IonQ Office Hours on the UF Discord, every Wednesday at 4pm ET. On the UF Discord you can join many quantum OSS community calls: Mitiq, Metriq, QIR Alliance, QICK, OpenQAOA, Covalent.

Thank you all for your continued support of the open-source quantum ecosystem!

Make sure to follow our Discord, Twitter, LinkedIn, and our [email protected]">Community Calendar.

New from UF

Mitiq
- New Releases: v0.28.0, v.0.29, v.0.30
  - In v.0.28.0: Quantum Subspace Expansion is now available in Mitiq! PEC Calibration contains some improvements and we added robust classical shadow estimation.
  - In v.0.29.0: Update Pauli Twirling, Classical Shadows, Stim + Mitiq tutorial to merge error correction with error mitigation.
  - In v.0.30.0: New documentation for the classical shadows technique, Pauli Twirling, and a tutorial applying both zero-noise extrapolation (ZNE) and Clifford Data Regression (CDR) to quantum simulation, for the 1D Ising chain, in Cirq. We add functions for "rotated" randomized benchmarking (RB) quantum circuits, for more general benchmarks.
- Talks:
  - UF tech staff was at IEEE Quantum Week in Bellevue, Washington, Sept 17-22! We gave a Mitiq tutorial, research talks and participated in an open science workshop.
Metriq
- New site frontend, with tidier charts of major metrics like quantum volume visible already on the homepage. We performed a redefinition of Platforms, including major Providers and Devices.
UF Research
- [2309.17233] Open Hardware in Quantum Technology
New Grants
- QlassKit: To Davide Gessa to develop QlassKit, a Python library that allows developers to write classical algorithms in Python and translate them into unitary operators for use in quantum circuits.
- labscript-qc: To Fred Jendrzejewski to further develop labscipt-qc, a software framework for cold atom research groups to make their experiments more accessible.
- Toqito: To Purva Thakre to grow Toqito, toward a mature open-source project and utilize it for further research in unextendible product bases.
- BGLS: To Alex Shapiro and Ryan LaRose to further develop bgls, an implementation of the gate-by-gate sampling algorithm of Bravyi, Gosset and Liu for classically simulating quantum circuit measurement.
- Qiskit-Qulacs: To Gopal Ramesh Dahale to further develop Qiskit-Qulacs, a plugin using Qulacs as a backend for Qiskit circuits.
- LambdaQ: To Radu Marginean to further develop lambdaQ, a functional programming language for quantum computing based on Haskell.
- mdopt: To Aleksandr Berezutskii to develop mdopt, an efficient tensor-network decoder.

News from UF Projects

Read Ali's inspiring blog post on his Summer internship at UF working on Metriq and the UF website!
A great blog post on the UF site by microgrant awardee Harshit Gupta on his project improving the Qiskit timeline transpile debugger.
Quantify is continuously updated. Changelog of Quantify scheduler is visible here. Some operational highlights include a new website (www.quantify-os.org and docs update. Now GitLab Pages are generated and hosted (quantify-core, quantify-scheduler)].
QWorld launched a new two-semester long global program called QClass23/24 in September 2023. It includes introductory and intermediate level QCourses & self-study modules, activities with industrial partners, a quantum jam, and several online talks by experts. It has received 2K+ applications from 103 countries, and 1350+ of them have joined the QClass23/24 Discord server. The website: https://qworld.net/qclass23-24/.

The 2023 QOSS Survey is here!

Wed, 27 Sep 2023 00:00:00 GMT

The 2023 Quantum Open Source Software (QOSS) Survey is here!

[Update: Survey is now closed]

This annual survey is a state of the community & industry snapshot, from the bottom up. It is a chance for anyone who codes, or wants to code, for and with quantum technologies, to share their voice in the development of our field. The survey covers information on demographics, experience, community, research, tech stacks and more.

If you are a user or developer of software for any kind of quantum technology, we kindly encourage you to take this ~10 minute survey. Please note the survey will be available through October 27, 2023. Thank you for your help in building a better quantum computing ecosystem!

Are you ready to take the survey? Click here to get started!

A very large and heartfelt thank you to all the Unitary Fund community members, advisors, and partners who continue to help us provide this survey as a resource, including work in designing, testing and providing general feedback.

Fill out the QOSS Survey here

Timeline Debugger for the Qiskit Transpiler

Wed, 20 Sep 2023 00:00:00 GMT

Qiskit transpiler is an important tool used to map any arbitrary quantum circuit into a physically runnable one, compatible with the properties of its target quantum backend. This process, called transpilation, includes expanding a circuit to the backend's qubit count, breaking down higher level quantum operations in terms of the supported basis set, and routing qubits according to the chip connectivity and optimization of the final circuit. While Qiskit's transpiler has built-in logging and callback mechanisms to help users understand about transpilation, most users don’t know about these methods, nor have sufficient knowledge about using them. This is where the project comes with an aim to provide an insight into the qiskit transpiler.

Qiskit Trebugger (transpiler-debugger) is a tool which provides a visual representation of the transpilation process. It was developed as an interactive tool with multiple views catering to the needs of different users. Available as a python package on PyPI, it can be used as a jupyter widget or a lightweight CLI tool to understand how a circuit goes through the qiskit transpiler. The following image shows a preview of the CLI view -

The debugger is divided into three main components -

1. Overview of the Transpilation Process There are two panels which highlight crucial information about the transpilation process. Some basic information such as the quantum backend, optimization level and version information is specified as the first level of information. The second level contains the total number of passes executed, and a comparison of the different statistics for the original and final circuits.

2. Details of the Transpilation Process The transpilation process in qiskit consists of multiple passes. Each of these passes either changes the circuit (Transformation) or the property set (Analysis). Moreover, the circuit properties such as its depth, width, operation count and type of gates change after each pass is executed. Both of the jupyter and CLI views provide a consolidated dashboard for this evolution.

3. Pass Level Details On a more granular level, users can also see a detailed view of each pass. This consists of the current circuit diagram, property set, logs emitted, documentation and the time of execution for the pass.

The pip install qiskit-trebugger command can be used to install the package in your python environment.

Views

- Jupyter

The debugger was originally built using the ipywidgets package for the jupyter notebook environment. Whenever our package is used to debug a quantum circuit, an interactive widget is rendered consisting of the transpilation overview and the transpiler pass information. Some special features supported by this view are circuit diffs and property set hierarchy. Using our circuit diff feature, users can see what exactly changed between the circuits of two transpiler passes whereas an expandable property set is provided for users to look at its internals.

Running the jupyter view


from qiskit.providers.fake_provider import FakeCasablanca
from qiskit.circuit.random import random_circuit
from qiskit_trebugger import Debugger
import warnings

warnings.simplefilter('ignore')
debugger = Debugger(view_type = "jupyter")
backend = FakeCasablanca()
circuit = random_circuit(num_qubits = 4, depth = 5 , seed = 44)

# replace qiskit's transpile call
debugger.debug(circuit, optimization_level = 2, backend = backend)

- CLI

The command line view for the debugger is a more recent development. Built using the ncurses and tabulate packages, it is a lightweight alternative to the jupyter view. It has minimal overhead for loading and can be used to debug circuits in a terminal environment. The CLI view is also interactive, with action keys for navigation and a status bar. Users can index into the pass list to see the details of each pass and toggle through different views. Most features of the jupyter view are supported in the CLI view as well. Note that this view can only be rendered in the terminal and not in a jupyter notebook.

Running the cli view


from qiskit.providers.fake_provider import FakeCasablanca
from qiskit.circuit.random import random_circuit
from qiskit_trebugger import Debugger
import warnings

warnings.simplefilter('ignore')
debugger = Debugger(view_type = "cli")
backend = FakeCasablanca()
circuit = random_circuit(num_qubits = 4, depth = 5 , seed = 44)

# replace qiskit's transpile call
debugger.debug(circuit, optimization_level = 2, backend = backend)

With that said, more information about the internals of the tool can be found in the following links -

The development of the project is under way with more upcoming features in both the CLI and the jupyter view. These include enhancing the logs and property set of the transpiler passes in the CLI view and introducing new elements in the widget such as the backend coupling maps, timeline drawer for qiskit pulse schedule and routing maps for the qubits.

A very big thanks goes out to Unitary Fund for supporting this project and giving us the opportunity to work on it. Moreover, we would also like to thank the Qiskit team for their support in the Qiskit Advocate Mentorship Program, and our mentors Kevin Krsulich and Matthew Treinish for their constant guidance and feedback.

Upgrading error mitigation to the fault tolerant regime with Mitiq (and a Stim tutorial)

Thu, 14 Sep 2023 00:00:00 GMT

In Mitiq v0.29.0 we added a tutorial demonstrating a method of combining quantum error mitigation (QEM) and quantum error correction (QEC). While QEM and QEC are typically thought of as separate approaches to dealing with errors in quantum computations, recently it has been shown that techniques such as zero noise extrapolation (ZNE) and probabilistic error cancellation can also benefit applications in fault-tolerant quantum computing [^1][^2][^3]. In this example, ZNE is applied with noise scaling by global unitary folding on logical randomized benchmarking (RB) circuits, and the use of Mitiq with the Stim stabilizer simulator as the backend is introduced.

About Mitiq

Mitiq is the leading quantum error mitigation compiler, with over 100k downloads. Because quantum computers have high error rates, compiling for error robustness is critical for useful applications [4]. Mitiq is an open source project developed by the Unitary Fund technical team, along with a community of over 50 contributors worldwide. For more information, see the Mitiq documentation.

About Stim

Stim is a quantum stabilizer circuit simulation package, specialized for the simulation of quantum error correction (QEC) circuits. It can be used as a Python package, a command line tool, or a C++ library. More information can be found on the Stim project page.

More information about the Mitiq and Stim workflow can be found in the tutorial.

A Mitiq + Stim tutorial for applying error mitigation on logical circuits

The idea for a tutorial with Stim was first inspired by a comment regarding Ref. [3] from a community member on SciRate (also an open access scientific platform!), suggesting the use of deeper circuits on the numerical example demonstrating a novel noise scaling technique proposed in the paper. The team agreed with the suggestion and quickly determined that a performant stabilizer simulator was necessary to run the deeper circuit simulations. Of the stabilizer simulators tested, Stim was the one that could execute all necessary simulations within the time constraints of the project. Furthermore, we were able to demonstrate ZNE effectively mitigating errors on the deeper logical RB circuits as well, strengthening the case for ZNE on logical circuits.

Quantum community impact

Ultimately, the research code for simulating logical circuits on the Stim backend and applying ZNE with Mitiq was reused and streamlined into a tutorial in the gallery of examples in the Mitiq documentation. In addition to the positive results, the project became an encouraging case study for open science and the use of constructive community feedback in refining scientific work. It also motivated a new connection between two powerful open quantum software tools, Mitiq and Stim, paving the way for future demonstrations combining QEM and QEC to minimize the effect of errors in quantum computations.

[^1]: Christophe Piveteau, David Sutter, Sergey Bravyi, Jay M. Gambetta, and Kristan Temme. Error mitigation for universal gates on encoded qubits. Phys. Rev. Lett., 127:200505, (2021). URL: https://link.aps.org/doi/10.1103/PhysRevLett.127.200505, doi:10.1103/PhysRevLett.127.200505.

[^2]: Yasunari Suzuki, Suguru Endo, Keisuke Fujii, and Yuuki Tokunaga. Quantum error mitigation as a universal error reduction technique: applications from the nisq to the fault-tolerant quantum computing eras. PRX Quantum, 3:010345, (2022). URL: https://link.aps.org/doi/10.1103/PRXQuantum.3.010345, doi:10.1103/PRXQuantum.3.010345.

[^3]: Misty A. Wahl, Andrea Mari, Nathan Shammah, William J. Zeng, and Gokul Subramanian Ravi. Zero noise extrapolation on logical qubits by scaling the error correction code distance. (2023). arXiv:2304.14985.

[^4]: Will Zeng and Nathan Shammah, Making quantum error mitigation practical, 2023. URL: https://unitary.foundation/posts/2023_qem/

Unitary Fund is awarded a NSF grant to grow the quantum open source ecosystem

Mon, 21 Aug 2023 00:00:00 GMT

We are thrilled to announce that Unitary Fund has been awarded a $1.5M grant by the National Science Foundation (NSF) to grow the open-source ecosystem around the Mitiq project.

This is a milestone for Unitary Fund, further establishing its impact as a new kind of research organization. We are grateful to the wide community of tech staff members, contributors, members, supporters, partners and users. We are excited for the growth of the Mitiq ecosystem.

About Mitiq

Mitiq is a compiler that makes programs more robust to errors in quantum computers. Because quantum computers have high error rates, compiling for error robustness is critical for useful applications. Mitiq is the leading quantum error mitigation compiler and has recently hit 100k downloads and is developed by a community of over 50 contributors worldwide.

About the Mitiq Open Source Ecosystem (OSE)

The Mitiq OSE will attract and support a large community of users and contributors that extends beyond today's core developers and initial user base. This expansion will include product management, infrastructure engineering, community management, governance, and user success. Specifically, this project will focus on user-led development of digital interfaces and resources, accelerated advancement in quantum error mitigation, compatibility with emerging hardware, dependencies and related software packages, establishment of standards and benchmarks, and dissemination of results and software integration.

By building the Mitiq OSE, we will increase open access to software based techniques that reduce noise sensitivities of programs and protocols, accelerating the adoption of cutting edge research by quantum computing users and improving quantum technology for all users across a significant new industry.

Dr. Nathan Shammah (PI) and Dr. Will Zeng (Co-PI) will coordinate the project for Unitary Fund. The grant is awarded within the innovative framework of the Pathways for Open Source Ecosystem (POSE) launched last year by NSF Directorate for Technology, Innovation and Partnerships (TIP).

From the award announcement

[This grant will allow Unitary Fund] to develop a sustainable OSE and infrastructure around the Python library Mitiq, a cross-platform compiler that enables programs to be more robust to the errors present in Noisy Intermediate-Scale Quantum (NISQ) hardware devices. The growth of an OSE around Mitiq will improve the performance of currently available quantum computers for users everywhere, and will accelerate the development of use cases for this critical technology across academia, government, and industry. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Meet the UF interns - Ali Gedawi

Fri, 18 Aug 2023 00:00:00 GMT

About Me

I am one of the 2023 Summer interns at Unitary Fund. I am a rising Senior at New York institute of Technology, studying Physics. Besides school, I am a research assistant with my professor, researching non-Markovian open quantum dynamics in squeezed environments. I was introduced to quantum computing through Qubit by Qubit Early immersion program, and I hope to continue it. After all, I just spent my Summer working on it.

Internship

Getting into this, I didn't really know what to expect. First, I am working remote, second, I am way out of my field, and third, what is GitHub? Even though I had daunting questions (and a near existential crisis) I had truly a great team behind me, and to support me. Dan, Vincent, Ben, Misty, Nate, Will, Nathan, and literally everyone I spoke to, either offered me help, advice, or generally good tips. When we started, we were tasked with getting the Metriq Client to run (I highly recommend for anyone else to do this as well, such a satisfying feeling once it all starts to work). Once that was completed, we focused on some Metriq submissions, and worked on some issues for the client or the website.

Then came the reveal of the new Unitary Fund website which looks superb (I didn't do any of the aesthetics, but I am more than happy to take the credit). We started to find and work on various issues and converted the HTML files to markdown. Srila (the other intern - go read her blog post) and I worked through those (becoming pros at GitHub in the process) and worked through the issues that we found. During the midst of all this, Nathan and Dan proposed for us to be a speaker on a Quantum Wednesday on the Unitary Fund Discord, so happily, we took on the challenge. Afterwards, we worked on the Metriq client, and tackled as many issues as we could.

Quantum Wednesday

Truth to be told, I was kind of hoping that my computer fried and I wouldn't have to do it. But I am so glad that I went through with it. Let me break down what Quantum Wednesday is. Find a research paper (or topic) that is interesting enough to do a 45 minute talk about. Simple enough right? So naturally I did my presentation on 4 research papers. Due to the nature of the other work I mentioned, I had one week to present a mock presentation, and two weeks until the actual quantum Wednesday. I have never googled so many terms in my life. These papers could've been written in another language the way I barely understood it the first, the second or the third time reading it. It was difficult, I said I was introduced to quantum computing, not that I was an expert in it. I spent roughly 25 hours reading, researching, and putting up my mock presentation in a week.

When the mock presentation day came, I can confidently say that it was the worst presentation of my life. I'll spare you the details, but it could be severely improved. On top of that, a final paper came out in relation to the other 4, and of course, I naturally took that on. With one week to present all 5 papers, I gave it my all, trying to correct my errors, reading the last paper, and trying to make a good presentation. When the actual day came, I can confidently say that it was good, actually really good. It roughly took me 25 minutes to present it all in a clear and concise way, and I spent the next 20 minutes professionally answering questions. Ultimately, I am so happy that I did it (a learning curve indeed, but a challenge I am happy that I took). You can find the necessary papers and slides here!

Regardless of the time, effort, sweat and everything in between, this is truly the gem of my time at Unitary Fund.

Closing Note

Unitary Fund is an open source quantum technology system that works to benefits the most people, and a place that I will cherish (and brag about) forever. I am genuinely, and sincerely happy I was able to have my internship here. The team is filled with such amazing people (They are truly the building blocks of Unitary Fund) that I had the utmost pleasure of working with. Working here was nothing short of a great learning experience, promoting me to be a better worker, researcher, and of course, better learner. Thank you Unitary Fund!

Unitary Fund Q2 2023 Update: unitaryHACK stats, UF France, 7 new grants and projects updates

Fri, 28 Jul 2023 00:00:00 GMT

Dear Unitary Fund community,

We are excited to share our 2023 Q2 quarterly update!

unitaryHACK 2023 arrived and wrapped up, thanks all for joining. This was Unitary Fund's largest event to date: over 750 participants from 80+ countries, solving 99 bounties with awards of $11k across 33 participating projects. Thanks to all participants, maintainers and sponsors (AWS, Classiq and UF members) for making this happen!

The community feedback for unitaryHACK has been amazing, with 44% of hackers said they will continue with the projects they hacked on during this event, and an additional 41% of hackers saying they would like to continue making contributions if they have time. An estimated 60% of hackers were making their first contributions to QOSS for this event. Please read more about winners, stats and project information about the event in this blog post here co-authored by unitaryHACK director Nate Stemen.

We're also excited to announce the inauguration of Unitary Fund France, Unitary Fund's first European office. We've also welcomed Min, Srila and Ali as Summer Interns.

We awarded 7 new grants this quarter to fund new projects and enrich existing projects of useful tooling for the quantum open source ecosystem, ranging from TorchQuantum for quantum machine learning, to stac, for quantum error correction, and also some follow up grants to QWorld and HieraQcal.

Last quarter was a very busy time for scientific research with open-source tools by the Unitary Fund technical staff and our collaborators, with three more papers uploaded on arXiv: Misty Wahl (UF tech staff) and co-authors at UF and the University of Chicago upgraded quantum error mitigation with zero-noise extrapolation to quantum error correction regime and fault tolerance in this paper.

Dan Strano (UF tech staff) and core contributors of the Qrack project, with collaborators from UF, tuned up the capabilities of what is possible to simulate with a single GPU in terms of NISQ devices, in this paper. Both papers got accepted as proceedings in IEEE Quantum Week! In this paper, researchers at Los Alamos National Lab and Unitary Fund tech staff showed how quantum error mitigation can be used to increase with Mitiq the effective quantum volume of four IBM Quantum devices. Finally, we've written a perspective on how to make quantum error mitigation practical sooner in this blog post.

Mitiq got a new calibration feature added, which you can read more in this blog post. You can use some pre-built routines to pick the best quantum error mitigation technique and parameters for your problem.

Thank you all for your continued support of the open-source quantum ecosystem!

Make sure to follow our Discord, Twitter, LinkedIn, and our [email protected]">Community Calendar.

New from UF

Mitiq New Releases:

v0.25.0: Bug fixing for digital dynamical decoupling (DDD), extended documentation for identity insertion as a noise scaling technique, new results from testing DDD on IBMQ hardware, a new function to generate W-state circuits for benchmarks, and a finalized calibration API.
v.0.26: Highlights from this release include functions for applying Pauli Twirling of CNOT and CZ gates, support for noise scaling by circuit layer in ZNE, functions to generate Quantum Phase Estimation benchmarking circuits, and a new example composing two Mitiq techniques: REM and ZNE. Special thanks to UF Ambassadors Purva Thakre and Aaron Robertson for their contributions to this release!
v.0.27: Highlights from this release include adding new benchmark quantum circuits: Mirror Quantum Volume Circuits (@purva-thakre) and adding PEC as technique supported by calibration (@Misty-W). After approval of the related RFC on quantum subspace expansion technique, the first utils have been added (@bubakazouba). Other improvements include a new tutorial on quantum many body scars (@DHuybrechts); issues solved during unitaryHACK such as improvement to the cost estimation for Calibrator (@YuNariai), Qiskit Upgrade and Deprecation Warnings (@andre-a-alves), and a new function to register user defined Mitiq converters (@Aaron-Robertson).

Metriq Hackathon contributors to Metriq added LaTeX parsing and completely revamped the Python Metriq client examples! We continued to build a pipeline for running independent hardware benchmarks and automatically inserting them into Metriq, which incidentally led Metriq developers to fix a critical bug in the open-source Qiskit Quantinuum provider module. Many new and historical results were added to the Metriq database, including results from our benchmark pipeline.

Podcast: Infinite Loops -- Will Zeng -- "Towards a Quantum Future" link

Talks: our staff gave talks around the world including the following:

NISQAH Conference -- Nathan Shammah "Digital error mitigation techniques and software tools" video, June 4th, 2023
SQUID -- Nate Stemen "Quantum Error Mitigation with Mitiq and quantum software with Unitary Fund" video, June 3rd, 2023
QIQT Conference -- Nathan Shammah "Recent Techniques in Quantum Error Mitigation", May 29th, 2023
Silicon Valley Quantum Computing Meetup -- Misty Wahl "Unitary Fund: Building the Open Quantum Technology Ecosystem ", May 13th, 2023 -
MSc course in AI Univ of Milan -- Nathan Shammah "Quantum Error Mitigation: Lecture + Hands-on Lab", May 2nd, 2023
PyData Seattle -- Nate Stemen "Growing the open source quantum ecosystem"video, April 28th, 2023

UF Research

2304.14969 Exact and approximate simulation of large quantum circuits on a single GPU
2304.14985 Zero noise extrapolation on logical qubits by scaling the error correction code distance
2306.15863 Increasing the Measured Effective Quantum Volume with Zero Noise Extrapolation

New Grants

To Jiaqi Leng and Yuxiang Peng to develop QHDOPT, a quantum algorithm for continuous optimization through the Quantum Hamiltonian Descent (QHD) framework.
To Son Pham and Tien Nguyen to develop QuTritium, a Python package that helps automate the calibration process and extends the functionality of the Qiskit package in a qutrit system.
To Hanrui Wang to further develop TorchQuantum, a Quantum classical simulation framework based on PyTorch.
To Abdullah Khalid to further develop stac, a circuit library optimized for building fault-tolerant circuits for stabilizer codes.
To Abuzer Yakaryilmaz to foster QWorld's activites, including QScience Days and QCourses.
To Miriam Büttner, Sunayana Dutta, Paolo Molignini, Rui Lin, Camille Lévêque, Axel Lode to organize a software developer workshop for the numerical simulation of ultracold quantum many-body systems (MCTDH-X).
To Eduardo Maschio to develop H-Hat, a quantum programming language made for developers.

News from UF Projects

Bra-Ket-Vue: A few years ago, we gave a UF microgrant for Bra-Ket-Vue, which later became a part of the Virtual Lab by Quantum Flytrap. The lab was recently nominated, among four other projects, including OpenAI and NASA websites, to the Webby Awards (Best Science Websites category). The Webby Awards, hailed as the 'OSCARS® of the Internet' by the New York Times, are one of the most prestigious honors in the digital industry*.* The Webby nomination page.] Articles: 1, 2, Crafted With Code

ALF: ALF has a new version, 2.5, which offers better handling of errors; improved, automatic compilation of HDF5; safer restart function. More details here.

QWorld: QWorld Quantum Science Days 2023 (QSD2023) was held virtually on May 29-31 bringing researchers across the quantum domain and the world together to network and present their work. We hosted 9 invited speakers who shared their perspectives on quantum simulation, quantum and society, circuit design and beyond. Aligning with QWorld's mission to educate globally and build an open quantum ecosystem, we premiered the thematic session "Building an Open Quantum Ecosystem" with speakers from diverse global and national initiatives to democratize quantum education and resources. Moreover, we selected a diverse and stimulating program of 31 contributed talks over three days. QSD2023 was sponsored by Unitary Fund and Classiq, and supported by the Latvian Quantum Initiative. QGermany joined the QCousins network as the 26th one.

Qrack: The Qrack developers and Unitary Fund wrote the first report on the design of Qrack and its comparative benchmarks, publishing the report on arXiv and ultimately being accepted into IEEE Quantum Week proceedings for 2023. In the meantime, Qrack has begun to experiment with and release "hybrid stabilizer" techniques that can exactly and approximately simulate near-Clifford circuits. These near-Clifford techniques can even be used for circuit compilation, as opposed to only for simulation.

Coming up this Quarter

More Quantum Wednesdays!

Jul 26th, Srila Palanikumar, "A review of Google Quantum's supremacy results"
Aug 2nd, Ali Gedawi, "IBM recent quantum error mitigation results and related classical simulations"
A full list of past talks with slides can be found in this repo.

A new community call is hosted on the UF Discord, by the QICK (Quantum Instrumentation Kit) project on Fridays at 1pm PT. You're welcome to join it!

UF tech staff will be at IEEE Quantum Week in Bellevue, Washington, Sept 17-22! We'll give a Mitiq tutorial, research talks and participate in an open science workshop.

Wrapping up unitaryHACK 2023!

Fri, 07 Jul 2023 00:00:00 GMT

Thanks to all that took part in unitaryHACK 2023; Unitary Fund's distributed hackathon supporting existing projects in the quantum open source ecosystem.

Whether you were a onlooker, maintainer, bounty hacker, or community member: Thank you, it was a blast, and Unitary Fund's largest event to date 💛🌴.

Winners & Stats

Over 700 participants joined unitaryHACK 2023 from over 80 countries (!!) with a strong representation of India (30%) and the USA (18%). Of these, 72 hackers claimed 99 bounties, with more than $11k awarded.

[A considerable bump in participation from 2022 that saw about 400 participants, 63 hacks and 27 hackers.]

Gregory Varghese, aka WingCode completed 10 bounties, with Davide Gessa, aka dakk following up with 9 bounties. A full leaderboard of hacks is available here. In the kick-off and wrap-up party on Unitary Fund's Discord, over 70 enthusiasts joined the celebrations.

This year 33 projects were featured, with the help of 45 maintainers!

Amazon Braket SDK, Bloqade, BQSKit, Covalent, Dora Factory Quantum Experiments, Error Correction Zoo, Graphix, HierarQcal, KQCircuits, lambeq, Metriq, Mitiq, OpenQAOA, pauliopt, PennyLane, Perceval, Pulser, PyClifford, PyQ, qBraid-SDK, QECFT book, Qiskit, Qiskit Aer, Qiskit Braket Provider, qrack, QuNetSim, QuTiP, scqubits, Symmer, Toqito, TorchQuantum, Yao, ZX Live.

These projects span a variety of languages such as Python, Julia, Rust, C++, and Jupyter Notebooks. Project topics span from open hardware and diagnostics (KQCircuits, scqubits) to measurement based quantum computing (Graphix), from quantum error correction (Error Correction Zoo, QECFT book) to compilers (BQSKit, Mitiq), to quantum machine learning (HierarQcal, TorchQuantum, PennyLane, lambeq), from efficient quantum circuit simulators (qrack, Symmer, PyClifford, pauliopt) to analog quantum computing simulators (Bloqade, Pulser) to full-stack SDKs (Qiskit, Amazon Braket SDK, Yao), from projects orchestration and APIs (Covalent, Qiskit Braket Provider) to quantum information and nonlocal games (Toqito), from quantum network simulations (QuNetSim) to open quantum systems (QuTiP).

Of the hackers, 70% thought the challenges were just the right difficulty, with the remaining 30% saying they were too hard. 44% of hackers said they will continue to contribute to the projects they hacked on during this event, and an additional 41% of hackers said they would like to continue making contributions if they have time. An estimated 60% of hackers were making their first contributions to QOSS for this event, with many of them contributing to open source for the first time! Congratulations to all for making such awesome contributions, it's really been wonderful to see!

Thanks so much to all the unitaryHACK supporters: AWS, Classiq, and the Unitary Fund members -- Core Members: IBM Quantum and Scientifica; Supporting Members: Agnostiq, AWS, Cisco, DoraHacks, Pasqal, Quandela, Qyber. Thank you all! 🙏Hope to see you next year, or even sooner on our community discord.

unitaryHACK 2023: The Unitary Fund hackathon supporting quantum open source projects returns!

Fri, 26 May 2023 00:00:00 GMT

Unitary Fund is happy to announce the third edition of unitaryHACK, which will run from May 26th to June 13th, 2023.

<div align="center"> <img src="https://res.cloudinary.com/dcz4ywuer/image/upload/v1690842150/tvf5ssrooxe25xxziua4.gif" style="width: 70%; height: auto;" /> </div>

unitaryHACK differs from the rest of the hackathon-style events in the quantum computing space because hackers support existing quantum computing projects. In addition hackers get paid for their work while building professional skills such as working on open source projects, and contributing to create a more functional, and featured, quantum computing stack. We want this event to show folks what amazing projects are out there, and help maintainers find new ways and contributors to continue to grow their projects. Event logistics are detailed in our hacker guide, and rules for contributing are available as well. In order to collect your winings, you'll need to be signed up! SIGN UP HERE!

We have more than 33 participating projects and over 100 bounties! You can find the full list here, which includes:

unitaryHACK is made possible by the maintainers volunteering time to review pull requests and engage with the community on our Discord server.

unitaryHACK is supported by generous donations: from AWS and Classiq; from Unitary Fund members - IBM and Scientifica, as core members - and Agnostiq, AWS, Cisco, DoraHacks, Pasqal, Quandela, and Qyber, as supporting members.

Making quantum error mitigation practical

Wed, 17 May 2023 00:00:00 GMT

Useful applications of quantum computers require significant reductions in logical error rates.[^1][^2][^3][^4][^5][^6] One direction to achieve this is to implement quantum error correcting codes. Another direction, complementing quantum error correction, are new techniques for quantum error mitigation.[^7][^8][^9][^10][^11][^12][^13][^14][^15][^16][^17] These are algorithmic methods that are designed to be less experimentally demanding than full quantum error correction. However, this benefit comes at the cost of being less general and more heuristic.

Challenges in quantum error mitigation

There are several key challenges in making error mitigation practical.

Reducing error mitigation overhead. For example, in some techniques, the number of samples $N$ required to approximate the expectation value output from an ideal quantum computer to within an error $\delta$ scales[^18] as $N \propto \gamma^2/\delta^2$, where $\gamma$ is a constant that becomes larger as the quantum program becomes larger and the quantum computer becomes noisier. The $\gamma$ values of approximately 1.02 have been measured in IBM processors.[^19] This exponential dependence emphasizes how important it is to improve performance of different error mitigating techniques and to study their fundamental limits.[^20]

Calibrating optimal techniques. While there are a growing number of options available, this means the programmer must choose what techniques to use and with what parameters. Making this choice well depends on the hardware target and on having a good model of the noise. Further, there is a tradeoff between spending valuable quantum computer time further calibrating the error migitation vs. exploiting the model that is currently available. Additionally, while there have been shown benefits to composing error mitigating techniques---such as[^13] where generalizing PEC and ZNE produces a more robust method---there are open research questions about how best to do this composition. These calibration and composition choices need to be made scalable so that they apply to larger QPUs whose output cannot be simulated and to problems where we cannot train on a previously known answer. Finally, several error mitigating techniques require lower level access to control electronics that is not always available from vendors. More abstract techniques and the integration of error mitigation at lower levels of the stack are needed to improve performance.

Error mitigation and fault-tolerance. How can error mitigation be applied to accelerate the deployment of error correcting codes? For example, Pauli twirling can convert coherent errors into stochastic noise[^21] that could improve the performance of error correction. Further, error mitigation can be extended into the fault-tolerant regime where it can reduce overheads[^22] and, in some examples, improve the number of logical operations that can be applied by a factor of 1000X.[^23]

Opportunities for quantum error mitigation

These challenges are opportunities to both improve the performance of today's quantum computers and also accelerate roadmaps across hardware modalities, including quantum sensors and networks. If properly seized, then error mitigation can provide a smooth ramp up towards quantum advantage,[^24] making it easier for the quantum technology industry to cross the chasm to valuable applications. We describe three key categories of opportunity:

There is an opportunity to use open source software, such as the cross platform error-mitigating compiler Mitiq,[^25] to study and automate the calibrations needed for optimal error mitigation. Open source error mitigation implementations are accretive, allowing researchers and programmers to take advantage of the state of the art without needing to implement everything from scratch themselves. The community using this software can study and fine tune these techniques across hardware platforms and upstream their learning.
Integrating these error mitigating techniques with hardware design offers an opportunity for hardware-software co-design. Here, error mitigating techniques can be considered in both NISQ and fault-tolerant quantum computer architectures. One could, for example, tailor the noise channels towards ones that are easy for mitigating techniques to calibrate and counter.
Research at the intersection of error mitigation and error correction. As error correction becomes more practical, it is likely that there are new error mitigating techniques that can be discovered that integrate well with error correction.

Assessment and Timeline

Progress on error mitigation can be assessed using benchmarks of performance such as effective quantum volume,[^23] improved performance of application level benchmarks, or improvements in logical gate fidelity or coherence. It is important that the assessed performance takes into account the cost and time of classical post- and pre- computations used in the error mitigation. Ideally these assessments of mitigation performance will occur in the supremacy regime where it is non-trivial (or impossible) to classically simulate the results directly. A final assessment for software tools, such as error mitigating compilers, is their usage by the community with metrics like downloads, GitHub stars, citations, etc.

Now is a good time to focus on these error mitigation challenges since (1) we have a stable pool of techniques that are ready to be reduced to practice and (2) we have a need from applications and fault-tolerant design to reduce error rates as quickly as possible. Success on these challenges can meaningfully affect the timeline to useful quantum computing across the whole field.

[^1]: Alexander M Dalzell, et al. End-to-end resource analysis for quantum interior point methods and portfolio optimization. arXiv preprint arXiv:2211.12489, 2022.

[^2]: Michael Kühn, et al. Accuracy and resource estimations for quantum chemistry on a near-term quantum computer. J. Chem. Theor. Comp., 15(9):4764– 4780, 2019.

[^3]: Shouvanik Chakrabarti, et al. A threshold for quantum advantage in derivative pricing. Quantum, 5:463, 2021.

[^4]: Andrew J Daley, et al. Practical quantum advantage in quantum simulation. Nature, 607(7920):667–676, 2022.

[^5]: Michael E Beverland, et al. Assessing requirements to scale to practical quantum advantage. arXiv preprint arXiv:2211.07629, 2022.

[^6]: Craig Gidney and Martin Ekerå. How to factor 2048 bit rsa integers in 8 hours using 20 million noisy qubits. Quantum, 5:433, 2021.

[^7]: Suguru Endo, et al. Hybrid quantum-classical algorithms and quantum error mitigation. J. Phys. Soc. Jap., 90(3):032001, 2021.

[^8]: Zhenyu Cai, et al. Quantum error mitigation. arXiv preprint arXiv:2210.00921, 2022.

[^9]: Chao Song, et al. Quantum computation with universal error mitigation on a superconducting quantum processor. Science advances, 5(9):eaaw5686, 2019.

[^10]: Christophe Vuillot. Is error detection helpful on IBM 5Q chips? arXiv preprint arXiv:1705.08957, 2017.

[^11]: Abhinav Kandala, et al. Error mitigation extends the computational reach of a noisy quantum processor. Nature, 567(7749):491–495, 2019.

[^12]: Tudor Giurgica-Tiron, et al. Digital zero noise extrapolation for quantum error mitigation. In Int. Conf. Quant. Comp. Eng., pages 306–316. IEEE, 2020.

[^13]: Andrea Mari, et al. Extending quantum probabilistic error cancellation by noise scaling. Physical Review A, 104(5):052607, 2021.

[^14]: Google AI Quantum et al. Hartree-Fock on a superconducting qubit quantum computer. Science, 369(6507):1084–1089, 2020.

[^15]: Benjamin McDonough, et al. Automated quantum error mitigation based on probabilistic error reduction. arXiv preprint arXiv:2210.08611, 2022.

[^16]: Shuaining Zhang, et al. Error-mitigated quantum gates exceeding physical fidelities in a trapped-ion system. Nature Commun., 11(1):1–8, 2020.

[^17]: Vincent Russo, et al. Testing platform-independent quantum error mitigation on noisy quantum computers. arXiv preprint arXiv:2210.07194, 2022.

[^18]: Ryuji Takagi. Optimal resource cost for error mitigation. Physical Review Research, 3(3):033178, 2021.

[^19]: IBMResearch. With fault tolerance the ultimate goal, error mitigation is the path that gets quantum computing to usefulness, 2021.

[^20]: Ryuji Takagi, et al. Fundamental limits of quantum error mitigation. npj Quantum Information, 8(1):114, 2022.

[^21]: Akel Hashim, et al. Randomized compiling for scalable quantum computing on a noisy superconducting quantum processor. Phys. Rev. X, 11:041039, Nov 2021.

[^22]: Matteo Lostaglio and Alessandro Ciani. Error mitigation and quantum-assisted simulation in the error corrected regime. Phys. Rev. Lett., 127(20):200506, 2021.

[^23]: Yasunari Suzuki, et al. Quantum error mitigation as a universal error reduction technique: Applications from the NISQ to the fault-tolerant quantum computing eras. PRX Quantum, 3(1):010345, 2022.

[^24]: Ryan LaRose, et al. Mitiq: A software package for error mitigation on noisy quantum computers. Quantum, 6:774, 2022.

[^25]: Ryan LaRose, et al. Error mitigation increases the effective quantum volume of quantum computers. arXiv preprint arXiv:2203.05489, 2022.

Unitary Fund to open first European office in Tours (France) in collaboration with Da Vinci Labs

Tue, 02 May 2023 00:00:00 GMT

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Unitary Fund, a non-profit organization supporting the quantum technology ecosystem, will open its first European office in Tours, France. Da Vinci Labs, a deeptech accelerator for quantum, AI, and synthetic biology, acted as an incubator for Unitary Fund’s European operations, providing incorporation and fundraising advisory services.

There is rapid growth across quantum technology, and the vision for a robust quantum industry increasingly resonates with scientists, engineers, investors, and corporations. Still, there are challenges to overcome as researchers need to develop error correction, scalable hardware technologies, useful algorithms with provable advantages, ways to benchmark and project the performance of heuristic algorithms, and more.

Some of these challenges are well addressed by academic and industry players. However, others are public goods that help everyone but that don't stand alone as businesses. These are the open development tools, standards, benchmarks, interfaces, educational and training materials, skill sharing networks, open source communities, mentorship networks and more that form the soil from which a rich industry and ecosystem can grow.

Unitary Fund’s mission is to foster the quantum ecosystem with a microgrant program funding explorers worldwide to work on quantum projects like open-source quantum software, educational materials and workshops, a new quantum sensor prototype, and much more. Unitary Fund has supported open-source projects like Pulser (a framework for composing, simulating and executing pulse sequences for neutral-atom quantum devices), mitiq (a compiler for error-mitigated quantum programming) and metriq (a platform for sharing quantum technology benchmarks).

Xavier Aubry, Da Vinci Labs Founder and Managing Director, commented: “Unitary Fund has the ambition to be the equivalent of the Linux Foundation for the quantum industry. As the ecosystem matures, open-source software platforms will be key to supporting use cases and applications of quantum technology. That’s why we decided to collaborate with Unitary Fund and help set up their European office in France.”

Nathan Shammah, CTO of Unitary Fund, comments: “The French quantum ecosystem has risen to global prominence, thanks to the excellence of its research and its network supporting deeptech transfer, with players like Quantonation. A first generation of quantum hardware spin-offs like Pasqal and Quandela, are committed to developing open source infrastructure. We’re looking forward to further collaboration with the Da Vinci Labs through a shared long-term vision of a sustainable and open quantum ecosystem in Europe.”

Will Zeng, Unitary Fund Founder and President, remarks: “We have supported innovative teams through our microgrants and hackathons for years now. With the help of Da Vinci Labs, we are excited to expand our commitment to developing the quantum ecosystem in France and in Europe.”

About Unitary Fund

Unitary Fund is a 501(c)(3) non-profit whose mission is to create a quantum technology ecosystem that benefits people around the world. We believe that expanding the pool of people working on quantum technologies is a way to ensure that the benefits of these tools are widely, swiftly, and equitably distributed. We primarily use two major programs to pursue this mission. Through Unitary Labs, we work on in-house projects that help the ecosystem as a whole. Through our microgrant program, we fund an inclusive community of explorers across the world to work on quantum technologies.

https://unitary.foundation/

About Da Vinci Labs

Da Vinci Labs is a research and incubation structure inspired by Leonardo da Vinci. Its interdisciplinary and humanistic approach aims to respond competitively to the ecological challenges of tomorrow and to bring out the future champions of deeptech, in particular in the field of quantum technologies, artificial intelligence and synthetic biology. To do this, Da Vinci Labs participates in European collaborative research projects and builds a technological infrastructure in Touraine, which will be made available to researchers and entrepreneurs ready to tackle our major societal challenges.

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Calibrating Error Mitigation with Mitiq

Mon, 17 Apr 2023 00:00:00 GMT

What is error mitigation calibration?

Error mitigation improves the performance of quantum programs, but with a myriad of mitigation strategies, and workflows to choose from, it can often be hard to know where to start. Further, once a strategy is chosen, there can be many parameters that need to be tuned to optimize its performance. For these reasons we have begun building a module within mitiq to help find the best mitigation strategy and parameters for your backend. This makes it simpler to take advantage of the best error mitigating techniques.

The new functionality is accessed by instantiating a Calibrator object as follows.

<!-- ```py from mitiq import Calibrator

cal = Calibrator(execute, frontend="cirq") cal.execute_with_mitigation(circuit)


![image demonstating the code workflow using a `Calibrator` object](/images/mitiq-demo.png)

The Calibrator runs a series of experiments using different parameters on a collection of circuits.
The performance of these techniques are then weighed according to the improvement across a variety of circuits, and the strategy that performed best is returned to be used immediately on your circuit of choice.

Our goal with creating this module is twofold:

1. Make error mitigation more accessible by requiring less expert use in order to operate.
2. Encourage quantum programmers to experiment with error mitigation.

Futher documentation related to this feature can be found in our [user guide](https://mitiq.readthedocs.io/en/latest/guide/calibrators.html), as well as a new tutorial demonstrating the [module in action on a fake Qiskit device](https://mitiq.readthedocs.io/en/latest/examples/calibration-tutorial.html) (along with a [video walkthrough](https://www.youtube.com/watch?v=dB_3R84ewig) of the tutorial).
Since this module is still relatively new, we'd love to hear your feedback!
Whether it's a bug, feature request, or comment, feel free to get in contact at [[email protected]](mailto:[email protected]), or [open an issue](https://github.com/unitaryfoundation/mitiq/issues/new)!

Unitary Fund Q1 2023 Update: UF Members, Mitiq and Metriq updates, and new grants

Tue, 11 Apr 2023 00:00:00 GMT

Dear Unitary Fund community,

We are excited to share our quarterly update and highlight UF's activities for last year in the recently released 2022 Annual Report: Check it out for lots of interesting content on microgrants, testimonials, stats and details on software and research from the past year.

Reminder: unitaryHACK 2023 is coming May 26-June 13th!

Last quarter we announced the 2023 cohort of Unitary Fund members: as core members, IBM Quantum and Scientifica Venture Capital, and as supporting members, Agnostiq, AWS, Cisco, Dorahacks, Pasqal, Quandela, and Qyber. Thanks to their leadership, and the generosity of our other supporters, UF can continue its mission of cultivating the quantum open source ecosystem.

We continue to update Metriq and have implemented an automatic API to run quantum computing benchmarks, as defined by the QED-C consortium. You can read more about it in this blog post.

Mitiq got some nice updates in its documentation and with a new quantum-error-mitigation calibration module that makes it easier to choose the right parameter to apply.

We awarded grants to enrich existing projects of useful tooling, such as OpenQAOA and the Qiskit transpiler, and funded Graphix, the first UF grant supporting the simulation of measurement-based quantum computing.

Thank you all for your continued support of the open-source quantum ecosystem!

Make sure to follow our Discord, Twitter, LinkedIn, and our [email protected]">Community Calendar.

New from UF

Mitiq New Releases: v0.23.0, v0.24.0. New features for the calibration of quantum error mitigation module and a new tutorial; The Examples section is tidied up and now has examples for digital dynamical decoupling (DDD) with Cirq and with Qiskit on hardware. Special thanks to the volunteering contributors for their help on the readout error mitigation module and identity insertion scaling for ZNE: @purva-thakre @nickgardner and @amirebrahimi!

Talks and Posters:

March 9th, 2023 - Qiskit Demo Days, "Updates from Mitiq". @nathanshammah
March 30-31st, 2023 - ARQC All-Hands Meeting, Berkeley Lab, Berkeley, Talk on Mitiq by @nathanshammah, posters by @mistywahl @natestemen @vprusso

Metriq Automatically running QED-C benchmarks on Metriq (check out the blogpost)

UF Research "Automated quantum error mitigation based on probabilistic error reduction", was published in the proceedings of IEEE International Workshop on Quantum Computing Software (link)

Q1 Grants

To Alejandro Montanez-Barrera to simplify benchmarking of optimization problems in OpenQAOA. [arXiv]
To Shinichi Sunami and Masato Fukushima to develop Graphix, an open-source library to optimize and simulate measurement-based quantum computing.
To Harshit Gupta to further develop a timeline debugger for the Qiskit transpiler.

News from UF Projects

HierarQcal: A quick and easy way to build or generate Quantum Convolutional Neural Networks, HierarQcal was featured on the UF blog in a guest post (link)
Lattice Surgery Compiler: A new paper and code for the Lattice Surgery Compiler was published in a paper called "A High Performance Compiler for Very Large Scale Surface Code Computations" You can read it at https://arxiv.org/abs/2302.02459
PyMatching: Paper on sparse blossom (pymatching v2) https://arxiv.org/abs/2303.15933. The paper is on version 2 (released last quarter) of PyMatching, which is 100x-1000x faster than earlier versions. The headline figure is that it can decode both X and Z bases of surface code circuits in under 1 microsecond per round on a single core up to distance 17 at 0.1% circuit noise, which matches the throughput of superconducting quantum computers. Pymatching version 2.1.0 was released in January 2023 with some more minor feature additions.
Quarc QUARC: A Hybrid System for Bounded Model Checking, was featured in a guest post on the UF blog (link)
QWorld: The second edition of the fully-virtual, graduate-level QCourse511-2 "Quantum Computing & Programming" was successfully completed in January 2023. 103 students from 36 countries passed the course. As a part of the class, and with the support of Unitary Fund, QWorld offered five self-study modules covering 30% of the course: Quantum Error Correction, Quantum Annealing, Topological Quantum Computing, Quantum Key Distribution, & Oracular Quantum Algorithms. Each student is asked to complete one self-study module. 83 students completed at least one self-study module successfully.
Plus, QGhana joined the QWorld family as the 25th QCousin: https://qworld.net/qghana/

Coming up this Quarter

Scientifica, a UF member, launched a Call 4 Ideas for startups in quantum!
unitaryHACK 2023 is coming May 26-June 13th! Sign up here!

Unitary Fund 2022 Annual Report

Mon, 20 Mar 2023 00:00:00 GMT

To the Unitary Fund community,

Technology often surprises us with its pace of development. Like many of you, I have been fascinated by recent releases in machine learning. Language and vision models like GPT-4, Claude, Midjourney, Stable Diffusion have debuted impressive features that have many updating their estimates for how soon Artificial General Intelligence may be developed. How has this happened?

Firstly, these results rely on long term investments in computing hardware. From CPUs to GPUs, TPUs, Apple Silicon and other new processors, the decades of hardware development that has led to today’s cloud computing resources have made these leaps possible. The seeds that we are now planting in quantum technologies across computing, networks and sensing will similarly grow over decades and form the foundation of new advances to come.

Secondly, the dominance of open source toolkits and communities has both accelerated machine learning and, so far, made those developments relatively accessible to researchers and companies across the world. It is an active and important conversation about what direction the future of AI will take, but there have been many benefits to how open it has been thus far. Similarly, our mission at Unitary Fund is to ensure that a thriving open ecosystem for quantum technologies can help them develop faster and to the benefit of more people.

The investments we make now in the open quantum technology ecosystem have a huge impact on our future.

We’ve driven this mission further last year,

launching Metriq, the open community-driven platform to host and share quantum technology benchmarks
growing Mitiq, the first open-source toolkit for quantum error mitigation to over 70,000 downloads and 50 code contributors
running unitaryHACK, with awarded bounties to over 63 merged pull requests across 30 projects with the help of 45 maintainers and hundreds of “quantum hackers”
building and launching the Quantum Open Source Software Survey and collected over 1000 responses.
awarding 14 grants to amazing projects, spanning from the first Rust projects supported by UF to an outreach program for highschool students.

<p class="leading-block"> And much more that you will read about in the full <a href="../../assets/Unitary_Fund_2022_Report.pdf" target="_blank">2022 annual report</a>.</p>

We are so grateful to our supporters, advisors, grants winners, open source contributors, hackathon participants and others who have all come together to form the growing Unitary Fund community. Thanks to all of you who have joined us in this mission. We are just getting started,

William Zeng

President, Unitary Fund

Automatically running QED-C benchmarks on Metriq

Tue, 28 Feb 2023 00:00:00 GMT

We are excited to announce the integration of an automated pipeline to add state-of-the-art benchmark from the Quantum Economic Development Consortium (QED-C) into Metriq, the open platform that makes transparent, accessible benchmarks available to everyone in the quantum computing community.

The Technical Advisory Committee (TAC) for Standards and Performance Metrics from QED-C provided an open-source suite of quantum benchmarks (GitHub) to measure the effectiveness of quantum computing hardware for specific applications (further information provided in this preprint). This provided some of the first application-oriented benchmarks that were made public with supporting data along with a preprint, an incredibly valuable asset to the benchmarking community. Recently, the QED-C benchmarks suite was updated and new optimization benchmarks (preprint).

The results of running these benchmarks can be found via this Zenodo posting. On Metriq, we have integrated these results into a submission that captures these results. While this submission on Metriq captures the results obtained by QED-C it also is a “living” result in that it is automatically updated with benchmarks obtained by running the QED-C code on a variety of hardware offerings.

On Metriq, we have established an automated pipeline that is able to run and update our submission via a fork of the QED-C benchmarking suite. This pipeline enables anyone to automatically run benchmarks for a specific algorithm, hardware provider, and quantum processor. This allows the Metriq community to continually extend the benchmarking foundation provided by QED-C to expand their results by running on further hardware providers to obtain up-to-date results.

The backbone of the pipeline is powered by the metriq-client project. This client allows the user to interface with the Metriq platform via a Python API. The user can perform queries or upload batched results via a Python script for submissions that may entail a sizeable amount of results that would be cumbersome to upload manually via the website.

Many new results have been added to the QED-C submission for the Bernstein-Vazarani task on Metriq thanks to the automatic QED-C to Metriq pipeline.

The automated QED-C to Metriq pipeline will be continuing to run on more algorithms and platforms to generate further benchmarking results to be displayed on Metriq!

HierarQcal - A quick and easy way to build or generate Quantum Convolutional Neural Networks

Fri, 17 Feb 2023 00:00:00 GMT

A typical quantum machine learning workflow consists of various components, each influencing the next to ultimately determine model performance. For example, if you want to build a quantum model for music genre classification, a pipeline might look something like this (from Lourens et al.):

Better models require better control over these components and a particularly important one is quantum circuit design. This is because it contributes largely to the expressivity, trainability, and computational complexity of your model. There are multiple levels to quantum circuit design, from the choice of combining individual quantum gates for different unitary operations, to the placement of these unitaries across the circuit. In the pipeline shown above, the circuit design is an instance of the Quantum Convolutional Neural Network (QCNN) which is a quantum circuit architecture inspired by Convolutional Neural Networks (CNNs). The main properties of QCNNs are:

Convolutions: a layer of identical unitaries applied in a translationally invariant manner on available qubits.
Pooling: a layer of measurements on a subset of qubits with rotations based on measurement outcomes applied to the remaining qubits.
Weight sharing between unitaries in the same layer.

The result is a space of circuit architectures that tend to be more computationally feasible (due to the weight sharing and systematic reduction of system size) and that show promising classification performance (Cong et al., Grant et al., Lourens et al.). Two instances of this space are shown below:

Now while these circuits are easy to understand geometrically, i.e. the first "pools" half the available qubits from bottom to top and the second from inside out, their implementation can be cumbersome. This is because you have to loop through all qubits and keep track of indices that correspond to the correct architectural operations like convolutions or pooling. For example, if you have code for QCNN 1 and want to change it to QCNN 2, it ends up being an unnecessarily involved process even though they only differ in a small conceptual way. This is where HierarQcal comes in, it enables the design of quantum circuits in an intuitive way. In fact, the circuits shown above were generated with the following two lines of code:

Semantically QCNN 1 is 8 qubits (Qfree(8)) with a convolution of stride 1 (Qconv(1)) and pooling from bottom to top (Qpool("right")) repeated three times ($\cdot$, $\cdot$)*3. As you can see the code resembles the verbal description of the architecture. It also captures the fact that the only difference between QCNN 1 and QCNN 2 is the pooling direction. This is the idea behind HierarQcal, to provide a way of capturing the design motifs of a quantum circuit in a hierarchical fashion. For example, the bottom-to-top QCNN above can be described with three levels of motifs:

The motifs on the first level we call primitives, the bottom-to-top QCNN has two: a convolution of stride 1 and pooling from bottom to top. One level up the hierarchy we create another motif that alternates between the two primitives, a convolution-pooling unit. The third level motif is three convolution-pooling units repeated. This final motif, which is one directed graph, contains the full QCNN architecture. You can check the paper (Lourens et al.) for the full theoretical framework, but basically, the effect of a primitive is based on its hyperparameters and the effect of its predecessor. This way, their individual and combined architectural effects are captured, enabling them to be dynamically stacked one after another to form second level $l=2$ motifs. Stacking these stacks in different ways constitutes higher-level motifs until a final level $l=L$, where one motif constitutes the entire QCNN architecture.

This hierarchical view is particularly useful for architecture search, algorithms that automatically design model architectures (such as for the QCNN). The main idea is to use smaller operations as building blocks for larger ones which result in an expressive representation that mimics design elements typically performed by humans. In classical machine learning literature, the field of neural architecture search (NAS) explores architecture representations as part of automated neural network construction. In particular, hierarqcal was inspired by the hierarchical representation presented in this paper by Liu et al..

Speaking of inspiration, our logo comes from Dall E 2 presented with the following prompt: A robot building itself with artificial intelligence, pencil drawing

Which touches on the idea of a robot building another, in some way hierarqcal is the pencil that allows you or a robot to "draw" quantum circuits. <br/>

There's a bunch of docs and tutorials that can get you started with building QCNNs or creating algorithms that generate them. Some useful things to mention are:

The package is quantum computing framework agnostic, so you can use it with any framework (e.g., Qiskit, Cirq, Pennylane) or your own, as long as it's in python. This is because the architecture representation is just a data structure and the package allows you to interact with it.
It's quick and easy to create a space of architectures which you can randomly sample to find good-performing circuits for your specific problem/data. This is a nice way get baseline performance for your model. See this tutorial on how to do it.
It's open source! So if you have cool ideas for quantum circuit primitives, feel free to add them. So far we have Qconv, Qpool and Qdense, but there are many possibilities that can be explored based on symmetry, locality, etc.

In all examples so far we've used CRZ and CNOT gates for convolutions and pooling, but this is arbitrary, it's easy to create a custom unitary which you pass to a primitive, for instance:

Where the corresponding code is: <script src="https://gist.github.com/matt-lourens/6cc14d37209de07abd707804f1b0219e.js"></script>

And here is a quick gif to highlight the design process:

That's it for now, a big shout out to the Unitary Fund that made all of this possible! If you have any questions or comments, feel free to reach out to me on twitter MeMattLourens.

Useful Links:

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Announcing the 2023 Unitary Fund Members

Tue, 07 Feb 2023 00:00:00 GMT

Since its launch last year, our membership program has allowed Unitary Fund to build on its foundation of grantmaking and community building to strengthen the quantum technology ecosystem. The support and thought-partnership these companies provide are vital to our efforts to diversify the field, share knowledge and resources, and support community-oriented research projects around the world. These initiatives include our Microgrant program, which has funded 71 grants across 23 countries; The Quantum Open Source Survey, with over 1,000 respondents in its first year; unitaryHACK; our open-access community calls; and Unitary Lab's projects which offer new and accessible tools to move the field forward.

Unitary Fund is proud to list supporters involved in all aspects of quantum technology: Those developing quantum hardware and quantum software, startups and enterprises, domestic and international organizations, all contributing to the open source ecosystem.

"We could not grow a quantum technology ecosystem that benefits the most people without the ongoing support and dedication of this member community. It is through their leadership that anyone around the world can access and benefit from Unitary Fund's programming, resources, and networks. We are thrilled to be working with this cohort to continue accelerating the arrival of quantum technologies and to ensure that their benefits are open and accessible," said Will Zeng, President at Unitary Fund.

We are excited to announce the 2023 Member cohort!

Core Member:

Supporting Members:

Agnostiq, AWS, Cisco, Dorahacks, Pasqal, Quandela, Qyber

We would also like to thank the following organizations for their support of Unitary Fund's mission:

Testimonials from our Members:

"The mission of the Unitary Fund to establish an open quantum software ecosystem is of vital importance to IBM Quantum and Qiskit. We are thrilled to be a part of this initiative which has already demonstrated its value to the broader quantum community" said Luciano Bello, Developer Advocacy Lead at IBM Quantum.

"Democratizing quantum technologies will take a diverse village -- from PhDs through software developers and beyond. While Amazon Braket is a town square for hardware providers, Unitary Fund provides a unique role on the path to democratization by establishing a community for quantum software developers, said Sebastian Hassinger, worldwide business development and go-to-market strategy for quantum computing at AWS. "Microgrants like those provided by Unitary Fund open the aperture even further for those who want to experiment with quantum computing projects through the lens of their expertise and without having to think about equations. This will be key for helping the industry move from theory papers to running code."

Loïc Henriet, the Chief Technology Officer of Pasqal added, "I strongly believe that a robust quantum software ecosystem will be needed if we want to make quantum processors useful. UF's vision to support new and innovative open source projects has already proved to be instrumental to accelerate its growth."

"Unitary Fund is a medium that provides an equal opportunity for anyone with an idea related to quantum technology, science, and education to create and innovate. Both the Unitary Fund microgrant program and the active community play an important role in enabling the largest group of people to contribute and collaborate in meaningful ways. Not only that, but for those who are new to the quantum field, it provides a starting point to ask questions and discover," noted Stephen DiAdamo, research scientist on the Quantum Systems team at Cisco. "Unitary Fund reduces the challenging entry barrier to quantum science allowing the quantum ecosystem to flourish. Cisco being a supporting member allows us to contribute to and support the Unitary Fund community, and moreover allows us to open new learning opportunities for those interested in quantum communication and networks."

Said Jiannan Zhang, Founder and CEO of DoraHacks, "Quantum computing can potentially solve many challenges we face today. While quantum computing hardware develops, it is important to build a strong and inclusive ecosystem that allows people to innovate with quantum technology. Open source developer communities and open source public goods are critical to achieve this goal. Unitary Fund has funded many talents via microgrants and unitaryHack. We are glad to continue supporting Unitary Fund this year and build a thriving open source quantum ecosystem together."

To find out how to get involved in our member program, email [email protected].

About Unitary Fund

Unitary Fund is a 501(c)(3) non-profit whose mission is to create a quantum technology ecosystem that benefits the people around the world. We believe that expanding the pool of people working on quantum technologies is a way to ensure that the benefits of these tools are widely, swiftly, and equitably distributed. We primarily use two major programs to pursue this mission.Through Unitary Labs we work on in-house projects that help the ecosystem as a whole. Through our microgrant program, we fund an inclusive community of explorers across the world to work on quantum technologies.

QUARC: A Hybrid System for Bounded Model Checking

Fri, 03 Feb 2023 00:00:00 GMT

Bounded Model Checking (BMC) is a well-established technique used to ensure the correctness of critical software. Some examples are verifying properties of software systems and malware detection. However BMC techniques do not generally scale. Thereafter, the aim of our project is to develop a compiler that encodes efficiently classical programs so that quantum computers can help accelerating bounded model checking even in the NISQ-era.

QUARC is a compiler that is included in the Unicorn toolchain. While Unicorn provides a word-level representation and some word-level optimizations such as the integration of powerful solvers for the Boolean satisfiability problem (SAT) and satisfiability modulo theories (SMT). SMT are a generalization of SAT, and refer to the problem of determining whether a mathematical formula is satisfiable. QUARC takes this word-level representation to generate an oracle for quantum computers so that we can search for inputs that may cause that certain properties of programs are not satisfied. More concretely, QUARC searches for inputs to programs that cause division by zero, invalid memory accesses, or exit codes different than 0.

For example, if you look at the following pseudocode


int main() {
   int x;
   read_input(&x); // read input and store it in x

   if (x == 100) {
      return 1;
   }
   return 0;
}

the oracle that QUARC produces will evaluate to true only when the qubits that represent <i>x</i> are equal to 100, because for all other value of <i>x</i> the exit code will be 0.

During the grant, we designed QUARC such that it does qubit level optimizations, reduces as much as it can the width of multi-controlled X gates, and also implements an algorithm to reuse ancillae. Moreover, we focus the most in reducing the domain of the function that the oracle is representing so fewer iterations are needed to find the input(s) to programs that cause specific machine states.

Right now QUARC can deal only with a subset of RISC-V, and even it is Turing-complete, we are still working to cover all of RISC-V. Therefore, since RISC-V is applicable to all languages compiled by GCC, QUARC targets a wide public that wants to make their software safer. Moreover, we are writing a paper for QUARC and polishing and optimizing our algorithm for reusing ancillae. As far as we know, QUARC is the first hybrid bounded-model checking and we believe there are certain kind of programs that can get a substantial speedup because of QUARC's encoding.

You can try QUARC with Rust using this link, and also with Python by checking this link.

Finally, QUARC has helped us explain concepts such as unitary matrices, oracles, qubits, superposition to computer science students doing their master's in topics related to formal methods. This is due to the fact that bounded model checking is deeply related with symbolic execution, and symbolic execution is a nice way to perceive quantum parallelism.

We thank very much Unitary Fund for their support. The grant allowed us to push further QUARC, which was initially only in our TO-DO list. The grant motivated us to do even more than was expected since we ended developing an algorithm that reduced substantially the number of ancillae that the final quantum program requires.

The unicorn team.

Unitary Fund Q4 2022 Update: New Ambassadors, Mitiq and Metriq updates, research, and project community calls

Tue, 17 Jan 2023 00:00:00 GMT

Dear Unitary Fund community,

We are excited to share our quarterly update and highlight some of what UF's been involved with so far this year. We announced a new batch of Ambassadors: Alberto, Amir, Nick and Rahul!

We continue to grow the Mitiq project with a wide community (over 50 contributors!). We've uploaded two research preprints using Mitiq: for automated error mitigation and testing error mitigation with Mitiq out-of-the-box on different hardware -- improving results of NISQ devices.

New projects joined the Unitary Fund Discord: OpenQAOA and Covalent.Check out their community calls that are hosted there.

We awarded our first grant ever to a project in Rust, for Quantum Error Correction, to Lev Stambler! We've analyzed and discussed with the community in two open Discord calls the insights from the Quantum Open Source Software Survey:

Thank you all for your continued support of the open-source quantum ecosystem!

Make sure to follow our Discord, Twitter,LinkedIn, and our [email protected]">Community Calendar.

New from UF

Mitiq The Mitiq whitepaper was published in Quantum 6, 774 (2022)

New Releases:

v0.20.0 focuses on updating our support for numpy (1.23), adding a tutorial demonstrating the learning-based PEC workflow, and scoping out what device/noise calibration might look like as part of Mitiq. Additionally identity insertion has been added as a noise-scaling technique available for mitigation protocols such as zero-noise extrapolation.
v0.21.0 officially adds support for the learning-based PEC sub-technique which is now fully documented and functions to apply Readout Error Mitigation (REM).
v0.22.0 focused on improving the Mitiq documentation with three new examples, new REM docs, and navigation improvements, along with some bug fixes. This release also adds a new module calibration which allows one to run a series of experiments to see what error mitigation parameters will work best for their particular setup.

Read more in our updated Examples section.

Special thanks to the volunteering contributors: @purva-thakre and @nickgardner @amirebrahimi!

Blog post: Combining Mitiq with Berkeley Lab's BQSKit for advanced control on compilation with quantum error mitigation by @natestemen

Talks:

November 29th, 2022 - Center for Research in Computing, National Polytechnic Institute Mexico, "Quantum Error Mitigation with Mitiq". @natestemen
October 28th, 2022 - Harvard University, "Quantum error mitigation and simulation with open source tools". Link to slides @nathanshammah
October 24th, 2022 - IBM Research NYC, ""Out-of-the-box" quantum error mitigation with Mitiq". @nathanshammah
October 21st, 2022 - Super.tech & ColdQuanta, ""Out-of-the-box" quantum error mitigation with Mitiq". @nathanshammah
October 20th, 2022 - Northwestern University, "The Mitiq open-source ecosystem for quantum error mitigation". @nathanshammah

Metriq You can keep track of Metriq's new submissions on Twitter!

Submitting new metrics is even simpler with arXiv autocomplete: you can watch a video tutorial here.

Metriq Featured Task Highlight: Quantum Volume

Research

arxiv:2210.08611 "Automated quantum error mitigation based on probabilistic error reduction", Unitary Labs team with Peter Orth (Iowa State) and Ben McDonough (Yale)
arxiv:2210.07194 "Testing platform-independent quantum error mitigation on noisy quantum computers", Unitary Labs team with Ryan LaRose (EPFL)

New Grant

To Lev Stambler to > write a highly performant decoder in Rust for quantum error > correction.

News from UF Projects

QuTiP QuTiP student presentations videos are on YouTube. A live benchmark page as well as a completely new qutip tutorials page are live on the QuTiP website.

QuTiP 4.7.1 was released -- https://github.com/qutip/qutip/releases/tag/v4.7.1v
QuTiP QIP 0.2.3 was released -- https://github.com/qutip/qutip-qip/releases/tag/v0.2.3
QuTiP hit 1,000,000 downloads on PyPI and Conda Forge!

A methods focused guide to quantum error correction: The initial draft of the guide is now available online. Please watch out for significant additions and improvements in the next few weeks.

Inside Quantum: The insideQuantum podcast has completed its first season of 12 episodes! So far, we've spoken with a wide range of fantastic guests including theorists working on quantum information theory, near-term quantum computing and machine learning, as well as experimenters who are using quantum technology to build the quantum internet and detect gravitational waves, and even entrepreneurs who are bringing quantum technology into the business world. If you've missed Season 1, or you'd like to remind yourself of what our guests had to say, be sure to check out our highlights episode - you can find it on our website insidequantum.org or on all major podcasting platforms. We're currently taking suggestions for Season 2 guests, so please get in touch if there's anyone you'd like to hear us talk to!

Coming up Next this Quarter

Xanadu's QHack comes back this February, you can register here
There are still a few days to sign up to MIT's iQuHACK

Metriq Featured Task Highlight: Quantum Volume

Wed, 21 Dec 2022 00:00:00 GMT

Metriq is an open source platform for tracking and sharing benchmarks in quantum technologies. A metric “task” compares performance of “methods” across the same workload of interest. Metriq’s mission is to make transparent, accessible benchmarks available to everyone in the quantum computing community.

We are excited to highlight recent developments in quantum technology research for you, powered by the Metriq platform! This month’s task is Quantum Volume!

Quantum Volume

Task description

Quantum volume expresses the maximum size (quantum circuit depth "n" times number of qubits "n") of square quantum circuits that can be implemented to at least 2/3 heavy output generation rate by a quantum computer, where "heavy outputs" are all outputs with ideal probability above median for the ideal circuit.

Analysis

According to submissions and results to Metriq, as hardware manufacturers announce their own quantum volume results, the state-of-the-art in quantum volume across the field seems to be growing exponentially, which is heuristically equivalent to linear growth in viable qubits.

New developments

Recent results from Quantum Volume in Practice: What Users Can Expect from NISQ Devices highlight the differences between self-report and announcement by hardware manufacturers, presumably under the optimal calibration and scheduling conditions, versus the lower effective quantum volumes that end-users are likely to achieve in practice in user-facing queues for cloud access to native quantum hardware.

Unitary Fund ambassadors announced!

Tue, 13 Dec 2022 00:00:00 GMT

We are excited to announce the new cohort of Unitary Fund Quantum Ambassadors!

About the Ambassadors program

New Ambassadors

The new ambassadors join the previous cohort of ambassadors. We are excited to announce the list below:

Alberto Maldonado Romo, Github, Twitter, LinkedIn. Alberto is a PhD student at the Instituto Politécnico Nacional, in Mexico and has been active in the Quantum Universal Education and Quantum Open Source Foundation activities. He has an interest in quantum algorithms and their application of Grove's algorithm; quantum machine learning using tensor networks, error mitigation using zero-noise extrapolation.
Amir Ebrahimi, Github, Twitter, LinkedIn. Amir, now at Photonic Inc. / U. T. Austin, first interacted with the Unitary Fund in 2021 and then took QWorld's QCourse511 (funded by Unitary Fund) where he first used Mitiq. Amir recently contributed a readout-error mitigation technique to the project and describes Unitary Fund as "at the heart of the "indie QC community"".
Nick Gardner, Github, LinkedIn, is a PhD student at Stanford University. His first contribution to Mitiq was adding quantum volume circuits to the suite of benchmarking circuits. Nick is working on a glossary of background concepts related to quantum error mitigation.
Rahul Mistri, Github, LinkedIn, is a Software Development Engineer at Amazon Web Services in South Africa and a quantum computing enthusiast. He first started attending Mitiq community calls in the background, listening and learning from the always active community. He tries to attend the Friday Community Calls as often as possible and contributed to the project's code (Clifford circuits and GHZ circuits) and documentation.

Spotlights on Ambassadors

We will be hosting blog posts from all the Ambassadors in the coming months so stay tuned right here! You can read more from previous ambassadors' spotlights: Misty Wahl and Andre Alves.

Join our newsletter to get updates about this blog in your inbox, follow us on Twitter, or join our Discord to hang out with the open quantum community 💛🌴.

Unitary Fund Q3 2022 Update: QOSS Survey, interns, Summer school and 7 new projects!

Wed, 09 Nov 2022 00:00:00 GMT

We are excited to share our quarterly update and highlight some of what UF's been involved with so far this year. We continue to grow the Mitiq project and Metriq.info platform with a wider community. We hosted two fantastic interns over the Summer, Maria and Karen, teaming up with Qubit by Qubit. We awarded 11 grants to amazing projects this quarter, spanning from the first Rust project supported by UF to an outreach program for highschool students. Finally, we've released the Quantum Open Source Software Survey and collected over 1000 responses: Thank you all for your continued support of the open-source quantum ecosystem!

Make sure to follow our Discord, Twitter, LinkedIn, and our [email protected]">Community Calendar.

New from UF

Mitiq
- The Mitiq whitepaper was published in Quantum 6, 774 (2022)
- New Releases: v0.17.1, v0.18.0, v0.19.0
  - Version0.17.1 includes support for the latest versions of Qiskit (0.37.1), Cirq (1.0.0), and Pyquil (3.2.1).
  - Version 0.18.0 focused on review and approval of two RFCs, one for Readout Error Mitigation (REM) and one for Identity Insertion Noise Scaling.
  - Version 0.19.0 expanded support to the most recent versions of Python: 3.8, 3.9 and 3.10, and is now compatible with Numpy 1.21.6. We have also added new tools for applying learning-based PEC, and introduced a function for learning depolarizing noise representations from Clifford circuit data.
  - Read more about learning-based PEC in our updated API-doc.
  - Special thanks to the external contributors @yitchen-tim, @amirebrahimi and @isaac-gs!
- Talks:
  - September 22nd, 2022 - IEEE Quantum Week, Workshop on quantum IR, "Mitiq: A cross-platform error mitigation toolkit". @andreamari
  - September 13th, 2022 - Quantum Africa 6 Conference, "Quantum Error Mitigation: An open-source software approach". @nathanshammah
  - August 15th, 2022 - WOMANIUM QUANTUM @Misty-W
Metriq
- Introduction of a new Metriq Twitter account that tracks submissions.
- You can submit results on existing benchmarks or propose new benchmarking tasks to the community. Visit Metriq.info and the #metriq channel on the Unitary Fund Discord to learn more!
- New Releases: v.0.6.0, v.0.6.1
  - Version 0.6.0 focuses on UX upgrades, providing the option to subscribe to specific benchmark updates. Single-page application (SPA) best practices implemented, including improved navigation. Auto-complete fields when pasting arXiv URL in new submission (thanks to @cometta from unitaryHACK!), mobile view and chart style improvements, cookie policy notification when first visiting the website, +30% growth of database, updated Python client models and route end points (thanks to @MariaM0003 and @KarenRezkalla2, QxQ interns). Version 0.6.1 introduced tag subscriptions and daily new submission updates by opt-in.
QOSS Survey
- With over 1,000 responses we have wrapped the first annual Quantum Open Source Survey. We want to thank everyone in the community who responded. This data will be an invaluable resource for all sectors of the quantum technology field, used to help guide funding, research, and new collaborations. The results have been posted on the Unitary Fund website.
New Grants
- To Stefanie Muroya Lei and Christoph Kirsch, to develop QUARC within the Unicorn framework, a bounded model checking that verifies classical programs using the best classical and quantum algorithms.
- To Omid Khosravani to develop adaptive quantum process tomography techniques through the use of reinforcement learning.
- To Kaitlin Gili to conduct an outreach project called Iteration One, sparking curiosity among U.S. high school students with the most limited access to physics and computer science knowledge.
- To Abdullah Khalid to write a methods focused guide to quantum error correction.
- To Hong-Ye Hu, Yi-Zhuang You, and Susanne Yelin, to open-source PyClifford, a fast and flexible Python-based Clifford + few T gates simulator.
- To Tim Weaving and Alexis Ralli, to develop Symmer into a fully scalable qubit reduction toolkit for the quantum computing community.
- To Paria Naghavi to add code, visualizations, and conceptual content to the QIR Book, to build knowledge bridges for incoming users to the ecosystem.
Grant Winner Video Series
- Hosted by Unitary Fund's Misty Wahl, our new video series highlights recently funded projects in the microgrant program. Check out work from QRAND, PIQUE, and 2QAN.
Unitary Fund Intern Blog
- Unitary Fund's summer interns Maria Maryam and Karen Rezkalla have written posts about their experience and work on Metriq's benchmarking tools.
SQMS/GGI Summer School: The UF Mitiq team (@andreamari @mistywahl @natestemen @nathanshammah @ryanlarose) participated in person at the Galileo Galilei Institute Summer School in Florence by SQMS. We gave a lecture on Quantum Error Mitigation (Slides, Video) + a hands-on lab on Mitiq (Jupyter notebooks. Video)

News from UF Projects

Qrack and PyQrack
- We are thrilled that the quantum computer simulator libraries Qrack & PyQrack have officially joined the Unitary Fund GitHub organization of open source quantum computing repositories! Qrack is a quantum computer gate model simulator written in C++11, released under LGPL-3.0.d. PyQrack is Qrack's dependency-free Python ctypes wrapper, to expose Qrack shared library binaries directly for just-in-time (JIT) execution via a Python interpreter: It gained over 300,000 downloads in a few months!
- In addition, Qrack's API v8 has been released! The focus of this update is the enforcement of bounds and input domain checking, to prevent bad user inputs from inducing segmentation faults. This quarter also saw Qrack achieve HPC distribution scaling to at least 8 GPUs in a node.
The ALF project has a new YouTube channel, along with a new reference paper.
QuTiP
- Alex and Simon from the QuTiP admin team gave a short course on QuTiP at the Quantum Africa Summer School in Kigali, Rwanda. You can find the Jupyter book here.
- Google Summer of Code student projects were completed, they are:
  - Christian: DevOps for Jupyter Notebooks in QuTiP tutorials
  - Shreyas: qutip-qip backend for Qiskit (blog)
  - Xavier: QuTiP Benchmarks
QWorld completed a 2-month long internship program, QIntern2022, with 20 projects, hosting 197 interns. New countries have joined the QCousins network. The 2nd Edition of the online introductory course on quantum computing and programming launched this quarter with more than 400 participating students. The course is conducted via a collaboration with the Faculty of Computing, University of Latvia.

Guest Blog Posts from the Community

An Introduction to Creating Quantum Oracles with HODL - Ayush Tambde
Random quantum volume circuits for benchmarking - Nick Gardner

Coming up next:

Metriq Weekly Jam Sessions on Discord are on Fridays at 9am ET
2022 Unitary Fund Ambassadors announcements
New quantum OSS projects hosted on the UF Discord for community calls
Videos from QuTiP's Google Summer of Code student projects
New research performed in Q4
New key features in Mitiq and documentation updates

Results Are in for the 2022 Quantum Open Source Software Survey!

Mon, 07 Nov 2022 00:00:00 GMT

We are excited to share the results for the 2022 Quantum Open Source Software (OSS) Survey organized by Unitary Fund. Collectively, over 1000 responses were provided by the community to the main software survey (Part I) and to the community survey on Diversity & Inclusion (Part II).

You can find the results below and view them in full screen mode at this link.

Part I of the survey was divided into the following sections:

Demographics
Experience (including: Cloud services; Full-stack development platforms and simulators; Software for applications and tools)
OSS Development & Research
Community

Let's highlight some of the most interesting results about quantum open source software users and developers.

Demographics: While the majority of quantum OSS users are researchers (55%), sizable communities identify themselves as software developers (34%), students (31%), educators (15%) or hobbyists (15%). This data speaks for the balanced heterogeneity of interests and sub-communities among quantum OSS users and developers. Almost 40% of respondents do not have a background in quantum research.

While about half of respondents are affiliated to an academic institution (49%), about one third work in an enterprise organization (29%) and a quarter in a startup (25%), with 9% having no affiliation and 8% working in government.

The most represented country is the United States (22%), with India coming in second (12%), the United Kingdom at 9%, and Canada at 6%. EU countries sum up roughly 15%, with Germany first among them at 5%. This data certainly speaks for the enthusiasm that quantum computing is generating in India where, compared to other major countries, fewer institutional or tech transfer initiatives have been developed (e.g, fewer startups or regional programs compared to Europe).

The majority of respondents either work full time (53%) or part time (10%) in the quantum industry, and among those, about 20% work fully remote, about 40% employ a hybrid format, and only 16% are fully in-person, possibly a signal of recent work format changes enabled by technology and accelerated by the pandemic.

Experience: About 90% of respondents use quantum software, of which about half are solely users, and 45% are either OSS project contributors, maintainers, or owners. Turning to Cloud services connecting to real quantum processing units (QPUs) or simulators, about 80% of respondents have used them in the past year: That's definitely a high percentage. The most popular service is clearly IBM Quantum (80% of respondents are current users), most likely leveraging their position as the first major provider of QPUs and providing free access to many devices. IBM is followed by AWS Braket (21% are current users, and 27% would be interested in trying it out in the next 12 months), with Xanadu at 16%, Microsoft Azure Quantum at 15%, and Google at 15%. Users with Rigetti Cloud Services (7%), IonQ (8%) and Honeywell Quantum (8%) are smaller through their individual cloud services, but one should keep in mind that their QPUs are popular and available also through the major cloud service providers. It will be interesting to see if in the future "vendor-lock-in" effects will consolidate the cloud offer or a multiplicity of cloud-access providers continue to build their own platforms will keep broad. Maintenance, documentation and price are major factors for users to decide whether to use a cloud service or another one.

With regards to Full-stack development platforms, respondents have indicated that IBM's Qiskit (including Qiskit Aer) is their most popular library (81%), followed by Google's Cirq and Xanadu's PennyLane (29%) and then by AWS SDK in Python (16%) and tket (15%) (Quantinuum). There is interest in AWS SDK for the next 12 months. Among libraries with more than 10% of users there are Strawberry Fields and QuTiP-QIP (an affiliated project of Unitary Fund and the only project of these not directly backed by a startup or corporate). Other popular libraries are Dwave's Ocean SDK, Q# (Microsoft) and cuQuantum (Nvidia), Rigetti's pyQuil and Quirk. Documentation is deemed very important or important by about 90% of respondents as a factor to weigh in when choosing an SDK.

With regards to tools for applications, Qiskit packages such as qiskit-optimization, qiskit-machine-learning, and qiskit-nature are among the most popular ones, followed by PennyLane's QML repo, OpenQASM, qiskit-finance, tensorflow-quantum and Unitary Fund's Mitiq for quantum error mitigation. Other popular projects include OpenFermion, the PyZX compiler, stim for quantum error correction. There is widespread interest for using other tools in the future such as covalent, qcor, NetKet, ScaffCC, orqviz, tweedledum, QuNetSim, SimulaQron, qmasm, and toqito: these projects range from compilers to network simulators to specific tooling.

With regards to OSS development and research, over 40% of respondents performing research define themselves as algorithm or applications developers, with about one third involved in circuit development & optimization or quantum simulation/Physics. A sizable percentage are involved in software development (30%) and quantum information theory (26%). Other interests include fundamental physics and quantum error mitigation, while less than 13% declare they are performing research in either quantum error correction, qubit characterization, or hardware: that's definitely surprising especially given the importance of QEC and software integration with hardware for the advancement of the field.

The most popular programming language is Python, and this was to be expected, but it is quite impressive that over 94% of respondents use it, while the second most popular framework is far behind, C/C++ (26%), with Mathematica and MATLAB tied at 10%, together with the Julia language. Rust appears at 7%. It will be interesting to see how a scientific language like Julia and a performant language like Rust will change in adoption next year. Jupyter Notebooks and notebooks in general are very popular as tools for software development (used by 78% of respondents), with 68% of respondents using an integrated development environment (IDE) and 52% using the command line or terminal.

With respect to the quantum software community, 56% find it very welcoming, 28% somewhat welcoming and 10% neither welcoming nor unwelcoming or worse. 94% of respondents have a positive view of OSS in the quantum software community, with 78% finding it has a very positive impact and 16% a somewhat positive impact. With respect to the most sought after sources of answers or information when developing quantum software, project documentation or project websites are the two most popular (84%), with project repositories and codebase coming in third. Standard forums are slightly less popular nowadays (8%), when compared to platforms such as the Quantum Computing Stack Exchange, Stack Overflow, and servers such as Slack and Discord, and Youtube videos. It is also quite surprising to read that among the types of resources most helpful for learning or contributing to quantum open source projects, video resources fare first (67% find them useful), followed by digital education text resources, hackathons, participative courses, mentorship programs and certificate or degrees (all above 40%).

Open-ended Feedback on the quantum OSS ecosystem and community from respondents can be found at this link. We highlight just a few below, that emphasize the work needed and requested to support quantum open source software:

"I wish that everyone could assist [the] quantum OSS community to accelerate its development."
"I think there are projects of high quality that are unfortunately underrepresented because they lack polish, industrial support, and/or advertising."
"I’d love to see more community-building; interviews with the personalities behind the tech that emphasize the humanity over the math and physics. We already have the math and physics bits, but do we really know each other?"
"I would like to see a quantum sdk that is not owned by a company and is of high quality. All research-related projects I have seen were not easy to use."
"In my experience the supportiveness and inclusivity of the quantum OSS community has been wonderful (I have most experience with Unitary Fund and Qiskit communities). As a student, finding a good and supportive teacher/mentor has always been the thing that decides which subject areas I end up falling in love with. The same has been true for learning about quantum computing, and quantum OSS. [..] the extent to which the quantum OSS community is welcoming and encouraging (and correspondingly does not fetishize "brilliance", "innate intellectual ability", or formal training in the way many STEM fields do)--will determine, more than anything else, the extent to which quantum computing can become a diverse, open and truly meritocratic (in the positive sense) field in the future. The idea that this kind of social-political progress in STEM can be part of what QC contributes to humanity is part of what motivates me to pursue a career in QC (in addition to the intrinsic fascination/wonder of QC, which is for me the primary reason)."
"It's something I've noticed in traditional open source software, and something I hope doesn't carry through to quantum open source software: OSS is taken for granted and doesn't get the recognition it deserves (which has hindered it), I think that we should publically recognise and celebrate the impact of Q-OSS, even if it's under a proprietary company (eg Cirq, Qiskit etc)"

Community: Diversity & Inclusion

Part II of the survey (shared as a separate survey for anonymity and hence in principle with a different or overlapping pool of respondents) focuses on providing a snapshot of the diversity and inclusion of the quantum software community. Similarly to the software survey of Part I, it shows that the USA and India are the most represented countries of residence. About a half of respondents are in the 25-34 age range, with 20% of respondents below 25 (but only 1% under 18 years old).

With regards to ethnicity, about a half of respondents identifies as White or of European descent, 12% as South Asian, 8% as Hispanic or Latino/a/x, 6% as Black or of African descent, and 4% or below as East Asian, South East Asian, Multiracial, Middle Eastern, Other, or prefers not to say. 73% of the respondents identify as male, 19% as female, 3% as non-binary, genderqueer, or gender non-conforming, 1% other and 7% prefer not to say. With respect to educational background, the largest group holds a PhD (36%) or multiple ones (2%), 33% have Masters or other non-doctoral post-graduate degree, 22% have a university degree and 8% high school/secondary school degree, other degrees, or prefer not to say. With respect to sexual orientation, 77% are straight/heterosexual, 9% bisexual, 9% prefer not to say, 2% are queer, 2% are gay or lesbian, and 1% have another orientation.

With respect to physical disabilities, 86% do not report any, while 7% prefer not to say and 5% replied other. 1% of respondents are blind or have difficulty seeing, are deaf or hard of hearing or unable to(/find it difficult to) walk or stand without assistance. With regards to mental health, 66% are not diagnosed with any mental health condition and 12% preferred not to say. Other respondents selected anxiety (12%), mood or emotional disorders (9%), concentration and/or memory disorder (8%), other (2%), autism (1%), or schizophrenia (1%).

Methodology

The survey has been open Sept. 7 – Oct. 7, 2022. The data is stored at github.com/unitaryfoundation/qoss-survey.

Unitary Fund circulated the surveys on its social media platforms (Discord, Twitter, LinkedIn, UF blog) and contacting major blogs (QC Report, Qiskit blog, PennyLane blog, etc.), newsletters (UF mailing list, QuTiP mailing list, ORNL quantum computing newsletter, IEEE Quantum, QED-c newsletter, academic networks, etc.), UF members, supporters and partners.

We are excited to repeat the survey in coming years and track the changes and trends in responses and in the field. Thank you to all that have participated!

Combining Circuit Compilation and Error Mitigation

Mon, 03 Oct 2022 00:00:00 GMT

Quantum circuit compilation is a task that has become ubiquitous in today's quantum programming landscape. Just as a classical program compiler takes programs specified at a high-level of abstraction and brings them down to a lower level that hardware can "understand", a quantum compiler converts abstract programs to a set of instructions amenable to a quantum processing unit's (QPU) constraints. Within the currently most common formalism of quantum programs as composed of "quantum circuits" (a series of gate operations on qubits), a compiler needs to transform the original quantum circuit by taking into account the QPU's characteristics, such as the native gate set (what gates can be implemented) and the processor topology (which qubits interacts with other qubits). This is an extremely important part of what is a full quantum stack, and is an active area of research how best to compile quantum circuits, e.g., by optimizing the depth of the quantum circuit or the frequency of a two-qubit gate, in order to reduce the impact of noise on the computation.

Error mitigation is a collection of techniques used to improve the performance of near-term quantum computers. While we hope one day to run error corrected codes that find and fix errors as they occur, current machines are not large enough, nor reliable enough for this task to be applied at scale. To this end error mitigation can make the computation of existing quantum computers more accurate and is believed to be a necessary stack also in the near term.

Both circuit compilation and error mitigation are increasingly important in building a full stack experience for near-term quantum computers, and hence it's important to understand how these two technologies interact. For this purpose, the Unitary Fund technical staff, working on the Mitiq error mitigation toolkit, teamed up with the team at Lawrence Berkeley National Laboratory who is developing the Berkeley Quantum Synthesis Toolkit---often written BQSKit for short---which is a compiler aimed at reducing circuit depth by reducing CNOT gate count. In the BQSKit team's research, they have been able to show their compiler reduces CNOT gate count up to 80% for specific quantum algorithms [1].

To begin to understand this tool's interplay with Mitiq we have written a tutorial which can be found in our documentation that describes a workflow of using the BQSKit compiler together with Zero-Noise Extrapolation, one of the quantum error mitigation techniques available through Mitiq. The tutorial demonstrates how the two packages work in tandem by generating random circuits and comparing the accuracy of error mitigation on pre and post-compiled circuits. This example was also discussed in the BQSkit tutorial given by Ed Younis and Costin Iancu at IEEE Quantum Week.

The tutorial was written before the 1.0.0 release of BQSKit which includes many improvements that we are working to support and incorporate soon. Check back for an updated tutorial and more results on the interaction of these two tools!

References

[1] Patel et al., Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (2022).

Introducing Mitiq, an open-source software package for error mitigation on noisy quantum computers

Sat, 10 Sep 2022 00:00:00 GMT

We're excited to introduce Mitiq, a toolchain that helps reduce errors in noisy quantum computers.

See it in action! Here's an example in Qiskit:

And in Cirq:

Mitiq's white paper has just been uploaded on the arXiv. In it, we introduce the library and guide first users through its main features. Mitiq is designed to be a thin layer between quantum programmers (and their circuits) and real quantum processors of choice, or simulators.

In the paper, we show how to improve the performance of real quantum processors, running quantum programs on publicly available quantum computers on the cloud, Rigetti Computing and IBM Q processors.

To begin with, we've focused on zero-noise extrapolation, an error mitigation technique that has already been tested in the lab. We show how to use zero-noise extrapolation even if you don't have low-level laboratory access to your QPU. Instead, you can implement digital zero noise extrapolation.

If you're interested in Mitiq and in quantum error mitigation, you can find information on usage and additional references in Mitiq's documentation at mitiq.readthedocs.io. To keep up to date with Mitiq's development, you can sign up for Unitary Fund's mailing list.

We're looking forward to the feedback of the quantum software community: from fixing bugs to proposing enhancements in zero-noise extrapolation to additional quantum error-mitigation techniques. We're keeping a list of events where members of the Unitary Labs team will be attending.

Best wishes,

Unitary Labs – the Engineering team at Unitary Fund (Andrea Mari, Nathan Shammah, Peter Karalekas, Ryan LaRose, and Will Zeng)

Announcing the Quantum Open Source Software Survey

Tue, 06 Sep 2022 00:00:00 GMT

We’re excited to share the first Quantum Open Source Software (QOSS) Survey with you all!

Please take a couple of minutes to fill out the QOSS Survey here

The QOSS survey aims at obtaining a community-wide and industry-wide snapshot that is representative of everyone who codes or wants to code for and with quantum computing technologies. We'll share the results publicly to ultimately get a better understanding of the quantum computing community’s needs and background and improve products/services/events and educational material.

The survey covers information on demographics, experience, community, research, tech stacks and specific feedback. A related survey addresses Diversity & Inclusion questions.

Please take a couple of minutes to fill out the QOSS Diversity & Inclusion Survey here

Once we collect all the responses, we will analyze this data based on each subsection, report our findings, and publish the aggregated results on the Unitary Fund website.

If you are a user or developer of software for any kind of quantum technology, we kindly encourage you to take this 5-10 minute survey. You have time only until September 23rd, 2022 to fill them out:

Fill out the QOSS Survey here Fill out the QOSS Diversity and Inclusion Survey here.

We thank all the community members that helped design, test and provide general feedback for this survey, from Unitary Fund advisors to Unitary Fund members and partners.

Inaugurating the Grant Winner Video Series

Fri, 26 Aug 2022 00:00:00 GMT

We are very excited to share our first episodes of Unitary Fund’s Grant Winner video series! Watch to learn more about our featured grant winners, their projects, their experience after winning the grant, and what they’re working on now.

Hosted by UF Technical Staff Member Misty Wahl– our first video features Pedro Rivero, author of QRAND and our second video is with Lia Yeh, Samanvay Sharma, and Alberto Maldonado with PIQUE.

<a href="https://youtu.be/LSOCHWSPvUc">About QRAND</a>: QRAND introduces a versatile interface layer between NumPy and several quantum computing platforms (qiskit, cirq, qsharp...), along with some useful functionality that enables the production of quantum random numbers (QRN) according to different quantum protocols, and for a wide variety of probability distributions.

<a href="https://youtu.be/wSFmtkS-AP8">About PIQUE</a>: People Interested in Quantum Universal Education (PIQUE) is a non-profit community that aims to disseminate educational resources about quantum. This community is focused on open educational resources in order to support the training of different students who want to share and/or learn about quantum.

Learn more about <a href="https://youtu.be/LSOCHWSPvUc">QRAND</a>, <a href="https://youtu.be/wSFmtkS-AP8">PIQUE</a>, and stay tuned for more videos!

Do you have an idea for a project in quantum technology? You can apply to a Unitary Fund Grant! Learn more here: <a href="https://unitary.foundation">https://unitary.foundation</a>

Meet the UF Interns - Karen Rezkalla

Mon, 22 Aug 2022 00:00:00 GMT

About Me

I am one of the Unitary Fund's interns here for Summer 2022. I am a rising sophomore Computer Engineering and Applied Mathematics double major at the University of Maryland, College Park, MD. I participated in the Qubit by Qubit training program for future quantum leaders before working with Unitary Fund. At my university I am a research assistant for the characterization of cosmic dust research for the NASA DART mission with UMD. I'm also in the Quantum Machine Learning research program with the Joint Quantum Institute (JQI) at UMD. I am very passionate about quantum computing and its application in the space industry.

Early Quantum Career Immersion Training and Internship Program

The Coding School aims to bring the opportunity of learning the skill of computing to primary and secondary education cohorts. Qubit by Qubit, which is part of The Coding School, created the Early Quantum Career Immersion Training and Internship Program aiming to provide undergraduate students that come from disadvantaged backgrounds and minorities to learn and have a voice in the quick paced growth of the quantum computing field. As a first generation Egyptian immigrant with a passion to grow my knowledge in quantum computing, the training program taught me all the essential physics, quantum mechanics, computer science, and leadership skills to use in my internship at Unitary Fund but also to add on to the growth of the quantum computing field. Moreover, it provided me with a wonderful community of like minded people to learn with and from but also friends that I will always stay in touch with. Here is the rundown of the 10-week program:

Weeks 1-4: Full time training with Qubit by Qubit. We learned Quantum Mechanics, Linear Algebra, and Computer Science from our instructor Phil Labrum. We got python interview questions to increase professency. Katherine Hanna and Lana Martin provided the leadership and professional development courses.
Weeks 5-6: Maria and I worked part-time with the Unitary Fund team and built the first open source Randomized Compiler with a group of my classmates from Qubit by Qubit.
Weeks 7-10: Full time work with the Unitary Fund team.

Metriq: Working at Unitary Fund Part-Time

During my two weeks of part time with Unitary Fund, Maria and I were assigned to work on the Metriq Project with Daniel Strano and Vincent Russo. Metriq is focused on making accessible benchmarks available for anyone in the quantum computing community. We made 10 submissions a week to the website adding tasks, methods, platforms, tags, and results to build the Metriq database as well as submitting issues regarding the website. I also started participating in the Discord and learning wonderful things from such a diverse community.

Metriq: Working at Unitary Fund Full-Time

After being familiarized with Metriq, while posting issues whenever we deem fit, it came the time to work and fix those issues. Since we worked with Python during our Qubit by Qubit training, we were assigned to update the Python client with the current JSON models. But first, we had to become full stack developers and use git. We learned how git works and how to use it thanks to Dan who guided us through every hurdle in the process. After a week of constant researching and trial and error, I finally had the frontend and backend environments accessible on my computer! I learned from Dan so much throughout that week. Mostly how experience, especially with software environments, betters your problem solving skills but also patience. Being patient with solving a problem but also with yourself giving time for you to learn how to tackle it is key to efficient problem solving. Furthermore, we spent time working on our weekly milestones, solving issues, understanding github etiquette, and communicating ideas and suggestions. We also participated in the majority of community calls. Always attending the UF Engineering meeting to hear the team plan and implement Unitary Fund missions, participating in the Marketing team meeting and learning how to increase accessibility to our projects, and getting to understand more about Mitiq too. Throughout that course of time, we were also able to meet one on one with the team. Talking to Will, Misty, Nathan, Dan, and the rest of the team made it OUR team too.

Closing Note

Thanks to Unitary Fund I learned how to be a better researcher, analyst when reading academic papers, a problem solver, a full stack developer, a team member,and a better learner. Also thanks to The Coding School and Qubit by Qubit for the thorough training and also for the community I made with my classmates and the one at Unitray Fund.

Meet the UF Interns — Maria Maryam

Mon, 22 Aug 2022 00:00:00 GMT

I was introduced to the Unitary Fund through The Coding School’s- Qubit x Qubit Early Quantum Career Immersion Program for undergraduate students. In June 2022, After three weeks of rigorous quantum computing training with Qubit x Qubit, I began my seven-week internship with the Unitary Fund. When I applied to the program and began learning about quantum computing, I had very little knowledge and experience in both quantum and classical computing. After learning the basics of quantum computing, I was eager to start my work with Unitary Fund and learn even more through hands-on work.

MY BACKGROUND

I am a second-year student at CUNY Queens College where I am double majoring in Computer Science and Linguistics. I am interested in machine learning, NLP, quantum computing, and any form of software development that is able to reach and help people.

THE INTERNSHIP

The first two weeks of my internship were part-time, during which I got to know the team and the projects better. Our first assignment was to make ten submissions to Metriq, in a week. This required a ton of reading through research papers, trying to understand tensor networks, and attempting to extract results from jargon-filled and oversaturated papers. Although it was not easy, it was incredibly beneficial for multiple reasons. The obvious reason is that I learned a great deal about quantum computing and scientific papers in general. I also got very familiar with the user interface of Metriq, which would be very beneficial for me in the coming weeks.

The second week was very similar, we had to add ten more submissions to Metriq, and we also had to open issue tickets on Github, things that could be improved regarding the user interface, or bugs that we noticed while making submissions. Much like the first week, I learned a lot and met with new people on the community Discord server. I love how open and diverse the community is because as a woman of color, it is difficult to find spaces that are welcoming, especially in the tech community. Everyone was extremely kind and helpful whether they were researchers at different companies or other students like me.

After the first two weeks, we began working full time, and this is when I truly got my first taste of web development and programming in general. We spent a few days setting up the web development environment which isn’t easy to do remotely, but Dan was immensely helpful and patient when I couldn't figure out how to clone a repository.

After setting up, we finally got to work behind the scenes of Metriq. We started updating data transfer object models and learning a great deal from Dan about data and how it is stored and moved. After updating the models, we tested the models to make sure each workflow was working as it should have been. The weeks we spent working on this were extremely exciting. Even though I didn’t completely understand everything, I enjoyed learning something new every day. I also appreciated the fact that Dan and Vincent trusted us with helping them improve their incredible hard work, Metriq.

The task I was most proud of completing during the internship was a front-end issue ticket that I solved. I added additional functionality to a button through the enter button. This was quite exhilarating albeit challenging. Making changes to the front-end of an application is especially exciting as a new developer because those changes can be seen by anyone and they are more tangible than other changes.

My experience as an intern at the Unitary Fund is one that I will cherish forever. It was my first experience in a professional setting, and I have learned a ton, not just technical skills but soft skills as well. I am extremely grateful that everyone decided to give me a chance to learn. The patience and kindness I was met with made this an unforgettable experience. I will definitely be contributing to open source projects of all types because of the Unitary Fund. Thank you to Karen Rezkalla for being a great friend and fellow intern during this journey. And finally, a huge thank you to the whole team, especially Dan and Nathan, for being an amazing group of mentors.

<p class="leading-block"> Stay up to date with what Maria is working on by following her on <a href="https://github.com/andre-a-alves" target="_blank">GitHub</a> and <a href="https://www.linkedin.com/in/maria-maryam-87432821b/" target="_blank">LinkedIn</a>! </p>

An Introduction to Creating Quantum Oracles with HODL

Fri, 19 Aug 2022 00:00:00 GMT

Overview

There are many languages and frameworks out there for writing quantum computing programs, such as Qiskit or Q#. However, many algorithms require black-box functions to work, and implementing these oracles in such frameworks is often cumbersome and non-intuitive.

Higher-Level Oracle Description Language, or HODL, is a programming language designed to make it easier to write oracles for quantum programs, providing a C-style interface through which we can code logic and arithmetic. It currently compiles to either OpenQASM 2.0, the Quantum Intermediate Representation (QIR) standard, or you can use it through a Qiskit interface. HODL is generally not intended to be a complete quantum framework — rather it was designed to do one thing really well, and that’s writing oracles.

Why HODL?

Let’s say for the sake of example that we want to write a program to perform the quantum search algorithm on a uniform superposition of 3 qubits. This means that all x from 0–7 are present with equal probability. We wish to use quantum search to find x where xy < y For any real, positive value of y, the only solution for x is 0. I’ve chosen this particular example since it showcases multiple features of HODL, such as multiplication, comparison, and uncomputation. While this will likely be a real pain to write using current frameworks, even using existing libraries, HODL handles all the complicated bits, letting you focus on the more important parts of your program. For a more detailed comparison between current frameworks and HODL, check out this paper¹.

So what does such a program look like in HODL? I’ll show you the code, and then we’ll dissect it line-by-line:

function some_oracle(super var, int num) {  
   if(var * num < num) {  
      mark(var,pi);  
   }  
}  
function main() {  
   super variable = 8;  
   some_oracle(variable,4);  
   diffuse(variable);  
   measure variable;  
}

Okay, so let’s break this down:

The first line declares a function, called some_oracle. This function accepts two parameters, a super and an int. A “super” is a way to denote a quantum variable, vs. using “int” for a classical integer, and also provides a handy way of declaring uniform superpositions, as you can see in the first line of the main function.

The next block of code checks that the inequality condition holds, and if so, applies a phase of π. Due to the principle of superposition, this ensures that all terms that fit the condition will be “marked” with a negative amplitude.

That’s it! That’s our oracle fully written. The next block contains the “main” function, within which we declare a uniform superposition of three qubits, apply the oracle, call the diffusion operator, and measure the result.

Compilation

Now how do we actually compile and run this code? If you use MacOS, and have Homebrew installed, then simply just “brew install hodl”. It’s also available on Anaconda, with conda install -c at2005 hodl. Then, once you’ve added the executable to path, execute the following command:

hodl --target qasm -o out.qasm code_file.hodl

to compile to OpenQASM 2.0, or:

hodl --target qir -o out.qir code_file.hodl

for QIR compilation, where you can replace code_file.hodl with whatever you choose to name your source file. After that, you can run out.qasm on whatever QASM-based system you want, and out.qir on a suitable QIR simulator.

What can HODL do?

HODL is a compiled programming language, meaning that a program called a compiler parses the code and converts it into a format computers can understand.

Classical interpretation. For example, if the programmer has 2+2 tucked away somewhere out there in the program, it’s going to be interpreted to 4, prior to code-generation. This example may seem a bit trivial, but classical interpretation doesn’t just parse constant expressions, but also those containing pure classical variables. This means that constructs such as loops and classically-conditioned if-else statements are expanded out.
Register-size estimation — simply meaning you don’t need to keep track of how the sizes of your registers change throughout the program. It also ensures that ancillary registers are allocated with a sufficient number of qubits so that the program outputs the desired result.
Uncomputation and garbage collection. What’s also pretty nice is that after ancillary registers are used up, HODL uncomputes them back to zero and recycles them as required. This ensures the program doesn’t go awry due to unwanted interference!

Qiskit Library

If you’re already working with another framework, such as Qiskit, and don’t want to work in two languages, then the hodl-qiskit library enables you to call HODL from inside Qiskit and output a QuantumCircuit object. You can read my other post which provides a deeper dive into the topic.

Conclusion

HODL is currently undergoing some serious development, while also being funded by Unitary Fund². There’s a lot to do, including writing documentation, fixing bugs, and making HODL a pretty handy and likeable tool for beginners and experts alike.

Notes

[1] In the paper there are some slight syntactical differences between the implementation of the diffusion operator, and use of the “oracle” datatype, which has since been removed for simplicity purposes.

[2] https://unitary.foundation/grants.html

Ayush Tambde is a secondary school student living in Dublin, Ireland. He is the author of the HODL language, and has received a grant from Unitary Fund to continue work on it.

Qrack and PyQrack join the Unitary Fund Organization

Mon, 01 Aug 2022 00:00:00 GMT

We announce with great pleasure and excitement that the quantum computer simulator libraries vm6502q/qrack and vm6502q/pyqrack have officially joined the Unitary Fund GitHub organization of open source quantum computing repositories! Get started with Qrack from the docs here.

Started by Daniel Strano (technical staff member of Unitary Fund) and Benn Bollay (CTO of Fusebit) in 2017 and winner of a Unitary Fund microgrant in 2019, Qrack is a quantum computer gate model simulator written in C++11, released under LGPL-3.0. Qrack is intended to provide maximum performance and minimum memory footprint for quantum computing workloads run on classical computer hardware. PyQrack is Qrack’s dependency-free Python ctypes wrapper, to expose Qrack shared library binaries directly for just-in-time (JIT) execution via a Python interpreter. Plugins and providers are available for Qiskit, XACC, and even the Unity video game engine, with plans to expand plugin support to virtually every major quantum open source framework in the global ecosystem. Supported platforms include all available Original Electronic Manufacturer combinations of x86_64, x86, ARMv7, and ARM64 instruction sets with Linux, Windows, Mac, iOS, and Android operating systems, as well as WebAssembly (Wasm).

Given Qrack’s support for Wasm, we’ve joked at the Unitary Fund that Qrack can theoretically run on literal internet-of-things enabled smart refrigerators, but open an issue ticket on the repository if we’re blowing smoke and you still need developer support for your smart fridge, seriously!

QFT Benchmark

A standard example of Qrack (and PyQrack) performance is the quantum Fourier transform (QFT). Comparative results from benchmarking are in the graph below and are available on Metriq (as single-valued exponential trendline slope comparisons). Historically, Qrack measures this benchmark with an initialization by random 3-parameter unitary single qubit gates across the register width for a fair comparison, because Qrack QFT performance on computational basis states is classically efficient because of the underlying Schmidt decomposition. That wouldn’t be representative of general demands for cases of the QFT. While Qrack would perform worse for a random fully entangled case, our choice of randomly initialized separable qubits generally become fully entangled by the end of the circuit, paying a representative performance penalty for potentially composing every initially separable qubit. Hence this has historically been deemed a fair benchmark by the Qrack team.

PyQrack has a commanding performance lead on this benchmark compared to other popular quantum computer simulators like Qiskit Aer (GPU) and QCGPU, where these three candidates are GPU-based simulators. Qiskit Aer (CPU) and Cirq (CPU) have been included on the chart, run on the same stock gaming laptop as the three GPU simulators, but remember that these software benchmarks are most fairly compared on identical hardware, whereas it isn’t possible for a CPU model and a GPU model to be the exact same hardware instance, obviously. However, PyQrack’s hybrid CPU/GPU methods utilize CPU simulation at the low qubit width end of the trend, which should be a fair comparison against CPU simulators until the user-selectable GPU switching threshold, which is 9 qubits in this case.

Qrack Architecture

Qrack is a collection of stacking and interchangeable optimization layers, which include OpenCL-based, scalable multi-device GPU, CPU, and GPU/CPU hybrid state vector simulation at base, hybrid stabilizer simulation with full and transparent recourse to state vector representation as fallback, an auxiliary quantum binary decision tree layer, and Schmidt decomposition techniques layered over stabilizer and state vector simulation for proactively and reactively identifying separable cuts in qubit subsystem representations to reduce memory footprint and improve execution speed. Floating point precision options available from source build include half, float, and double, with even limited support for quad math. By design, most users don’t need to worry about complicated custom configuration of the layers and settings at all; just instantiate a default C++11 QInterface or Python QrackSimulator class and go! The highly-optimized default layer stack will automatically leverage hybrid stabilizer simulation for a Clifford circuit or preamble, for example.

Check out the repositories on the Unitary Fund GitHub organization, star and share, and get Qrackin’! You rock!

Random quantum volume circuits for benchmarking

Sun, 31 Jul 2022 00:00:00 GMT

About quantum volume

This past spring I contributed a function to Mitiq for sampling random quantum volume circuits. Quantum volume is a single-number benchmark for near-term quantum computers proposed in 2019 by researchers at IBM (see here for a nice overview). The quantum volume of a quantum computer quantifies the largest random circuit of equal width (number of qubits) and depth (layers of gates) which that quantum computer can successfully implement. As a benchmark, it is meant to serve as a more accurate single-number summary of the quality of a quantum computer than simpler quantities such as the number of qubits, or average gate fidelity. Various features of a quantum computing system jointly contribute to its quantum volume score, including how many qubits it has, the fidelity of its operations, and the degree of connectivity of its qubit layout.

Random quantum volume circuits

The random quantum circuits used in quantum volume experiments consist of d layers of the following computation performed on d qubits: randomly permute all qubits, then apply random two-qubit unitary transformations to every pair of adjacent qubits (leaving one qubit out each time if the number of qubits is odd). Success in executing the circuit is defined in terms of the heavy output generation problem (can the computer produce a set of output strings more than two-thirds of which are "heavy"--have a greater than the median probability of being generated--for that random circuit?).

Adding quantum volume circuits to Mitiq

The functions I implemented for Mitiq generate this type of random circuit and calculate (classically) its set of heavy output strings.

This was my first real project in the world of quantum computing software, and thanks to the Mitiq team it was a great experience--I learned a ton and am excited to work on future Mitiq projects. Thank you especially to Andrea, Nathan, and Misty for being so welcoming and helpful!

About me

I am a graduate student at Stanford University interested in quantum computing, focusing on quantum error correction. Working on a team with Nyle Wong and Zhaoyi Li, I began contributing to Mitiq in the Stanford course "Quantum Computing: Open-Source Project Experience" (CS59SI).

Unitary Fund Q2 2022 Update: Metriq, unitaryHACK and new projects!

Mon, 11 Jul 2022 00:00:00 GMT

Dear Unitary Fund community,

We're excited to share our Q2 2022 quarterly update and highlight some of what UF's been involved with so far this year.

We launched Metriq, the community-driven platform to benchmark quantum computing metrics. We partnered with IQT Labs, USRA, RIKEN, the SQMS quantum research center, Cambridge Quantum, Strangeworks, Agnostiq, Super.Tech, Quantonation, the Quantum Computing Report and more organizations. Add and review benchmarks at: https://metriq.info/

unitaryHack 2022: our quantum open source hackathon rocked the quantum dev community! We made distributed bounties to over 63 merged pull requests across 30 projects. Read more in the blog post about wrapping-up unitaryHACK 2022.

As the year progresses, we remain committed to growing the quantum open source ecosystem. Thank you all for your continued support. Make sure to follow our Discord, Twitter,LinkedIn, and our [email protected]">Community Calendar.

New from Unitary Fund

Metriq: Read more about the announcement here from the Metriq team developers, Dan Strano and Vincent Russo
unitaryHACK was a blast! You can find results on the event page.
The Unitary Fund staff mentored Nick, Nyle, and Zhaoyi, three students from Stanford's CS59SI course, helping them getting started with quantum OSSS and contributing to Mitiq.
Mitiq: We released version 0.14 through 0.17 of Mitiq (full changelog):
- In version 0.14 we focused on updating dependencies and making progress on two new features, dynamical decoupling and learning based error mitigation techniques. A number of high priority bugs and issues also were fixed.
- In version 0.15 we focused on updating dependencies and making progress on two new features, dynamical decoupling and learning based PEC. For dynamical decoupling, high-level functions and rules were added. For learning-based PEC, a function calculating representations with a biased (combination of depolarizing and dephasing) noise model was added. Several high priority bugs and issues were also fixed. Special thanks to new contributors @RubidgeCarrie and @nickdgardner for their contributions to this release!
- In version 0.16 we finalized the documentation of Digital Dynamical Decoupling. This is a major milestone, you can read more about this technique in this blog post.
- Version 0.17 was focused on unitaryHACK contributions.
New manuscript co-authored by Unitary Fund's staff member, Vincent Russo, on "Arkhipov's theorem, graph minors, and linear system nonlocal games", arXiv:2205.04645

New Grants

To Haoxiang Wang and Min Li, to develop a high-level API for variational quantum algorithm (VQA) training with quantum error mitigation.
To Matt Lourens, to develop Dynamic QCNN, a tool to generate quantum convolutional neural network models programmatically.

News from UF Projects

Blog: How to Run Programs on Quantum Computer for Free
QuTiP:
- The QuTiP project published its 2021 Annual Report. Highlight: Over 0.8M downloads.
- The video of the Quantum Software Talk on QuTiP QIP by Boxi Li is online for everyone to watch!
- QuTiP Google Summer of Code projects 2022 have successfully started. You can get updates from the students on their projects:
  - Christian: QuTiP notebook CI testing and v5 update; https://christian512.github.io/
  - Xavier: QuTiP benchmarks https://xspronken.github.io/
  - Shreyas: qutip-qip backend for Qiskit https://medium.com/@claretgrace0801/the-qiskit-skeleton-8f228f2d731e
Qrack: The Quantum Insider ranked Qrack as #5 best QC simulators for 2022, in a list of the top 63
InsideQuantum, the podcast telling human stories behind quantum technologies, just launched the first two episodes
The ALF project added: modularity, HDF5 support, installation script. More details here
A publication on the BraKetVue project just came out: P. Migdał, K. Jankiewicz, P. Grabarz, et al. "Visualizing quantum mechanics in an interactive simulation - Virtual Lab by Quantum Flytrap", Optical Engineering 61(8), 081808 (2022)
QWorld organized a very successful Quantum Science Events Days Conference with more than 700 participants. You can watch Unitary Fund's talks here:
- Nathan Shammah on "Quantum Error Mitigation on NISQ computers and simulators"
- Dan Strano on "Metriq: a platform for community-driven quantum benchmarks | QSD 2022"
- They conducted a fully-online graduate-level pilot QCourse on "Projects in Quantum", supported by Unitary Fund
- QFrance has joined the QCousins network
- QSpring2022 started with several local workshops conducted by around 20 QCousins

Coming up next quarter:

Maria and Karen are interning for part of the Summer at Unitary Fund! This is within the Qubit by Qubit (QxQ) program "Early Quantum Career Immersion: Training & Internship Program (EQCI)", which provides promising diverse undergraduates with a pathway into quantum computing
Unitary Fund's Ryan LaRose, Nathan Shammah and Andrea Mari will give talks at SQMS/GGI Summer School on quantum simulation in Florence, July 26-29, 2022

Wrapping up unitaryHACK 2022!

Fri, 08 Jul 2022 00:00:00 GMT

Whether you were a participant, maintainer, bounty hacker, or community member: Thank you for participating in unitaryHACK 2022! It was a blast 💛🌴. Check out some of the highlights from the event!

## Community voices

It's been great to host a kick-off party on Twitch, hosted by Misty Wahl, from the Unitary Fund technical staff and a Mitiq maintainer [Video], together with other project maintainers and community leaders, including:

Catalina Albornoz, from Xanadu's Pennylane

[Video]
Luciano Bello, from IBM's Qiskit

[Video]
Filippo Vincentini, postdoc at EPFL and maintainer of NetKet

[Video]

Hear what our community members had to say about unitaryHACK!

From Alberto Maldonado, maintainer from the Quantum Universal Education project,

"UnitaryHack is an event where you can demonstrate your skills and abilities, while helping and make an impression on the quantum community."

Maria Gragera Garces, first-time contributor to the Quantum Universal Education project with a bounty and also to Qiskit, said that

"UnitaryHACK was a great place to learn and network with members in the quantum community. It was an amazing experience for me! And helped me push some of my first contributions into the quantum open source ecosystem! Thank you unitaryHACK ❤️"

Gregory Vargese, aka @WingCode, the participant with most hacks: 8 bounties completed. In the wrap-up party on Unitary Fund's Discord, all the three of them were featured in the community call, together with maintainers from PyQIR, QuTiP, Qiskit, Mitiq, Qrack, Toqito and many participants.

Janne Kotilahti, maintainer of KQCircuits at IQM, said that "it was great to get the first non-IQM contributions to KQCircuits. Looking forward to next year's unitaryhack!"

For Luciano Bello, maintainer of Qiskit at IBM, "Qiskit is a better project after unitaryHACK"

## Winners & Stats

30 projects from the quantum open source ecosystem participated in unitaryHACK 2022, with the support of over 45 maintainers. We had over 400 participants in unitaryHACK 2022. Over 73% of participants were either at their first quantum or open source event. Over 63 bounties were made during unitaryHACK 2022 by 27 hackers. More stats and graphics are below:

Leaderboard of the unitaryHACK bounty winners:

Completed bounties by project per users:

Completed bounties per participating project
Hackers per country

Once again, unitaryHACK would not be possible without the support of generous donors including Microsoft Azure Quantum, DoraHacks, Jens Koch, and Unitary Fund's members, including IBM, Accenture, Xanadu, IonQ, Boston Consulting Group, Pasqal, IQM, DoraHacks, and Agnostiq.

See you in 2023 with unitaryHACK and sooner on the Unitary Fund Discord server.

How to Run Programs on Quantum Computers for Free

Mon, 27 Jun 2022 00:00:00 GMT

The Unitary Fund team and Advisory Board often get asked this question: “How can I run programs on quantum computers?” Today there are a lot of options for free cloud-access to quantum computing services and we’ve taken a shot at summarizing some of the well known ones. If you know of platforms or programs that we have missed then please do reach out to [email protected]

IBM Quantum

IBM Quantum regularly releases free to access hardware on an a-la-carte selection of QPUs (although some get routinely decommissioned, such as the beloved ibmq-armonq, the first to provide pulse-level access). Many IBM Quantum QPUs are free to access, while some are only for partnerships. There are also special access programs for educators and researchers.

AWS Braket

AWS Braket is fully integrated in the AWS dashboard as one of its existing services and has many devices. It provides one hour per month of free credits for simulation but not yet a default mechanism to access QPUs or free credits for QPUs. They run a wider cloud credit for research program that includes quantum, although you need to be full-time in academia to apply. Unitary Fund obtained several credits by asking, so it is always worth trying to contact the Braket team.

Azure Quantum

Azure Quantum provides $500 free per each provider (IonQ, Quantinuum, etc.) upon signing in + more credits for approved research projects.

IonQ Credits

IonQ has a research credit program with the call closing soon, on June 30th 2022. Hopefully there will be more!

Quantum Inspire

Quantum Inspire is an initiative by TU Delft in The Netherlands. As far as I know, it is the only provider of quantum-dot-based spin qubits publicly available on the cloud, for free. The downside is that, last time I checked, they have sort of a cQASM interface that is not exactly OpenQASM. Plus, the devices can be off the grid for maintenance.

Xanadu

Xanadu recently launched free cloud access, upon sign-up form for Borealis, in conjunction with the publication of their results in Nature.

Adding Digital Dynamical Decoupling to Mitiq

Tue, 21 Jun 2022 00:00:00 GMT

The Unitary Fund team is excited to announce the addition of dynamical decoupling features to Mitiq, the open-source quantum toolbox in Python that mitigates errors of NISQ devices.

Dynamical decoupling is a technique originally developed at the pulse level and has been modified to work in the context of gate-based quantum computers in digital dynamical decoupling (DDD). The Mitiq community has designed and implemented this technique into it's own module mitiq.ddd.

Here is a sketch of how digital dynamical decoupling is applied in Mitiq.

Learn more in the documentation

You can find a lot of details about the actual use of this technique in Mitiq in the Users Guide part of the documentation, covering all about how to easily apply DDD, pros and cons of when to use this technique, what additional options are available when using DDD, what happens at the code level, and information about the theory behind DDD.

A Mitiq community achievement

The code design document was drafted by Aaron Robertson in collaboration with the Unitary Fund technical staff: Aaron is a Unitary Fund ambassador, and rightly so – thank you, Aaron!

The dynamical decoupling module has been deployed into Mitiq since version 0.16.0 and it marks a major milestone in the 2022 Mitiq Roadmap.

This is a reminder for everyone to join the Mitiq community calls, which are held weekly on Fridays at 6pm CET / 12pm ET on the Unitary Fund Discord.

unitaryHACK 2022: The Unitary Fund hackathon supporting quantum open source projects returns from June 3rd, 2022

Tue, 24 May 2022 00:00:00 GMT

Unitary Fund is glad to announce the 2022 edition of unitaryHACK, which will be hosted from June 3rd to June 17th, 2022.

UnitaryHACK is very different from the rest of the hackathon-style events in the quantum computing space because contributions support existing quantum computing projects, pay people for their work, and help build critical professional skills like working on OSS or quantum computing stack tools. We want this event to show folks what amazing projects are out there, and help you find new ways and people to help grow your projects. We have added to the webpage what you can expect before and during the event, as well as the rules for the event.

To get started with unitaryHACK, SIGN UP HERE

We have more than 24 participating projects and over 85 bounties! You can find the full list here, which includes:

Covalent
Error Correction Zoo
KQCircuits
Interlin-q
Metriq
Mitiq
Netket
PennyLane
QCOR
Quantum Universal Education
Quantify-Core
Quantify-Scheduler
quantumalgorithms.org
qiskit-nature
qiskit-terra
qunetsim
Toqito
QuTiP
Pulser
Yao.jl
Scqubits
Qrack
XACC

unitaryHACK is made possible by the maintainers volunteering time to review pull requests and engage with the community during Office Hours held on Unitary Fund’s Discord server.

unitaryHACK is supported by generous donations from Microsoft Azure Quantum, DoraHacks, Jens Koch, and Unitary Fund’s members, including IBM, Accenture, Xanadu, IonQ, Boston Consulting Group, Pasqal, IQM, DoraHacks, and Agnostiq.

Save the date for the kickoff party: June 3rd, 2022, at 9am PT / 12pm ET / 6pm CET we’ll kick off unitaryHACK 2022 on the Unitary Fund Discord server.

Unitary Fund launches Metriq

Tue, 17 May 2022 00:00:00 GMT

Unitary Fund is proud to announce a new open source software tool for the quantum computing community, at https://metriq.info!

Metriq’s mission is to make transparent, accessible benchmarks available to everyone in the quantum computing community.

With the growth of quantum computing in academia and industry, it can be hard to keep track of the many new developments. Metriq helps with this. Any user can (1) make submissions that show performance of methods against tasks and/or (2) define new tasks that results can be submitted against. For example see historical results for quantum volume, a task commonly used to benchmark hardware performance.

Check out this overview for a quick tour of Metriq:

The tasks in Metriq span different categories from applications and hardware to compilers, simulators and error mitigation/correction.

We believe it is important both to have new results as well as new tasks, because, in a space as new as quantum computing, we can’t be sure what the most useful benchmarks will be yet. This is why we have adopted a wiki-like approach, where users can submit, edit, and discuss the presented results.

Metriq already includes more than 150 submissions across quantum computing applications, compilers, hardware, simulators and more. Submissions are from researchers and developers across the quantum computing community. Results include sources and are openly accessible for free.

Metriq organizes benchmark information transparently, by and for the community.

The full source code of all components of Metriq app are free and public via the Unitary Fund GitHub organization, including web front end, REST API back end, and PostgreSQL database schema creation scripts. Code is provided under Apache License 2.0, and content is contributed under (Creative Commons) CC-BY-SA.

Metriq is endorsed by a growing group of partners from across startups, national labs, research groups, and deep tech investors including IQT Labs, USRA, RIKEN, the SQMS quantum research center, Cambridge Quantum, Strangeworks, Agnostiq, Super.Tech, Quantonation, and Unitary Fund.

If you would like to be part of supporting Metriq then reach out to: [email protected].

Whether you are a professional quantum hardware researcher, a quantum software developer, or a hobbyist eager to learn more about progress in the field, Metriq is free and open to community contributions. Come see how the latest quantum technologies measure up!

If you’d like to learn more or have help making a submission then reach out to us at [email protected].

QuTiP 2021 Annual Review

Mon, 11 Apr 2022 00:00:00 GMT

Earlier this year the QuTiP Admin Team conducted its annual review.

We happy to report that 2021 was a busy, productive and successful year for QuTiP with many new features, bugs fixed, contributions from the community, and, of course, lots of support from the Unitary Fund.

Individual sections of the report are linked to below:

And the full report can be found here.

In addition, 2021 was also QuTiP's 10th anniversary -- congratulations and thank you's to everyone who contributed to getting us where we are today, and here's to the next ten years!

Unitary Fund Q1 2022 Update: New projects, advisors and supporters!

Wed, 06 Apr 2022 00:00:00 GMT

To the Unitary Fund community,

We're excited to share our Q1 2022 quarterly update and highlight some of what UF's been involved with so far this year.

We continue to award new grants, update Mitiq, and add ambassadors, advisors, technical staff and even new members to our program! For more detailed information, have a read at our key highlights below.

As the year progresses, we remain committed to growing our support towards the quantum open source ecosystem. Thank you all for your continued support and being a part of our journey. Make sure to follow our Discord, Twitter,LinkedIn, and our [email protected]">Community Calendar.

Upcoming event: our quantum open source hackathon unitaryHACK 2022: Register Now!

New from Unitary Fund

Welcome Misty Wahl to the Unitary Fund Team! Misty will be joining

as Member of Technical Staff with a focus on Mitiq.
Two new Advisory Board members!
- Amira Abbas, PhD
  
  student at the University of KwaZulu-Natal and Quantum Research Advocate at IBM
- Stephen DiAdamo, Research Scientist at Cisco and author of the
  
  QuNetSim Python package (and fmr. Microgrant winner)
IBM and Accenture are some of our [[newest

additions]{.ul}](https://unitary.foundation/posts/2021-corporate-members.html) to our member program as Core Members. We thank IBM and Accenture and look forward to furthering our mission with their support.
Agnostiq has joined as a Unitary Fund

[Supporting Member]{.ul}. We're excited to work with Agnostiq and making a step towards creating a strong ecosystem, together with our other Supporting Members -- Xanadu, IonQ, BCG, Pasqal, IQM, and DoraHacks.
Congratulations to Victory Omole for

winning the [2021 Wittek Quantum Prize]{.ul} for his work on Google's Cirq library and other open-source projects.
Join us every other Thursday for [[QiR community calls on our

Discord]{.ul}](https://discord.gg/57nHcRS6CQ).
Mitiq
- We released version 0.12 through 0.13 of Mitiq (full
  
  changelog):
  - The 0.12 release contains a considerable overhaul of the
    
    documentation organization and content (special thanks to Misty Wahl and Purva Thakre!), [check it out]{.ul}.
  - The 0.13 release is compatible with the latest Cirq version
    
    and contains GHZ circuit support (special thanks to Rahul Mistri). Two design documents, on learning-based PEC and digital dynamical decoupling were approved, thanks to Misty Wahl and Aaron Robertson. Thanks @astrojuanlu for useful suggestions about readthedocs, as we improved the HTML display of notebooks.
- The [[2022 Mitiq
  
  roadmap]{.ul}](https://github.com/unitaryfoundation/mitiq/wiki#mitiq-2022-roadmap) has been discussed and approved
- We added a [[Projects
  
  Ideas]{.ul}](https://github.com/unitaryfoundation/mitiq/wiki/Project-Ideas) section for students who may want to collaborate.
- The Unitary Fund team, together with collaborators at Johns
  
  Hopkins, uploaded [a paper]{.ul} with a study on how to reduce the impact of correlated noise on zero noise extrapolation.
- The Unitary Fund team uploaded [[a
  
  paper]{.ul}](https://arxiv.org/abs/2203.05489) showing the improvement of effective quantum volume with quantum error mitigation, using Mitiq.

New Grants

To Ayush Tambd, secondary

school student and quantum enthusiast -- for developing HODL language designed to make it easy and intuitive to write arithmetic, relational, and logical operations for quantum programs: GitHub arXiv
To Steven Thomson, Marie

Skłodowska-Curie Fellow at Freie Universität Berlin -- for creating a new quantum technology podcast aimed at highlighting the diverse range of people who work in quantum technology.
Unitary Fund became a sponsor for the [[Quantum

Journal]{.ul}](https://quantum-journal.org/).

News from UF Projects

QuTiP has been accepted for Google Summer of Code 2022. Applications

for students open April 4th and close April 19th. Check out [current Project Ideas]{.ul}.
Blog: [[Implementing a Variational Quantum Algorithms module in

QuTiP]{.ul}](https://unitary.foundation/posts/vqa_in_qutip.html)
- QuTiP's qutip-qip package consists of classes QubitCircuit and
  
  Gate, which simulate the dynamics of quantum circuits. For VQAs, these gates should be parameterized. In addition to the gate parameters, initialization options, which are fixed throughout the optimization process, will be easily defined in one object. For these purposes, we define two new classes, VQABlock and VQA, which are abstractions on Gate and QubitCircuit, respectively.
[[Two papers on quantum open source software

projects]{.ul}](https://unitary.foundation/posts/pulser_qutip.html) supported by the Unitary Fund were published in the open-access, community-driven journal Quantum.
- The papers provide information on Pulser and qutip-qip, two
  
  Python packages for the pulse-level simulation of quantum programs on quantum computers.
Blog: [[OQuPy: Open Quantum Systems in

Python]{.ul}](https://unitary.foundation/posts/2022_oqupy.html): A Python 3 package to efficiently compute non-Markovian open quantum systems.
- Additions to the OQuPy package with hopes that they would
  
  further attract new users who might find some use of these in their own research.
  - Calculation of bath correlations from system correlations
  - Non-perturbative simulation of a system coupled to multiple
    
    environments

Coming up next quarter:

unitaryHACK is returning in June 2022: [[Register

Now!]{.ul}](https://airtable.com/shrJeycewBFqdot2B)
Boxi Li is giving a Quantum Software Talk on "*QuTiP qip:

Pulse-level circuits simulation"* this Thursday April 7th at 6pm CET / 12pm ET, on Unitary Fund Twitch channel
QuTiP is participating in Google Summer of Code 2022: Applications

are open until April 19th, find guidelines and project ideas here.
QCHack 2022 by the Quantum Coalition (Yale x MIT):

quantumcoalition.io

Unitary Fund welcomes Agnostiq as a new Unitary Fund supporting member

Thu, 31 Mar 2022 00:00:00 GMT

We are excited to share that <a href="https://agnostiq.ai/" target="_blank" class="highlight">Agnostiq</a> is now a part of our Corporate Member Program as a Supporting member!

<a href="https://agnostiq.ai/" target="_blank" class="highlight">Agnostiq</a> is an interdisciplinary team of physicists, computer scientists, and mathematicians with the shared aim of using cutting edge technology to build practical applications. They are already engaged in the quantum open source community with the open development of their project <a href="https://github.com/AgnostiqHQ/covalent" target="_blank" class="highlight">Covalent</a>, a workflow orchestration platform designed for quantum and high-performance computing.

“We need better hardware, better software and a strong collaborative community for quantum computing to succeed. Agnostiq’s partnership with Unitary Fund is another step towards building a strong ecosystem to build better software tools" said Ian Buckley, Community & Partnerships Lead at Agnostiq.

We're excited to move forward and further both of our missions together. To learn more about our new member program, email [email protected]">[email protected].

About Unitary Fund

<p class="leading-block"> Stay up to date with what Unitary Fund is working on by following us on <a href="https://twitter.com/unitaryfund" target="_blank">Twitter</a>, <a href="https://github.com/unitaryfoundation" target="_blank">GitHub</a>, and <a href="https://www.linkedin.com/company/unitary-fund" target="_blank">LinkedIn</a>!</p>

A Python 3 package to efficiently compute non-Markovian open quantum systems.

Mon, 14 Mar 2022 00:00:00 GMT

About Us

We are both PhD students (one recently finished) in the Keeling/Lovett groups at the University of St Andrews where our work has focused on building tensor network algorithms to simulate non-Markovian open quantum systems. We began developing the OQuPy package to open up these methods to a much wider audience by placing the complex algorithms behind a simple and intuitive interface. We applied to the Unitary Fund to help support the extension of OQuPy to include a few new tools for open quantum systems analysis recently developed in our groups. We'll get on to those but first a brief background on the key ideas.

About OQuPy

When an open quantum system is strongly coupled to a structured environment, describing the dynamics of that system becomes a challenging problem. Moreover, traditional approaches, based on time evolution of the reduced density matrix are generally not able to correctly calculate higher-order or multi-time correlations. In the past few years tensor network techniques based on an influence functional approach have been developed to address both these issues [1-5]. Here the tensor network representation is used to efficiently capture the non-Markovianity or "memory effects" that arise from the non-trivial coupling. This efficient representation lies at the heart of the OQuPy package and is what every module builds upon.

Extending OQuPy

Beyond the core functionality there have been a number of extensions developed in recent years that, while proven effective in published work, were relatively detached from the existing package and lacked a well maintained code base. Here we will focus on two of these:

Calculation of bath correlations from system correlations
Non-perturbative simulation of a system coupled to multiple environments

We decided to add these to the OQuPy package with hope that they would further attract new users who might find some use of these in their own research. The first of these allows further characterisation of the behaviour of an open quantum system by giving insight into the specific role of the environment which can become increasingly significant in cases of strong coupling. The second gives the user the possibility to account for strong coupling to multiple environments and examine the effect of their interplay on the system’s evolution. Thanks to the Unitary Fund we were able to support the implementation of these to OQuPy. We will now briefly cover the background to both these features and how they currently fit into the package.

Bath Dynamics

It has long been accepted that in simulating open quantum systems one must typically trace over the environmental degrees of freedom and thus lose access to the wealth of information contained in them. In the weak coupling limit this is of little consequence as we would generally expect the environment to be effectively stationary and not be doing much interesting. However, as the coupling is increased the role of the environment becomes increasingly significant. In this regime correlations can build between the system and environment which lead to complex behaviour in the system observable dynamics. When we trace over the environment in this case we are obscuring half of an intricate back-and-forth between system and surrounding. Fortunately, all is not lost. In fact it was shown in Ref [6] that, for a linearly coupled Gaussian environment, any correlation functions of the bath can be expressed purely in terms of the system correlation functions.

We have added a module bath_dynamics.py to the OQuPy package which currently contains a TwoTimeBathCorrelations class. This allows calculation of any second-order bath correlation function of a given model. Any necessary system correlation functions are computed and then stored for re-use on future bath correlation calculations. Check out this tutorial for a demonstration.

Multiple Environments

There are many processes in reality that can be modelled as a finite system coupled to independent baths. Quantum dots driven by an optical field often couple strongly to the vibrational degrees of freedom of their host material too. Looking to nature: photosynthetic complexes often display strong coupling between their electronic and vibrational degrees of freedom and of course are coupled as well to photons from the Sun. Were both baths coupled weakly then typically their effects on the system are treated additively, as if the the other bath didn’t exist. However, when either bath is strongly coupled this additive treatment can break down. When a quantum system is strongly coupled to a single bath it begins to make less sense to talk about them as distinct entities and rather consider hybrid excitations of correlated states between them. For example in light-matter coupling we may consider working in a polariton basis or similarly a polaron basis for strong electron-phonon coupling. When we introduce a second bath, even though independent from the first and potentially weakly coupled, it unavoidably interacts with the strongly coupled first bath via these correlated states. In Ref. [7] it was shown how we can extend the base algorithm to capture the non-additive effects of multiple environments.

This multi-environment feature was implemented in OQuPy with minimal adjustment of the existing code. One can simply follow the procedure for building a process tensor (as outlined here) of each environment and then submit them in a list to the compute_dynamics function.

Further and Future Extensions

Beyond the features covered above we recently added modules that allow the user to simulate chains of open quantum systems (each coupled to their own environment) by using tensor network representations to efficiently capture temporal and spatial correlations [8]. Further to this we hope to soon have a mean-field extension of TEMPO added where the number of degrees of freedom is reduced analytically through a supression of correlations between identical systems [9].

We sum up the current functionality of OQuPy in the following graphic:

If you have any questions or suggestion please don’t hesitate to get in touch and post an issue on GitHub!

References

[1] Strathearn et al., New J. Phys. 19(9), 093009 (2017).
[2] Strathearn et al., Nat. Commun. 9, 3322 (2018).
[3] Pollock et al., Phys. Rev. A 97, 012127 (2018).
[4] Jørgensen and Pollock, Phys. Rev. Lett. 123, 240602 (2019).
[5] Fux et al., Phys. Rev. Lett. 126, 200401 (2021).
[6] Gribben et al., arXiv:2106.04212 (2021).
[7] Gribben et al., PRX Quantum 3, 010321 (2022).
[8] Fux et al., arXiv:2201.05529 (2022).
[9] Fowler-Wright et al., arXiv:2112.09003 (2021).

Unitary Fund 2021 Annual Report

Mon, 14 Feb 2022 00:00:00 GMT

To the Unitary Fund community,

2021 was a year of rapid growth across quantum technology. Steady technical progress was matched with a completely new level of resources and funding for the space. The $2.5Bn+ invested in quantum computing companies just last year is more than the total across the previous decade combined. The vision for a robust quantum technology industry increasingly resonates with scientists, engineers, investors, and customers.

Still, there are challenges to overcome. New capital in our space must be deployed to fill gaps in the quantum ecosystem. We need to develop error correction, scalable hardware technologies, useful algorithms with provable advantages, ways to benchmark and project the performance of heuristic algorithms, and more. Some of these challenges are well addressed by academic and industry players. However, others are public goods that help everyone but that don’t stand alone as businesses. These are the open development tools, standards, benchmarks, interfaces, educational and training materials, skill-sharing networks, open source communities, mentorship networks and more that form the soil from which a rich industry and ecosystem can grow.

Unitary Fund helps build these crucial public goods.

These tools and communities lower the barrier to entry for new people and ideas. They form the ecosystem that companies will hire from and sell into. We believe that investment in public goods and open communities will get us both to a quantum tech future faster and to a future that benefits more people.

And we aren’t the only ones. Our supporters, advisors, grants winners, open source contributors, hackathon participants have all come together to form the growing Unitary Fund community.

I’m thrilled by the diversity of the talent that I get to work with across the community. From experts with decades of experience at the largest global companies to high school students to developing countries. I am inspired by the creativity and drive that I see everyday. It is a joy to share a passion for quantum technologies with all of you.

As you will see in the following pages of our annual report, we are growing rapidly and are excited for what comes next.

<p class="leading-block"> Read the full <a href="../../assets/Unitary_Fund_2021_Report.pdf" target="_blank">2021 annual report</a>.</p>

Thanks to all of you who have joined us in this mission.

William Zeng

President, Unitary Fund

Implementing a Variational Quantum Algorithms module in QuTiP

Wed, 09 Feb 2022 00:00:00 GMT

About me

I'm an undergraduate student at the University of Sydney, studying Physics and Computer Science. I've worked on a few quantum computing projects in the past and was really excited to be awarded a microgrant by the Unitary Fund to work on this project. My personal website is available at benbraham.com.

Background

Many groundbreaking quantum algorithms (e.g. Shor's, Grover's) require quantum computers with a large number of qubits and high fault-tolerance to produce useful output for non-trivial problem instances. While this is likely some time away, there exist algorithms that aim to leverage the current power of noisy intermediate--scale quantum (NISQ) systems. Variational Quantum Algorithms (VQAs) are a hybrid classical-quantum type of algorithm in which parameterized quantum circuits (PQCs) are optimized, with an objective function being evaluated on quantum hardware and the parameter update occurring on a classical machine.

One current area of interest in VQAs is that of the "initialization" for the algorithm. Problems are described by a quantum circuit, with its structure based on a circuit ansatz - usually inspired by the problem one wishes to solve. The performance of the algorithm is heavily influenced by the circuit structure, as well as the initial parameters of the circuit. It is therefore worthwhile to have the tools to test VQA formulations on a classical simulation of a quantum system, before expending time and resources to apply it on real quantum hardware.

QuTiP is a open-source python project for simulating quantum systems. In this project, I designed and wrote an implementation of a VQA module for QuTiP's qutip-qip package, which allows users to define and evaluate the effectiveness of VQAs on their local machines.

Module Overview

Most quantum algorithms deal with quantum circuits, which are made up of quantum gates. In QuTiP's qutip-qip package, there exist classes --- QubitCircuit and Gate --- which simulate the dynamics of quantum circuits.

For VQAs, we now want these gates to be parameterized. In addition to the gate parameters, we want initialization options, which are fixed throughout the optimization process, to be easily defined in one object. For these purposes, we define two new classes, VQABlock and VQA, which are abstractions on Gate and QubitCircuit, respectively.

1. The VQA_Block class

The VQABlock class encapsulates one component of our circuit and can store the action of one or more quantum gates. It can hold parameters, or keep note of how many free parameters it needs as input to be translated into a gate on the quantum circuit.

In quantum computing, all quantum gates can be described by unitary operators. Our VQABlock class has a method that will generate a unitary operator for the quantum circuit; but crucially, the value of this operator can change based on the parameters the VQABlock receives.

The VQABlock holds information about the operator it can generate, the parameters it needs, and methods to compute derivates of its operator. Using this information, the algorithm can compute gradients of its cost function. The optimization process is thus a loop in which VQABlocks are evaluated to inform the minimization of the cost of a circuit.

2. The VQA class

The VQA class holds information about the problem being optimized. It has methods to run optimization procedures with various options, such as the number of qubits required, the number of layers --- or repetitions --- of the circuit, and the optimization method to use. Here, we allow access to all of the function minimization methods available within the scipy library, as well as allowing user-defined optimization methods.

One part of the optimization process is specifying a "cost function" which the optimizer can use to assess the performance of a particular parameter set. In the case of a real quantum computer, the only output we have comes from taking measurements of the system. In quantum computing, these are usually represented as "bitstrings", which encode the measurement outcome. For example, the measurement outcome of a two qubit system with one qubit measured in the |0> state, and another in the |1> state can be represented by the bitstring |01>.

If the cost method is set to BITSTRING, then the user needs to provide a function that takes in this string of 1's and 0's, and returns the associated cost.

Because we're performing a quantum simulation, we don't just have to deal with measurements --- we can "peek under the hood" of the simulation to get more information, including the actual state of the system before measurement. With this, we allow two more methods for specifying a cost:

If the cost method is set to STATE, then the user can provide a function that takes in a quantum state and returns a cost.
If the cost method is set to OBSERVABLE, then the user can provide an observable and the cost becomes the expectation value of that observable in the final state of the circuit.

The VQA class stores a list of VQABlock instances, and can perform an optimization of their free parameters with a number of different options.

By allowing VQABlock instances to take more complicated structures and custom functions that generate their unitaries, we enable a range of quantum control problems to be approached within the framework of a PQC. One such abstraction is the Parameterized_Hamiltonian class, which can sit in a VQABlock within the circuit. On the side of the user, it's easy to define different types of VQABlocks with different methods for generating unitaries, and let the module decide how to compute gradients for you.

Below I have included a general example of how the module can be used, in which a combinatorial optimization problem is approached using a VQA.

Example

Here we will look at how one might implement a VQA in this module. To begin, we'll introduce the partition problem.

The partition problem asks if there is a way to partition a set of integers, $S = [s_0, s_1, \dots s_n]$, into two subsets $S1$ and $S2$ such that the sum of elements in each of these sets is equal. For example, the set $S = [1, 4, 3]$ can be partitioned into the sets $S1 = [1, 3]$, $S2 = [4]$. The optimization version of this algorithm asks for the partitioning that minimizes the difference in these two sums.

This problem is known to be NP-Hard, so there is no known efficient classical algorithm for solving it. One way of finding approximate solutions to this (although it is not yet clear if VQAs give a speed-up here), and other combinatorial problems is through a VQA known as the Quantum Approximation Optimization Algorithm (QAOA).

The QAOA gives us a circuit ansatz that we can use to approximate solutions to combinatorial problems. In general, if we can encode the solution to our problem in the ground state of a Hamiltonian, $H_P$, and we can pick another Hamiltonian, $H_B$, that doesn't commute with $H_P$, then our circuit takes the form:

$$ U(\beta, \gamma) = \prod^p _{j=0} \quad e^{-i\beta_j H_B} e^{-i \gamma_j H_P} $$

where each $\gamma_j$ and $\beta_j$ is a free parameter, and we repeatedly apply unitaries generated by $H_P$ and $H_B$, $p$ times.

We now need to work out how to encode our problem in terms of the ground state of a Hamiltonian. The cost of our solution is given by the difference of the sums of the two sets, i.e. sum(S1) $-$ sum(S2). As $S1 \cup S2 = S$ and $S1 \cap S2 = \emptyset$, this is equivalent to taking a weighted sum over $S$, where we assign a weight of $-1$ to elements partitioned into $S2$. We can describe this with the Hamiltonian

$$ H_P = \left(\sum_{s_i \in S} \quad s_i \sigma_z^(i) \right)^2 $$

where $\sigma_z$ is the Pauli $z$ operator, and the superscript indicates it acts on the $i$th qubit. Clearly the lowest energy state for this Hamiltonian corresponds to the partitioning of the elements of $S$ that minimizes the difference between sum($S1$) and sum($S2$). Now that we have encoded the cost minimization into the energy levels of a Hamiltonian, we're ready to translate our idea into code.

After defining our Hamiltonians as quantum objects (matrices with more bells and whistles) with QuTiP's Qobj class, we can define our VQA as follows:

This code has constructed a quantum circuit that looks as follows:

After calling the optimize_parameters method, we can plot the results of the optimization process in terms of the measurement outcome probabilities.

Here, we have passed in the label_sets parameter to the plot function, which labels measurement outcomes by their corresponding set partitioning of the problem instance.

There are many parameters to tweak here, such as the number of layers used, initialization conditions, the optimization algorithm parameters and constraints, as well as gradient computations. It is my hope that this tool allows anyone to dive straight into VQAs.

References

Other examples, including the max-cut problem examined in the original QAOA paper, can currently be found on my GitHub.

I opened an issue to discuss with the QuTiP admins how to best include these features into the main qutip-qip project codebase.

Future work

There are always possible optimizations and additions for a tool with this kind of scope. There have already been some great suggestions on the associated GitHub Issue for integrating this with other QuTiP tools, and when the pull request goes up, there will likely be more. Please feel free to contribute or join the discussion!

This project has laid the foundations for a very general set of tools to define VQA problems. The code written should be robust enough that expansions to allow more specific formulations are possible.

Acknowledgements

Throughout my work on this project, I've been privileged to have the supervision of A/Prof. Daniel Burgarth and Dr. Mattias Johnsson at Macquarie University.

Thanks to the Unitary Fund for supporting my project, and for all the advice and chats along the way!

Open Quantum Systems in Python (OQuPy)

Mon, 07 Feb 2022 00:00:00 GMT

When an open quantum system is strongly coupled to a structured environment, describing the dynamics of that system becomes a challenging problem. Moreover, traditional approaches, based on time evolution of the reduced density matrix are generally not able to correctly calculate higher-order or multi-time correlations. In the past few years efficient tensor network-based techniques based on an influence functional approach have been developed to address both these issues [1-5]. With the development of the OQuPy (Open Quantum Systems in Python) package we hoped to open up these methods to a much wider audience by placing the complex algorithms behind a user-friendly and intuitive interface.

Extending OQuPy

Calculation of bath correlations from system correlations
Non-perturbative simulation of a system coupled to multiple environments

We decided to add these to the OQuPy package with hope that they would further attract new users who might find some use of these in their own research. The first of these allows further characterisation of the behaviour of an open quantum system by giving insight into the specific role of the environment which can become increasingly significant in cases of strong coupling. The second gives the user the possibility to account for strong coupling to multiple environments and examine the effect of their interplay on the system's evolution. Thanks to the Unitary Fund we were able to support the implementation of these to OQuPy. We will now briefly cover the background to both these features and how they currently fit into the package.

Bath Dynamics

Multiple Baths

There are many processes in reality that can be modelled as a finite system coupled to independent baths. Quantum dots driven by an optical field often couple strongly to the vibrational degrees of freedom of their host material too. Looking to nature: photosynthetic complexes often display strong coupling between their electronic and vibrational degrees of freedom and of course are coupled as well to photons from the Sun. Were both baths coupled weakly then typically their effects on the system are treated additively, as if the the other bath didn't exist. However, when either bath is strongly coupled this additive treatment can break down. When a quantum system is strongly coupled to a single bath it begins to makes less sense to talk about them as distinct entities and rather consider hybrid excitations of correlated states between them. For example in light-matter coupling we may consider working in a polariton basis or similarly a polaron basis for strong electron-phonon coupling. When we introduce a second bath, even though independent from the first and potentially weakly coupled, it unavoidably interacts with the strongly coupled first bath via these correlated states. In Ref. [7] it was shown how we can extend the base algorithm to capture the non-additive effects of multiple environments.

Implementation

For the bath dynamics functionality we have added a module bath_dynamics which currently contains a single class: TwoTimeBathCorrelations. This allows calculation of any second-order bath correlation function of a given model. Any necessary system correlation functions are computed and then stored for re-use on future bath correlation calculations.

The multi-bath feature was implemented with minimal adjustment of the existing code. As such it is relatively easy to use but certainly could be optimised in future. One can simply follow the procedure for building a process tensor of each environment (as outlined here) then submit both as a list to the compute_dynamics function.

Further and Future Extensions

Beyond the features covered above a module was recently added which allows the user to simulate a chain of systems each coupled to their own bath by using tensor network representations to efficiently capture temporal and spatial correlations [8]. Further to this we hope to soon have a mean-field extension of TEMPO added where the number of degrees of freedom is reduced analytically through a supression of correlations between identical systems [9].

We sum up the current functionality of OQuPy in the following graphic:

If you have any suggestion for features you'd like to see then please don't hesitate to get in touch on our issues page!

References

[1] Strathearn et al., New J. Phys. 19(9), 093009 (2017).
[2] Strathearn et al., Nat. Commun. 9, 3322 (2018).
[3] Pollock et al., Phys. Rev. A 97, 012127 (2018).
[4] Jørgensen and Pollock, Phys. Rev. Lett. 123, 240602 (2019).
[5] Fux et al., Phys. Rev. Lett. 126, 200401 (2021).
[6] Gribben et al., arXiv:2106.04212 (2021).
[7] Gribben et al., PRX Quantum 3, 010321 (2022).
[8] Fux et al., arXiv:2201.05529 (2022).
[9] Fowler-Wright et al. arXiv:2112.09003 2021.

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Unitary Fund Announces New Support through New Membership Program

Mon, 31 Jan 2022 00:00:00 GMT

Since 2018, Unitary Fund has supported the open quantum technology ecosystem around the world. We’ve awarded more than 50 microgrants to projects from more than 20 countries, developed the leading error-mitigating quantum compiler, run hackathons, and supported open source community building.

Today, Unitary Fund is proud to announce our new corporate member program. We thank these organizations for their support and look forward to their further contributions in the coming year.

The corporate member program contributes to Unitary Fund’s work on a recurring, annual basis, and consists of two tiers: Core members and Supporting members. Core members are a part of the Unitary Fund’s Strategic Board which reviews strategy, budget, impact, and recommendation’s quarterly.

“The backing from these important members of the quantum ecosystem emphasizes the importance of our programs and the shared goals we all have in realizing the potential of quantum technology,” said Will Zeng, President of Unitary Fund. “There’s lots more work to do and we welcome new support!”

Unitary Fund Core Members: IBM and Accenture

“Our support of Unitary Fund is an important part of IBM’s effort to develop an open ecosystem around our Qiskit software, community and quantum computing platform” said Liz Durst, Director, IBM Quantum & Qiskit Community.

“Helping talented individuals with the opportunity to advance their innovative ideas is a core part to growing the quantum ecosystem. We are especially excited to enable underrepresented entrepreneurs through the Unitary Fund as part of our Corporate Citizenship efforts,” said Carl Dukatz, Accenture Quantum Program Lead. “Additionally, Accenture has a long history of contributing to open-source and is glad to work with the Unitary Fund to create the important foundations for quantum.”

The Unitary Fund awards $4,000 grants to individuals and teams pursuing projects that leverage quantum technologies to benefit humanity. The program is unique in its inclusivity (no credentials are required to apply) and low friction (awards are no-strings-attached).

Unitary Fund Supporting Members: Xanadu, IonQ, BCG, Pasqal, IQM, and DoraHacks

"It was important for Pasqal to reaffirm its support to open-source initiatives in quantum software by becoming a sponsor of Unitary Fund” says Loïc Henriet, Chief Technology Officer of Pasqal, a French startup building quantum processors out of neutral atoms. “We are thrilled to join the efforts led by Unitary Fund to build a solid ecosystem in this field."

"We are delighted to support the Unitary Fund's mission. They are doing first-class work building out a quantum ecosystem for everyone. You can see the Unitary Fund's impact everywhere you look," said Nathan Killoran, Head of Software, Algorithms, & Quantum Machine Learning at Xanadu, a photonic quantum computer company in Canada.

To learn more about our new member program, email [email protected].

About Unitary Fund

Meet the UF Ambassadors – Andre Alves

Tue, 25 Jan 2022 00:00:00 GMT

Having a somewhat unorthodox background, my introduction into the quantum computing space actually began with a TikTok video. Like any other computer engineering student in their mid-30s stuck at home during a pandemic lockdown, the app seemed like a fun way to pass some boredom. I was later introduced to Unitary Fund through my participation in the Quantum Open Source Foundation's Quantum Mentorship Program, where the project I chose to undertake was to make a meaningful contribution to Unitary Fund's error-mitigation toolkit Mitiq.

Discovering Quantum Computing

After walking across Spain trying to decide what to do with my life during the winter of 2019, I decided to move to Germany to go back to university for a career change. I had just resolved that I would abandon a failing business venture, and the idea of going back to school to return to working on technical topics seemed like the perfect next life step for me. My first bachelor's degree in physics was more than 12 years old, and I never actually used it. Instead, my degree tended to just fulfil the requirement of me having a bachelor’s degree to start each job I took.

Fast-forward one tuition-free semester spent studying information engineering, and the COVID-19 pandemic was coming into its own, leading to a lot of time stuck indoors. (For those who do not know, most university programs in Germany are tuition-free, even for foreigners, and many are in English. I do not speak German.) For a curious student like myself, the first lockdown was a perfect opportunity to explore my interests and get involved with whatever projects seemed like a fun way to spend my spare time. Building keyboards and designing custom printed circuit boards (PCBs) became a special interest for a while, but it seemed to quickly get expensive.

Eventually, I stumbled upon a TikTok video talking about quantum computing. Having heard of the topic before but not knowing much about it, I took advantage of my free time and looked into this emerging and exciting field that seemed like the perfect way to combine my earlier education in physics with my current education in information engineering. Information engineering is a combination of computer science and electrical engineering, and it is referred to as computer engineering in many places.

Since I first started learning more about it, I have been hooked on quantum computing. While possibly over-hyped and over-promised by the media, the future impact this field of computing will likely have remains significant. I liken it to having the opportunity to get involved in learning about classical computing in the 1950s when computers consisted of mammoth, building-sized machines that could accomplish relatively little compared to what we now think of and associate with a computer. But the major difference between then and now is that in the 1950s, most people did not have access to those computers. Meanwhile today, anyone with a laptop and an internet connection can not only learn about quantum computing, but they can even run code on real quantum hardware for free!

Getting Involved with Unitary Fund

I participated in the third cohort of the Quantum Open Source Foundation's Quantum Mentorship Program, where my mentor Tom Lubowe suggested making a contribution to Mitiq as a good project for me. To apply for the mentorship program, QOSF required applicants to choose a challenge from a list of options and submit their unique solution along with their application. Consequently, I built a small, Python-based quantum simulator. Although I had already learned to code in C and Java, that simulator was my first Python project and the vehicle by while I learned that programming language, which I have since used for several open-source contributions as well as work, school, and personal projects.

Once I started attending the weekly Mitiq meetings (every Friday at 17:00 UTC on discord) to understand what was going on, I was amazed at the open and welcoming community I found at Unitary Fund. Along with that sense of community, following along during the meetings helped me understand what were priority issues, and I decided to tackle creating decorators for PEC, a quantum error mitigation technique available in Mitiq. Decorators already existed for ZNE at the time, so this task was essentially making it so users could have the same or similar options for how to implement both techniques within their programs. In addition to that contribution, I made a few others that were mostly focused on organizing testing and improving documentation.

While I was working on my contributions to Mitiq, I found out about Unitary Fund’s Unitary Hack 2021 quantum hackathon and started learning about what other projects existed. Having done a bunch of work with networking back when I was in the military, QuNetSim, a quantum-enabled network simulator, caught my eye. As part of the hackathon, I improved the template used to generate a default network, and I improved upon and expanded another hacker’s contribution to automatically generate standard topologies.

Current Projects

I have a habit of overextending myself and getting involved in too many simultaneous projects. Now is no different! My current academic semester which is soon wrapping up has been spent in a full-time software engineering internship, and I thought I would have way more spare time than I have had. As a result, my progress on my current projects is moving forward at a snail’s pace, but I slowly continue to working on them all. My biggest problem is that everything within the field seems exciting to me, so I keep taking on additional projects before I have a chance to finish the previous one. But with my graduation about a year away, my simple goal is to complete all of these before I earn my degree.

Work Project

Luckily for me, I was able to find a quantum computing project within the company where I currently work, and I convinced my supervisors to assign me to it. As a result, for the last two months of my internship, I have been tackling the conventional full-stack development behind that webapp. While it will be made publicly available later this year, my employer is submitting a patent for the project's backend, so I cannot get into its details. But I can say my time has been spent working with ASP.NET, C#, and Vue.js, which have all been new to me, and I am very excited for when this project is released to the public.

Quantum Comparator Circuit / Random Number Generating

Spooky Manufacturing designed a quantum random number generator that makes use of a laser, polarized beam splitter, photoresistors, and an Arduino-compatible microcontroller. I loved their idea, which is based on comparing two voltage signals and choosing the higher one. But I believe by eliminating the comparison step, which required an analog-to-digital conversion, the same thing can be done faster! So, I had an idea to improve their design by building a quantum-based comparator circuit where phototransistors can be used in such a way where when one electrical path opens, it shorts out the other path. I also want to use an FPGA to receive the signal, since that will be much faster than a general-purpose microcontroller.

Building this device is obviously a multi-step process, and I am currently at the circuit-proof-of-concept stage. At this point, I have designed and conventionally simulated the circuit. When I get back home in mid-February, I will order the necessary components, build it, and test it out. If the circuit works as I imagine, the next step will be to program an FPGA to work with the incoming signal. The final step will be to put it all on a small printed circuit board (PCB) that can interact with another electrical device, hopefully by USB. Depending upon a number of factors, I am considering approaching some of my professors with this idea as the basis for a bachelor’s thesis project later this year.

As an aside, drawing the circuit using CircuiTikZ required creating a laser diode component, since that was not part of the package, yet. The component is now a part of the official CircuiTikZ release.

Study Bank for Qiskit Certification Test

Anyone who has spent some time in the quantum computing space has surely come across Qiskit, IBM’s open-source quantum computing software development kit. I recently became an IBM Certified Associate Developer – Quantum Computation using Qiskit v0.2X, which obviously required studying. Along with a more thorough study guide, IBM published a 20-question sample test, but while the question bank provides a list of correct answers, it does not offer any explanations for those answers. So as a study aid for myself, I created a JupyterLab answer bank for that sample test. The JupyterLab not only gives the correct answer, but it also explains each question, explains why each potential answer is right or wrong, and provides links to references for each question. I hope to improve the explanations and references with time, as well as potentially expand the lab and add more questions

QuNetSim Graphical User Interface

During Unitary Hack 2021, there was an open issue tied to a bounty that involved creating a user interface for QuNetSim. I got in touch with QuNetSim’s creator and Unitary Fund micrograntee Stephen DiAdamo about what he had in mind for such an interface. While it was outside the scope of what I could accomplish during the hackathon, I pitched my friend and UI/UX designer Frances Poblete to help design the UI, and she agreed. Her design looks great, and the prototype will form the basis for building the UI.

While I have not found the time to dedicate to improving my front-end development skills during this last semester, I still plan to be a major contributor to this UI as it gets built later this year.

<p class="leading-block"> Stay up to date with what Andre is working on by following him on <a href="https://github.com/andre-a-alves" target="_blank">GitHub</a> and <a href="https://www.linkedin.com/in/andre-a-alves/" target="_blank">LinkedIn</a>! </p>

Stay on the pulse of open-source quantum simulation with Pulser and QuTiP

Mon, 24 Jan 2022 00:00:00 GMT

Today two papers [H. Silvério & S. Grijalva et al., B. Li et al.] on quantum open source software projects supported by the Unitary Fund are published in the open-access, community-driven journal Quantum. The papers provide information on Pulser and qutip-qip, two Python packages for the pulse-level simulation of quantum programs on quantum computers.

Pulser is a software for controlling and simulating neutral-atom quantum processors. It enables users to control the arrangement of qubits in arbitrary geometries on Pasqal chips and to write sequences of laser pulses to be applied on the system. A custom emulator relying on QuTiP is included to reproduce the expected behavior of the hardware. The Pulser manuscript can be found here.

An example of a pulse sequence for Bell state preparation created in Pulser. Each channel changes its target qubit along the sequence and is populated with pulses addressing a specific energy transition, thus executing the necessary quantum gates. A detailed explanation can be found in section 3.2 of the Pulser paper. H. Silvério & S. Grijalva et al. Quantum 6, 629 (2022).

"We set out to develop Pulser based on the conviction that neutral-atom quantum devices can only be fully put to use when the programmer has hardware-specific knowledge and control. We are very proud to have created an open-source tool that enables anyone to program and simulate neutral-atom devices. Particularly, it opens the door to using the devices as quantum simulators and analog quantum computers, giving users the power to go beyond the quantum circuit model." said Henrique Silvério, head of the Quantum Libraries team at Pasqal and the main developer behind Pulser.

The second paper illustrates the possibility to simulate noisy quantum processors with the qutip-qip package from the Quantum Toolbox in Python. It bridges the gap between the gate-level circuit simulation and the simulation of quantum dynamics following the master equation for various hardware models. Provided a Hamiltonian model and a map between the quantum gate and control pulses, it can be used to compile the circuit into the native gates of a given hardware, generate the physical model described by control pulses and use QuTiP's dynamical solvers to obtain the full-state time evolution.

The QuTiP QIP manuscript can be found here.

Figure 3 from B. Li et al., Quantum 6, 630 (2022).

Celebrating quantum open-source software contributors: Announcing the 2021 Wittek prize winner with QOSF

Fri, 21 Jan 2022 00:00:00 GMT

Unitary Fund is glad to announce the 2022 edition of unitaryHACK, which will be hosted from June 3rd to June 17th, 2022.

To get started with unitaryHACK, SIGN UP HERE

We have more than 24 participating projects and over 85 bounties! You can find the full list here, which includes:

Covalent
Error Correction Zoo
KQCircuits
Interlin-q
Metriq
Mitiq
Netket
PennyLane
QCOR
Quantum Universal Education
Quantify-Core
Quantify-Scheduler
quantumalgorithms.org
qiskit-nature
qiskit-terra
qunetsim
Toqito
QuTiP
Pulser
Yao.jl
Scqubits
Qrack
XACC

unitaryHACK is made possible by the maintainers volunteering time to review pull requests and engage with the community during Office Hours held on Unitary Fund’s Discord server.

Save the date for the kickoff party: June 3rd, 2022, at 9am PT / 12pm ET / 6pm CET we’ll kick off unitaryHACK 2022 on the Unitary Fund Discord server.

A Bird's-Eye View of Upcoming System-Level Quantum-Classical Compilers

Thu, 13 Jan 2022 00:00:00 GMT

As quantum computers mature, software systems for compilation and control will necessarily need to improve in order to enable the full performant capabilities of a heterogeneous quantum-classical compute node. We envision the need for system-level compiler toolchains akin to those we have today for classical computing --- extensible, modular systems with unified intermediate representations that enable a wide array of optimization and code-generation techniques. What is the current state-of-the-art for system-level quantum compiler technologies today, and how is the quantum computer science community organizing to deploy these novel, next-generation software systems? In this blog post, I hope to answer that question and specifically highlight two recent developments that leverage the software infrastructure from the LLVM ecosystem --- the Quantum Intermediate Representation (QIR) and the MLIR Quantum Dialect. These two projects represent the latest with respect to deploying familiar, open-source, system-level compilation toolchains for quantum-classical computing today.

Community Efforts on Quantum Compilers

Any compilation toolchain starts with the definition of a robust intermediate representation (IR) that languages can lower to and that can be further lowered to native code for a wide array of compute backends. There have been a number of recent community-wide efforts focused on the design and implementation of quantum IRs for future compiler technologies. One effort that is important to highlight is the Practical Intermediate Representation for Quantum Computing (PIRQ) working group within the broader Quantum Economic Development Consortium (QED-C). The PIRQ effort has brought together researchers from across industry, academia, and the national laboratories to discuss the concrete requirements and recommendations for any future robust, extensible, and unified intermediate representation for quantum computing. The working group hosted a multi-day workshop in July of this year bringing together interested parties from across the quantum computing landscape to demonstrate currently available approaches and distill and discuss common features and requirements. The usual feature requirements were discussed --- things like mapping available language approaches to any desired quantum backend. More subtle features also came to the forefront throughout participant demonstrations and discussions - the need for an adaptable and fungible IR that could describe multiple layers of quantum language abstraction, and the need to ensure integration with existing classical compiler infrastructures, like the LLVM. These unique features were actually demonstrated by a number of independent institutional approaches, thereby highlighting their unique and innate value.

Concurrently, on the topic of LLVM for quantum computing, another community effort has arisen that seeks to bring together researchers across industry, government, and academia to define a concrete specification for a quantum-classical runtime API at the LLVM IR level of abstraction. The QIR Alliance (here, QIR stands for Quantum Intermediate Representation) is a new open source community within the Linux Foundation that seeks to develop forward-looking quantum-classical intermediate representations in order to enable full interoperability within the quantum software ecosystem. This organization has a special focus on enabling a QIR at the LLVM IR level, as well as supported tooling around this unified representation. Currently, the organization hosts an LLVM based specification for quantum computing (more on this in the next section), tools and python bindings for generation, optimization, and transformation of this IR representation, and the QCOR C++ compiler, which has put forward compiler tools that lower OpenQASM 3 to the QIR. This organization and the work that it has proposed has garnered broad support from the community, and as of this writing, Microsoft, Oak Ridge National Laboratory, Quantinuum, Rigetti, Quantum Circuits Inc., and NVIDIA are all involved and contributing.

LLVM-based Quantum Intermediate Representations

Let's first focus on work being done to enable quantum integration within the LLVM. As noted above, a specification has recently been proposed that enables integration of common low-level quantum computing intrinsic operations (quantum register allocation deallocation, qubit addressing, instruction/gate invocation, etc.) at the LLVM IR level. The Quantum Intermediate Representation (QIR), put forward by researchers at Microsoft in collaboration with partners from industry and the national laboratories, represents a concrete API specification defined at the LLVM IR level for common quantum computing tasks. The QIR specifies the declaration and signature of external runtime library functions that perform low-level quantum operations. Moreover, it defines opaque types for qubits, measurement results, and general arrays, thereby allowing runtime library implementations of the QIR to concretely specify the internal structure of these types.

To make this all a bit more concrete, here’s an example for the creation of a simple two-qubit Bell state: <script src="_markdown/snippets/bell_ll.js"></script>

The specification declares functions for common operations related to quantum-classical computing. The above example demonstrates how we have functions for allocating qubits as an opaque array of opaque qubit types, as well as functions for addressing those qubit instances and performing quantum and classical operations on them. All that is required is that an appropriate implementation of this library API is specified at link time. Implementers are free to provide these functions in a way that best fits their needs. Therein lies the extensibility of this approach --- QIR is a unified representation that can enable execution on any platform via an appropriate link-time specification of a QIR runtime library implementation. Moreover, its power and utility derives from its natural extension of the LLVM IR. It retains the entire LLVM software toolchain and ecosystem --- many languages lower to the LLVM, linking QIR implementations is readily available at the command line, and transformations on the QIR LLVM instances can be done through routine LLVM passes and its corresponding pass management system. The QIR does not natively extend the list of provided LLVM IR Instructions (a notoriously difficult task requiring a complete fork, and future maintenance, of the system), but instead expresses quantum functionality as a declared, yet not implemented, runtime library API. With the QIR, the broader quantum computing community has started to define a common, unified compiler representation for quantum programs that high-level languages can target, can be optimized and generally transformed via routine pass implementations, and can ultimately be lowered to executable code targeting vendor-provided quantum computers.

Of course, the Bell state is not a super illuminating example demonstrating the true utility of embedding a quantum-classical IR within the LLVM. The true utility of the LLVM is found in its wealth of existing classical control flow utilities and IR passes that analyze and simplify the code to make it more efficient. Check out the example below where we have a 15 qubit GHZ state coded up in OpenQASM 3, leveraging typical classical control flow: <script src="_markdown/snippets/ghz_ctrl_flow.js"></script> Notice we have the same QIR specification operations on opaque qubit and array types, but that the loop has been succinctly expressed using standard classical LLVM instructions, specifically the phi node and branch statements. This is what we mean when we say don't reinvent the wheel for the classical side of quantum-classical compilation. There is a wealth of existing compiler IR technologies that are open and can be leveraged in the definition of a hybrid IR for quantum computing. Moreover, by building upon LLVM, we pick up classical optimization passes for free. For example, in the above loop, we know that there are a constant number of iterations (14). The LLVM IR Pass system has various implementations that can detect something like this and unroll the loop. By turning these passes on with -O3, we see the following simplified QIR code: <script src="_markdown/snippets/ghz_ctrl_flow_opt.js"></script> This type of optimization is nice in the NISQ era, the above code could be easily transpiled to the native gate set and assembly input for any of the publicly available quantum computing architectures.

Multi-Level Quantum IR

The second feature highlighted from broader community discussions is the notion of requiring multiple levels of IR abstraction for the typical quantum-classical computing compilation pipeline. The QIR represents just one level of abstraction in the compiler lowering pipeline, and it is really the lowest machine level before necessary transformation to analog pulses for physical control of the quantum computer. There are, of course, other layers of abstraction, specifically those that may sit closer to the programmer and the language being used. Oftentimes, compiler optimizations may be better suited for language-levels of abstraction, where more of the original intent and semantics are still expressed. Moreover, multiple levels of IR abstraction can provide a mechanism for efficiently mapping languages to object code via the LLVM-based QIR. In other words, can we provide a robust and pre-implemented infrastructure that makes it simple to lower languages through multiple levels of IR abstraction to something at the quantum-classical machine level like the QIR?

Recent work has begun to tackle these challenges via a novel classical compiler IR framework called the Multi-Level Intermediate Representation (MLIR). The MLIR promotes a flexible approach to defining compiler IRs as well as a system for progressive lowering of one IR abstraction layer to lower ones. With this approach, you can define a language-level IR incorporating the unique semantics of the programming language, perform language-specific optimizations, and then take that representation down to lower level IR abstractions like the LLVM machine-level IR. If you can lower down to the LLVM IR, then you can readily generate executables and object code with the existing LLVM toolchain.

The MLIR has been recently extended to support quantum computing language features via a new dialect implementation contributed to the QCOR C++ compiler from ORNL (in the MLIR, a dialect is a collection of language-IR-specific operations). This dialect defines operations that are close to typical features present in available quantum languages, and most importantly, defines the translation mechanism necessary for translating that MLIR dialect representation down to the LLVM IR in a manner that is adherent to the QIR specification. Moreover, since dialects in the MLIR are modular components, we are free to leverage existing dialects for classical control flow, variable declarations and allocations, and function declaration and implementation. One truly gets a hybrid quantum-classical IR with the ability to optimize and lower to a QIR representation. In this way, as seen in Figure 1, prototyping new quantum-classical language compilers amounts to mapping language parse or abstract syntax trees to the quantum-classical MLIR representation, and then leveraging the existing infrastructure to lower down to executables and object code.

Let's demonstrate this workflow with the GHZ code again, but this time with a bit of added complexity --- specifically, we'll pull out the controlled-not operation into its own subroutine and add classical variable declarations. Moreover, we'll add in some X gates that should all effectively cancel out, and that any good compiler should be able to detect and throw away. <script src="_markdown/snippets/mlir_ghz_qasm.js"></script> In order to lower a language like OpenQASM 3 (or any other quantum language) to the QIR, one simply has to map the language parse or abstract syntax tree to an MLIR representation leveraging the newly developed Quantum Dialect in tandem with pre-implemented classical dialect operations. This MLIR Quantum Dialect, as well as the rest of the infrastructure that performs quantum-classical optimizations and progressively lowers down to the LLVM, is provided by the open-source QCOR project. <script src="_markdown/snippets/mlir_ghz_mlir_code.js"></script> You’ll notice in the MLIR representation that one can define classical variables and leverage typical control flow structures like loops and conditionals, and that stand-alone functions can also be declared and defined. The great thing about this representation is that the language level semantics are retained, and quantum and classical optimizations can be applied. Specifically, not that all quantum operations consume a quantum.Qubit value, and produce a new quantum.Qubit value. This feature allows one to effectively map out value use-define chains that provide key insight into how quantum data flows through the IR nodes. This data flow enables one to pick out common patterns efficiently, specifically those patterns that are common circuit optimizations. For example, the extra X operations introduced present a use-define pattern whereby an X gate consumes a qubit and produces another qubit value, which is then consumed by another X gate operation. This pattern can be easily searched for by the compiler and the operations can be thrown away. Moreover, by applying common classical optimization passes first, like function inlining, we can optimize these quantum gates away across loop boundaries. <script src="_markdown/snippets/mlir_ghz_opt.js"></script> Employing available classical optimizations and using pattern recognition on qubit data flow to pick out quantum circuit optimizations, we arrive at the above code snippet ghz_opt. Notice that the loop has been unrolled, functions inlined, and all unnecessary quantum operations have been removed.

<script src="_markdown/snippets/mlir_compile_bash.js"></script> After lowering this MLIR instances down to the LLVM IR adherrent to the QIR, one can readily generate executable object code. All that is left to do is link to any library that implements the QIR specification. The QCOR project provides one that delegates to the XACC framework, thereby enabling this simple GHZ code to run on IBM, Rigetti, IonQ, and Honeywell physical architectures, as well as a wide-array of simulators. As seen in the above shell commands, one simply specifies the backend to target (cuQuantum SDK, IBM physical backend, etc.) and the above lowering workflow takes the OpenQASM 3 code down to a hybrid quantum-classical binary executable.

Conclusion

These are early days to be sure, but we are seeing improvements in quantum hardware implementations with regards to things like lower noise, processing longer depth circuits, and tighter CPU-QPU integration and fast feedback and control. It is time to begin thinking about compiler architectures that enable performant interplay between quantum and classical resources. It is equally important to understand how quantum compilation strategies fit into the broader classical compilation pipelines in use today. Quantum computers are likely to work in tandem with classical computing resources, and it is important to design IR and software infrastructures that are ultimately integrable with classical workflows. Here we have provided a high-level view of recent work enabling such a performant compiler toolchain, and specifically how the community is beginning to leverage classical frameworks like LLVM and MLIR for future quantum-classical compiler integration. There is much to be done and these approaches are innately designed to be extensible, fungible, and modular, so that as quantum computers advance, so too can our compiler software ecosystems.

Get Started with the Concepts in this Blog

If anyone would like to quickly get up and running with these next-generation system-level quantum compiler technologies, we've put together a Docker image with the examples described in this blog post. To try it out, run the following

docker run -it qcor/cli-unitary-blog bash

Within the container, lower to MLIR and QIR, and build quantum-classical executables: <script src="_markdown/snippets/unitary_docker.js"></script>

<p class="leading-block"> If you'd like to connect with Alex and learn more about the work in this blog, check out his <a href="https://www.linkedin.com/in/alex-mccaskey-17a35636/" target="_blank">LinkedIn</a> and <a href="https://github.com/amccaskey" target="_blank">GitHub</a> profiles!</p>

Unitary Fund Q4 2021 Update: New projects, hires, and open roles!

Mon, 10 Jan 2022 00:00:00 GMT

To the Unitary Fund community,

Hope that you all are having a welcome start to 2022. In this quarterly newsletter we'll take a look back at some highlights from the last quarter of last year.

In addition to new grants and updates to mitiq, we're proud to have enabled, together with QOSF, the 2021 edition of the Wittek Prize. Look out to hear about the winner soon!

Also be on the lookout for our 2021 Annual Report, which will summarize updates from our programs and community from the whole of last year.

We continue to work hard to support the development of a vibrant, open quantum technology ecosystem. Thanks to all of you who have joined us in this mission.

New from Unitary Fund

Staff additions Alwoina Yap and Frances Poblete have joined the Unitary Fund team to help us improve and scale our marketing and communications reach.

Mitiq: We released version 0.11.1 of Mitiq, adding PennyLane support. The Mitiq integration with PennyLane is featured on the PennyLane blog! Andrea Mari gave a recorded Qiskit Seminar on Mitiq.

Our paper on extending probabilistic error cancellation got published in Phys. Rev. A. (arXiv:2108.02237).

We hosted two Quantum Software Talks (check out the videos, the talks are great!):

Pedro Riveiro spoke about QRAND, a library for quantum
The PyGSTi team spoke about this Python tool for noise > characterization

We attended Q2B with a booth and a talk by Sarah Kaiser. Thanks to our ambassador Misty Wahl who also volunteered to attend and represent Unitary Fund!

Sarah Kaiser is a 2021 Python Software Foundation Fellow.

New Grants

To Lingling Lao, to develop 2QAN, a compiler that optimizes quantum circuits for 2-local qubit Hamiltonian simulation problems. [arXiv]
To Ben Braham, to develop a framework to define and run variational quantum algorithms in QuTiP, leveraging quantum optimal control to parametrize control pulses.
To Hoang Van Do, Elie Gouzien, and Saesun Kim to develop a Heisenberg-picture simulator and universal gate set for high dimensional systems.
To Abuzer Yakaryilmaz and the QWorld team to organize QCourse511, a graduate-level online course on quantum computing and programming.
To George Watkins, Alex Nguyen, Varun Seshadri, and Keelan Watkins to further develop a lattice-surgery-based quantum error correction compiler.

News from UF Projects

QuTiP held its first community call, with Google Summer of Code projects. Videos can be found here.
PennyLane community calls are now being hosted weekly on our Discord.
The KnowYourLimits project, OSS for the assessment of noisy, limited connectivity quantum devices for optimization, by Daniel Stranca is out with docs.

Coming up in 2022

QuTiP community meeting: 26th of January 2022. 2pm-3pm CET, discord.unitary.foundation
QHack 2022 is coming February 14-22, 2022! Applications are open.
In 2022, we are resuming the Quantum Software Meetups with the folks from QOSF, on Gather Town.

Best wishes to all of you,

Will and the Unitary Fund Team

A Krylov Approximation Method for Quantum Evolution

Wed, 17 Nov 2021 00:00:00 GMT

<p class="leading-block"> This post was originally published on <a href="https://medium.com/@julian.ruffinelli/krylov-approximation-method-for-quantum-evolution-148b3f023ec4" target="_blank">Medium</a>, and is being syndicated here. </p>

Laboratories around the world are in the race to develop increasingly accurate quantum devices. To carry out this successfully, it is necessary to compare quantum devices against classical devices. For this reason, it is important to have efficient classical algorithms to perform quantum simulations. Krylov-subspace methods approximate the exponential of a matrix on a vector. For quantum simulation, the mechanics of the approximation are the following. An initial state in a (possibly very) large Hilbert space is first mapped to an effective subspace, the Krylov subspace, that captures the most relevant features of the dynamics. Within this low-dimensional subspace, time evolution is (cheaply) computed. Finally, the evolved state is mapped back to the large Hilbert space. Besides quantum simulation, the method has other important applications like solving systems of ordinary differential equations ref, large-scale linear systems, finding the best dimension for PCA ref, and more.

The physics of Krylov-error: Loschmidt echo approach

The evolution in the effective subspace is determined by a tridiagonal matrix; this type of system is equivalent to a tight-binding model with random hopping probabilities. The initial state starts at one end of the chain and starts to propagate throughout the sites. The approximation comes from cutting off the chain at one site. Now the error in the method is nothing but the Loschmidt echo between evolving forward with the full chain and backward with the cut version.

This view of the problem makes it clear that the error will grow when the wave function starts to populate the site after the cut. The details of this analogy and how it is used to determine the error bound is discussed in our research paper https://arxiv.org/abs/2107.09805.

Error bounding and efficient iterations

One of the biggest problems with this type of method is the control of the error. After a short time, the error starts to grow exponentially. For the method to be useful one must restart the subspace when the error reaches a certain threshold. With this in mind, tight error estimation becomes crucial. If the bound overestimates the error one may end up doing a lot more iterations than needed and the method becomes inefficient.

The solution to the bounding problem

Taking inspiration from the analogy between the Krylov method and the tight-binding model presented above, one cheap and efficient way to estimate the error is to approximate the missing hopping amplitudes with the average of the previous ones. This leads to a tighter, almost perfect bound that translates to an optimal number of iterations (see figure).

Algorithm implementation and use example

We have developed a Python software package to support these Krylow simulations called PyKrylovSolver. You can install directly from GitHub by doing,

pip install git+https://github.com/emilianomfortes/krylovsolver/

The package enables the time evolution of state vectors for time independent Hamiltonians, building on the Qutip framework.

The function krylovsolve evolve the vector (“psi0”) under the action of a Hamiltonian (“H”), using a krylov approximation of dimension (“krylov-dim”) and a tolerance imposed by the user (“tolerance”). The output is either the state vector or the expectation values of supplied operators (“e_ops”), computed at each time in a list (“tlist”). The following example evolves a spin chain of 8 sites under a transverse Hamiltonian,

Contribute

You are most welcome to contribute to the development of the algorithm by forking the PyKrylov Solver repository and sending pull requests, or filing bug reports on the issues page. Any code contributions will be acknowledged in the upcoming contributors section in the documentation.

Citing

If you use our error bound approach for the Krylov approximation in your research, please cite the original paper available here.

Meet the UF Ambassadors – Misty Wahl

Thu, 11 Nov 2021 00:00:00 GMT

I was introduced to the Unitary Fund through their inaugural hackathon, unitaryHACK 2021. My journey in quantum formally began in January 2021 with the MITxPro quantum computing course series. At the end of the course, I was looking for practical experience to continue my learning project, and one of the instructors suggested joining a quantum-themed hackathon. A quick search revealed that unitaryHACK was scheduled for the following month. I registered immediately and browsed the list of issues tagged for the hackathon, ultimately selecting one on applying error mitigation to a variational problem.

Hackathon project

One of the projects supported by the Unitary Fund is Mitiq, a Python toolkit for applying quantum error mitigation techniques. Noise in quantum computers can arise from a variety of sources, such as errors in state preparation, gate applications, and measurement, as well as interactions with the environment. Mitiq compiles quantum programs in intelligent ways to reduce the effect of noise on the output. At the time of writing, Mitiq supports the error mitigation techniques Zero Noise Extrapolation, Probabilistic Error Cancellation, and Clifford Data Regression. Mitiq is designed to wrap a user-defined function, which is referred to in the documentation as an “executor.” An executor takes a quantum program as input, executes it on a backend, and returns expectation values.

The challenge presented in the hackathon was to create a tutorial example demonstrating the application of one of the error mitigation techniques in Mitiq to a variational problem. Without error mitigation, noise from the quantum computer would result in poor convergence or non-convergence of the algorithm. Adding error mitigation would then allow convergence or improve convergence. Part of what interested me about the problem was that it was more research-oriented, since there was no guarantee that the desired behavior was actually achievable, although previous demonstrations indicated a solution was likely to exist.

Creating the tutorial example

I chose a simple Variational Quantum Eigensolver (VQE) problem for the tutorial example, since it is a well-known algorithm with broad practical applications. VQE is a hybrid quantum-classical algorithm used to solve eigenvalue and optimization problems. The VQE algorithm consists of a quantum subroutine run inside of a classical optimization loop. In the example, the goal of the optimization was to find the smallest eigenvalue of a matrix H, which is the Hamiltonian of a simple quantum system. I used Rigetti’s pyQuil frontend to address the need for a full-length Mitiq - pyQuil tutorial (beyond executor setup) and to use the VQE implementation and the VQE example in Grove, another Python library that is related to pyQuil.

In the example, the ansatz consists of a rotation by an angle theta and a layer of static gates. For simplicity, the quantum program is run on a noiseless backend and a depolarizing noise model is added to the static gates. The example is somewhat artificial, but it was kept simple to focus on demonstrating the benefits of error mitigation. The circuit was also kept small to avoid a long execution time on a quantum simulator.

I selected the Zero Noise Extrapolation (ZNE) technique since it is relatively simple to apply, while still yielding interesting results. ZNE computes the observable of interest at several controlled noise levels, beyond the minimum noise strength in the computer, and then extrapolates back to the zero-noise limit. The two main components of ZNE are noise scaling by unitary folding and extrapolation. For more information about ZNE, see the corresponding section in the Mitiq Users Guide.

In developing the tutorial, I encountered some interesting challenges; some I addressed by modifying the problem setup, while others prompted small improvements to Mitiq itself. Initially I kept the circuit in my example short to avoid a long execution time and executed it on a noisy QVM. After experimenting with different extrapolation techniques and scale factors, I saw a negligible mitigation at best. On some runs I found that the extrapolation failed, or that it performed worse than the noisy circuit without mitigation. Eventually I learned that the cause was in the particular noise model of the pyQuil QVM. For short circuits such as the one I initially tested, errors are modeled primarily as measurement errors, which are not mitigated by unitary folding.

The next step was to increase the length of the circuit, but I found the execution time could take 30 minutes or longer, which was impractical for a tutorial example and doubly impractical for execution during the Mitiq documentation build. As a new user of pyQuil, I was unaware that the pyQuil compiler reduced the length of the circuit in very clever ways, so when I added more static gates, the compiled circuit passed to Mitiq still did not have enough gate operations for a valid extrapolation. The compilation step was also costly in execution time.

While investigating how to make the optimization efficient on longer circuits, I learned that pyQuil supports parametric compilation. For parametric programs, the compilation is done outside the optimization loop, and the parameters are updated via a memory map (in v2) or the method program.write_memory (in v3). When I attempted to pass a parametric program to Mitiq and apply ZNE, I discovered that Mitiq would not accept the memory map. I filed an issue to that effect, and it was fixed within a few days! Later I found that support for parametric programs was not entirely necessary for the VQE example, once the compilation step was removed to allow use of custom gates. Instead, I repurposed the demonstration of ZNE with pyQuil and parametric compilation as a separate tutorial.

Even after adding more gates, the desired behavior of ZNE enhancing convergence to the minimum energy was still elusive on the noisy QVM. That was mainly because the circuits were still relatively short, and therefore the errors were still primarily measurement errors. Rather than continuing to add gates to the circuit and increasing the execution time, I decided to use a noiseless QVM and then manually build a depolarizing noise model on the static gates. In pyQuil, noise models can be added by defining custom gates with the Kraus operators representing the desired noise model at a given noise level. It should be noted that Mitiq does not fold custom gates, and therefore custom gates must be defined in the executor function, which is then wrapped by the function applying the chosen error mitigation technique.

In the end, once I defined an appropriate circuit and noise model, I was able to show that applying ZNE enhanced convergence to the minimum energy. While the VQE algorithm is generally considered to be robust to noise (see the VQE tutorial in pyQuil / Grove), I observed that without mitigation, the accumulation of errors still resulted in loss of accuracy and additional iterations required to reach convergence. While there was some variation from run to run, applying ZNE generally improved convergence to the minimum energy in terms of accuracy, number of iterations, or both. The performance increase from ZNE was most evident in the energy landscape plot, where the noisy landscape was noticeably flatter than the landscape generated with ZNE.

Community impact

I expect the quantum OSS community can benefit from this project and similar projects in a variety of ways. Of course, continuing to expand the collection of Mitiq examples will help educate the community on using Mitiq and the supported error mitigation techniques. Furthermore, I hope the results demonstrated in the example will encourage users to apply error mitigation to other problems of interest. For instance, it would be interesting to see Clifford Data Regression applied to more use cases, as it is a relatively new technique. Also, more extensive use of error mitigation is likely to motivate refinement of existing methods and the development of new ones.

Finally, I wish to emphasize that as a Mitiq contributor, I have been able to connect directly with the development team and raise improvement suggestions. In response, the team added support for pyQuil parametric programs as mentioned earlier, as well as some improvements to facilitate contributing to Mitiq for Windows users. The Mitiq team also provided many helpful suggestions during the development of the example, and I am grateful for their support. It is my hope that this iterative and collaborative approach will encourage more contributors to join the quantum OSS community and help build the ecosystem.

<p class="leading-block"> Stay up to date with what Misty is working on by following her on <a href="https://twitter.com/mistyawahl" target="_blank">Twitter</a>, <a href="https://github.com/Misty-W" target="_blank">GitHub</a>, and <a href="https://www.linkedin.com/in/misty-wahl" target="_blank">LinkedIn</a>!</p>

Learn how to write new quantum algorithms on quantumalgorithms.org

Tue, 09 Nov 2021 00:00:00 GMT

Have you ever tried to learn about quantum algorithms but got stranded by the lack of structured material online? We've got you covered. Now you can learn more about it on https://quantumalgorithms.org!

Quantumalgorithms.org is an open-source book on quantum algorithms with two purposes:

Closing the gap between the usual introductory course in quantum computing and the state-of-the-art research papers in quantum algorithms.
Being the peer-reviewed, up-to-date, go-to reference for lemmas, theorems, corollaries, and algorithms needed by quantum algorithms researchers and quantum software developers.

As of today, the book focuses on an algorithmic perspective of quantum machine learning and touches topics like quantum algorithms for Monte Carlo, techniques for lower bounding query complexity, and numerical experiments on real datasets. A sizeable appendix also covers the theory needed to understand quantum machine learning from a computer science perspective. This is how the content is structured so far.

In Part 1 - introduction and toolkit - we briefly introduce our formalism for quantum computing, with the axioms of quantum mechanics, explaining how to I/O (input and output) classical data in a quantum computer. Then, we outline a list of theorems and algorithms that are the basic toolkit of the quantum algorithm researcher and give concrete examples on how to use them. You can find in here all the subroutines for performing singular value estimation, phase estimation, finding the minimum, distance estimation, inner product estimation, amplitude estimation, and so on.

In Part 2 - quantum algorithms and quantum machine learning - we see how to use the techniques described previously, with a focus on machine learning. We see how to perform clustering (q-means, quantum Gaussian mixture models) and dimensionality reduction (quantum PCA and quantum slow feature analysis). Last but not least, we have a chapter on quantum algorithms for Monte Carlo (which we are expanding in these weeks to include more algorithms and applications), algorithms on graphs, and techniques for lower bounding the query complexity of your algorithms, and much more.

In Part 3 - the appendix - we focus on putting together the mathematical background, definitions, and theorems that are used throughout the book. We put much emphasis on linear algebra, concentration inequalities, and tricks that are often taken for granted in most papers.

The book has a core team and many contributors that help keep it updated, clear, and correct. It started in its early days from the old blog of Alessandro Luongo, subsequently including parts of his Ph.D. thesis on quantum machine learning. Then we added contents from the MSc thesis of Armando Bellante. We recently hosted five students from the mentorship program of the Quantum Open Source Foundation. With them, we worked on quantum algorithms on graphs, quantum algorithms for speeding up Monte Carlo techniques, and quantum perceptrons algorithms. Many friends and great researchers have contributed to the project by spotting typos, writing chapters, submitting parts of their papers or thesis chapters. We wholeheartedly thank them and report their names here: Patrick Rebentrost, Yassine Hamoudi, Martin Plávala, Trong Duong, Filippo Miatto, Jinge Bao, Michele Vischi, Adrian Lee, Samantha Buck, Sathyawageeswar Subramanian.

Quantumalgorithms.org has constantly been growing. The project is currently supported by the Unitary Fund and the Centre For Quantum Technologies (the CQT of Singapore). These funds are dedicated to compensating collaborators that help us write more high-quality content and enrich the book's quality. At the moment, two collaborators are working on some brand-new, thrilling chapters that should be available by the end of the year!

The book has already been used as teaching material for two different courses at Politecnico di Milano. We hope quantumalgorithms.org can be used fruitfully in many other courses, summer schools, workshops, etc., in the future. Do you plan to teach quantum computing and quantum algorithms and need some lecture notes to support your teaching? Let us know! We would be extremely happy to cite your course on our website, share our teaching experience based on these lecture notes, and hand out additional material not yet transcribed on the website.

This is just the beginning of our journey. In the future, the book will cover more content: new quantum algorithms and more appendices to cover advanced theoretical computer science topics. Interested MSc and Ph.D. students are encouraged to engage with the core team of the open-source project (contacts below!). We need your help in building this giant book! There are many big and small issues on GitHub that are waiting for you! New chapters are waiting to be written, and many sections could be expanded or ameliorated.

As the book grows, we are encouraging all kinds of contributors:

Typo Hunters,
Friendly Reviewers,
Consistency Fanatics,
Precise Writers.

To name some tasks, we are searching for contributors to improve the section on error propagation and write more introductory material in chapters 2 and 3. Another much-appreciated contribution would be to give us feedback on the book's content: are there parts that are too hard to understand? Can a section be made more easily accessible? Are we missing some algorithm or paper to cite? We also have a list of exercises that are waiting to be added to the book. Are you willing to go the extra mile, write a whole new chapter, and get paid for your contribution? Contact us, and let's have a chat! We are waiting for you!

The core team,

Alessandro Luongo, ale[at]nus.edu.sg
Armando Bellante, armando.bellante[at]polimi.it

P.s. We are working on some high-quality quantumalgorithms.org's swag for our contributors ;)

Improving VQA Performance through Error Mitigation

Wed, 27 Oct 2021 00:00:00 GMT

About Me

I am a senior in high school with a great interest in Quantum Computing. I was able to learn about it by taking QubitxQubit’s Introduction to Quantum Computing course last year.

Project Background

The originally proposed purpose of this project was to improve Variational Quantum Algorithm (VQA) performance using error mitigation. VQAs use parametrized quantum circuits and a classical optimizer to minimize a cost function. VQAs have the potential to effectively address the constraints of near-term Quantum Computers, but noise poses a challenge to the effectiveness of VQAs.

However, error mitigation strategies could solve some of the problems associated with noise in VQAs. In this project, I used the error mitigation strategies offered by Mitiq to assess their effect on VQAs.

Mitiq Overview

Mitiq is a platform agnostic error mitigation software library with three built in error mitigation methods: zero noise extrapolation, probabilistic error cancellation, and clifford data regression. Through the course of this project, I worked with the Mitiq team and contributed to the documentation and benchmarking techniques (more on that later).

My Experience with Mitiq

My experience with Mitiq as a user has been quite positive. With extensive documentation and an intuitive interface, Mitiq has proven to be very user friendly even for those with little experience with error mitigation such as myself. Additionally, Mitiq is constantly being updated with new features and examples.

But, what’s more impressive is my experience with Mitiq as a contributor. Mitiq has a very knowledgeable and helpful team that is always ready to review pull requests and help contributors out with any issues they have. Additionally, the Mitiq team also has weekly community meetings for Mitiq where anyone can join and ask questions about Mitiq, pose new ideas, and have discussions about how to best improve Mitiq. It’s this attitude of inviting a variety of opinions to the development of Mitiq that allows it to be constantly improving very quickly.

Mirror Circuits

Although I began my project by looking at the effect of error mitigation on VQAs, it quickly became apparent that there was a lack of benchmarking methods available to measure the effectiveness of quantum processors with and without error mitigation. This is why a large amount of my time on this project was spent working on implementing the Randomized Mirror Circuits benchmarking method as presented in this paper.

Mirror Circuits use a similar principle to Loschmidt echo circuits, which are circuits that have the form $UU^\dag$. This is useful because the circuit should yield the 0 bitstring 100% of the time barring any errors, meaning we can use it to measure the error rate of a quantum processor.

However, there are multiple problems that inhibit the effectiveness of Loschmidt echo circuits, the first of which being systematic error cancellation. The simplest example of this would be if there is an error that makes $R_x(\pi/2)$ applied to a qubit actually apply $R_x(\pi/2 + \epsilon)$. The inverse of this gate would then be $R_x (\pi/2 - \epsilon)$ and the resulting bitstring would still be 0 in spite of the error. Another limitation of Loschmidt echo circuits is that a single input state is used, so errors not impacting that single state are not accounted for. Finally, only one measurement basis is used so errors that are not apparent in that one measurement basis are not accounted for.

It’s these limitations with Loschmidt echo circuits that prompted the creation of the Mirror Circuits benchmarking method. Mirror Circuits take the Loschmidt echo circuits and use key changes to it to avoid the aforementioned problems with them. For these purposes, it’s best to think of the echo circuit as a series of Clifford layers followed by the inverses of each of these layers. To reduce the chances of systematic error cancellation, we insert a central random pauli layer and insert random pauli layers between each layer. Additionally, we add a layer of random single-qubit Clifford gates to the beginning of the circuit, and the inverse of that layer to the end of the circuit to avoid the problems involving preparing and measuring in only one basis. After these changes, we are left with this:

This is an example of a simple, single layer randomized mirror circuit. The nice thing about randomized mirror circuits is it still only has one possible output making it easy to use for benchmarking quantum processors, while minimizing the problems present in Loschmidt echo circuits.

I implemented a function in Mitiq (code here) to generate these randomized mirror circuits for any provided computer architecture. Through conversions, users can easily get mirror circuits in any existing package supported by Mitiq, for example Cirq, Qiskit, pyQuil, Pennylane, and the Amazon Braket SDK. This function provides another benchmarking circuit to easily test error mitigation methods in Mitiq. For example, the Mitiq team has already used mirror circuits to benchmark zero-noise extrapolation on Rigetti devices through AWS (blogpost, notebook).

Other Works

Although the Mirror Circuits implementation was the main result of my research, I also recently spent time reading this paper on the effects of error mitigation on VQA trainability. It seemed to have some insight about the error mitigation methods used in Mitiq so I gave a presentation on this paper to the Mitiq team recently. The slides for the presentation can be seen here. Although the paper was largely theoretical it emphasized the difficulty of VQA trainability in the presence of noise even with error mitigation. However, it showed that Clifford Data Regression, one of the Error Mitigation methods in Mitiq, appears to have a promising effect on VQA trainability.

Final Thoughts

I have learned very much about Error Mitigation throughout the course of this project while being able to contribute to Mitiq and the field as a whole. I want to thank the Unitary Fund team for their continued help and support. I’d especially like to thank Ryan LaRose for being my advisor throughout this project and consistently guiding me and providing advice.

Announcing the Unitary Fund Ambassador Program and introducing our first Ambassadors

Mon, 18 Oct 2021 00:00:00 GMT

Quantum technology is growing rapidly, and finding space where you can grow and succeed is more important than ever. Open source tools and communities are a critical component in enabling the development of cutting-edge quantum technologies. However, there is a lack of acknowledgement for the amazing things people are supporting these efforts and projects around the globe. As a non-profit organization supporting the open quantum ecosystem, we want to help change that.

Unitary Fund Ambassadors program

The Unitary Fund is excited to announce our new Quantum Ambassadors program, a way of recognizing individuals that are directly addressing the challenges of the growing quantum community. Unitary Fund Quantum Ambassadors bring together their peers to learn new skills, develop open source tools, and build the open quantum community all over the world.

Introducing the first Ambassadors 🎉

Picking our first Ambassadors was a hard job, with so many amazing folks contributing to the open quantum ecosystem. Given the competitive field, these individuals are outstanding in how they engage and collaborate with the community, and make their own contributions to OSS projects. So, without further ado, here are our first group of ambassadors!

Andre Alves | GitHub LinkedIn
Aaron Robertson | GitHub LinkedIn
Purva Thakre | GitHub
Misty Wahl | GitHub LinkedIn

We will be hosting blog posts from all the Ambassadors in the coming weeks, so stay tuned right here! Join our newsletter to get updates about this blog in your inbox, follow us on Twitter, or join our Discord to hang out with the open quantum community 💛🌴.

unitaryHACK retrospective: Growing the quantum open source community one commit at a time

Wed, 13 Oct 2021 00:00:00 GMT

We'd like to thank our sponsors Xanadu, DoraHacks, and Pasqal for helping to make this event a reality 💖

At Unitary Fund, we help those interested in contributing to open quantum projects learn and practice the skills they need to do so. In May 2021, we organized unitaryHACK, a distributed quantum open source hackathon with 4k USD in bounties, physical and digital swag, and 20 participating projects. Working with open source project maintainers, we helped community members with a wide variety of backgrounds make meaningful contributions to their projects. Maintainers as well as Unitary Fund staff were on hand on our Discord to help out with questions about the quantum technologies as well as the tools they use like git, GitHub, and a variety of languages and platforms used in the quantum space (Python, Julia, Q#, C++, Ruby, etc.)

Digital swag for unitaryHACK, designed by Frances Poblete.

So, what did the community create?

Over 370 attendees registered for the hackathon, many of whom were new to open source contributions, quantum computing, or both! At the end of the two-week event, unitaryHACK enabled over 64 contributions, 26 bounties claimed, and half of the participants had never contributed to open source projects before. Established projects like Q#, QuTiP, SciRate, and PennyLane were featured along with more recent ones like Yao, QuNetSim, and Pulser, among many more. Some of the functionalities added resolved long standing issues, like one for QuTiP dating back January 2018! There were 3 new projects that were started as a result of this events, SciRate discord bot, Yao.jl examples website, and two new libraries for Yao.jl interfaces for the IBMQClient and OpenQASM), and almost all participants had not contributed to open quantum projects before, many of which are still actively engaged in the projects they contributed to as a part of the hackathon.

During unitaryHACK, we were super impressed by both the high quality of the participant's contributions, and also their enthusiasm — we've seen several become ongoing contributors long after the event! It's been a fantastic way to source applicants for our quantum software roles at Xanadu.

—Josh Izaac at Xanadu

All in all, it was a great way to introduce lots of folks to open source quantum projects, and grow the community of quantum developers. That’s all for now, but stay tuned to our Discord, Twitter, LinkedIn, mailing list, and community calendar and join one of the most influential communities in quantum technologies.

Would you like to help support future iterations of unitaryHACK? [email protected]">Get in touch with us, and we would love to collaborate!

Unitary Fund Q3 2021 Update: New projects, the 2021 Wittek Prize and QuTiP community calls

Mon, 11 Oct 2021 00:00:00 GMT

To the Unitary Fund community,

As we reflect on this last quarter, the pace of developments in the field continues to impress. There have been large fundraising rounds for private (and now first public) companies as well as new government initiatives. At the end of the day, though, technologies and industries are built by people and communities. Just the kind that we are growing through Unitary Fund.

This last quarter has seen growth among discords, talks, and meetups as well as new grant funded projects. Do you want to help recognize someone who has made a big impact to the community? As a reminder the 2021 edition of the Wittek Prize, organized together with QOSF, is live, and nominations open. Check out the website – it’s awesome!

We continue to work hard to support the development of a vibrant, open quantum technology ecosystem. Thanks to all of you who have joined us in this mission.

New from Unitary Fund
We’re looking for someone to join the Unitary Fund team for a part-time role in Marketing and Communications. Read more about the flexible hours, fully-remote role here.
About Mitiq:
We released versions 0.7.0 through 0.10.0 of mitiq adding many new collaborators from the community. Thanks for your contributions!
We released a new version of the Mitiq whitepaper describing the new techniques of probabilistics error cancellation and clifford data regression that have been added to the library.
The new Mitiq integration with Braket is featured on the AWS blog!
We co-authored a new paper on quantum error mitigation, further extending the applicability of the promising technique of probabilistic error cancellation to avoid tomographic overhead (arXiv:2108.02237).
We hosted Goutam Tamvada in our Quantum Software Talks Series where he spoke about VeriFrodo: an open source library implementing a post-quantum communication protocol in Jasmin.
We spoke about Unitary Fund to many new communities, including at Duke Quantum Computing Meetup and at the QEAM 21 workshop!
New Grants
To Brian Shi to build Qdot, a Scala 3 library (QASM-transpiler) that allows Scala/Java developers to write native quantum/hybrid programs.
To Gerald E. Fux and Dominic Gribben from the TEMPO collaboration to develop OQuPy, an open source python package for simulating non-Markovian open quantum systems using tensor network techniques. In particular, the grant will enable adding two new features: studying the role of environment correlation functions through observables of the system and of multiple environments coupled to a single system.
To Utkarsh Azad and Animesh Sinha to build a visualization tool called qLEET for exploring loss landscapes, expressibility, entangling capacity and trainability for noisy, parameterized quantum circuits.
To Danny Samuel, to improve and extend the performance of variational quantum algorithms with error mitigation, benchmarking them with mirror circuits.
News from UF Projects
QuTiP 10-year anniversary was held on Unitary Fund’s Discord. Blog post here. Slides here.
Quantum Flytrap completed a seed round of VC investment and participated in the CDL Quantum Bootcamp. They also started working with another UF project Qubit by Qubit who have started using their Virtual Lab (with constantly expanding functionalities) for their courses.
The interlin-q project will be presenting at the SC21 conference in November and an extended writeup will appear in the conference proceedings in IEEE
QWorld organized their internship program, first global and online summer school with 675 graduates, and have started their first graduate-level online course on quantum computing and programming.
Quantum Community Updates
We’re organizing with the QOSF the 2021 edition of the Wittek Prize. Nominate someone here. The prize consists of $4,000 awarded to an outstanding contributor to the quantum open source community. It will be announced at the end of the year.
We’re hosting a monthly Quantum Software Meetup with the folks from QOSF, on Gather Town. It’s an informal meetup to discuss new technologies, share resources, and learn from projects’ updates. https://unitary.foundation/meetup.html
We’re involved in organizing two workshops within IEEE Quantum Week (October 18-22, 2021): One on Quantum Intermediate Representation and one on Open Quantum Hardware. Sign up to join.
We’re hosting the QuTiP community Call quarterly on the Unitary Fund Discord server. The next call is on October 27th, 2021, at 2pm CET featuring three talks on the 2021 Google Summer of Code projects (Tensorflow data layer; CuPy data layer; Unitary decomposition to universal gates). Save the Community Calendar event in your agenda.
Pennylane has begun hosting their regular community calls on the Unitary Fund discord.
There is a new call for papers in Research Topic in Frontiers of Physics on “Programming Physical Quantum Systems: Methods, Applications, Languages and Compilers”

Best wishes to all of you,

Will and the Unitary Fund Team

New support for Mitiq on Amazon Braket

Mon, 04 Oct 2021 00:00:00 GMT

The Mitiq development team is excited to announce that with the latest release of Mitiq, Amazon Braket is now supported as a back-end for running verbatim circuits. To demonstrate this, we collaborated with the Braket team to benchmark the performance of the Rigetti Aspen-9 device with and without Mitiq’s zero-noise extrapolation on mirror circuits.

Results from the benchmark and methodology are detailed on the Amazon Braket blogpost, and you can check out the sample code in the Mitiq docs.

Two Workshops Organized in 2021 IEEE Quantum Week: Open Hardware and Intermediate Representations

Fri, 24 Sep 2021 00:00:00 GMT

We believe that it is important to involve the research and technical communities to ensure the quantum open source ecosystem can scale. For this reason, Unitary Fund is co-organizing two workshops as part of International Conference on Quantum Computing and Engineering (QEC21), run by IEEE which is one of the largest professional societies in the world.

The first workshop is on Quantum Intermediate Representations (mini-website). This workshop explores approaches that let quantum language compilers target a common intermediate layer that can be further lowered to any native backend architecture. Common standards are required to reduce the proliferation of quantum computing system architectures and associated mechanisms for high-level programming, which place a burden on programmers hoping to write quantum-classical applications that target a variety of quantum backends. The workshop will be held on Friday, Oct 22, 2021 Time: 10:45-16:45 Mountain Time (MDT).

The second workshop is on Open Quantum Hardware. While open-sourcing “quantum software” is already established, this workshop focuses on the ongoing and upcoming development of the tools and components actually used to build quantum computers and make them accessible: From software for electronic design and analysis, to control systems and testbeds. The Workshop will occur on Tuesday October 19th from 10:45 to 16:45 Mountain Time.

Registration for IEEE Quantum Week is still open! You will find open-access material in Unitary Fund’s repository, such as on the Open Quantum Hardware mini-website.

zs We would also like to highlight an in-depth tutorial at QCE21 from one of our collaborators called “Pulse-level Programming of Neutral-Atom Devices with Pulser”. This session is scheduled for Tuesday, Oct 19, 2021 at 10:45-14:30 MDT.

Microgrant Update: Interlin-q for distributed quantum computing: A path to large scale quantum computing

Fri, 17 Sep 2021 00:00:00 GMT

This post was originally published on Medium, and is being syndicated here.

A major obstacle for quantum computers to overcome in order to be useful for industrial scale problems is the need to be scaled up. Scaling quantum computers up to levels beyond the NISQ (i.e. 10s-100s of noisy qubits) era will require scientific breakthroughs and overcoming many current technological hurdles. One proposed solution to overcoming the scaling problem is to connect many smaller scale quantum processors together to form a distributed quantum computing. In this article I’ll summarize what a “distributed quantum computer” means and also discuss the challenges introduced when networking quantum computers. At the end, I will summarize and demo the Interlin-q project which aims to aid in studying some of the problems faced when dealing with distributed quantum computing.

To start off, it’s important to know what is meant by “scaling” when it comes to quantum computing. Scaling with regards to quantum computing generally refers to a few key things. Firstly the number of logical qubits that the quantum computer contains. “Logical” here effectively means a qubit that one can perform logical operations on. The number of logical qubits is important because as the size of the inputs — longer lists, bigger numbers, etc.— to a quantum algorithm grows, generally the number of qubits required to the perform the algorithm increases, and usually quite rapidly. For example, using Shor’s factoring algorithm, it takes 5 qubits to factor the number 15, but at the scale of 2048 bit RSA, the main cryptographic protocol for the Internet, it may require tens of millions of qubits (albeit not all logical). The current available quantum computers have in the range of hundreds of qubits, and it projected to take decades to reach millions of qubits with the current trends, although this is generally a controversial topic.

Another component to scaling up is the number of sequential operations (or logical gates) that can be applied to the qubits before too much noise is introduced to get any useable information out. This is generally referred to as the maximum circuit depth of the quantum computer. Circuit depth depends on a number of things, but most important are 1) the quality of technology performing the operations on the qubit, for example microwave or laser pulses, and 2) the quality of the qubits themselves, generally measured by how long they can remain in their quantum states before decohering to a classical state. These two properties are the main factors that govern how deep a circuit can be. Circuit depth is important because non-trivial quantum algorithms not only require many qubits, but will generally require a high circuit depth, and so being able to perform many sequential logical operations on the qubits will be of top importance for scaling.

Lastly, the next most common feature referred to when discussing scaling is how “connected” the quantum computer is, or “qubit connectivy”. What connectivity measures is effectively the number of qubits that each qubit can interact directly with. For example, if a quantum computer has n qubits and each qubit can interact directly with each other qubit, then the connectivity of this quantum computer is n-1. If on the other hand a qubit can only interact directly with one other qubit, then the connectivity is 1. This is important because when performing controlled operations (e.g. a CNOT gate), generally the qubits need to be physically near each other. If the qubits are not connected nor near, then moving the qubits to a place where such a controlled operation can be performed is required. This is usually done via what is known as a “swap chain” or via a teleportation protocol. The more connected a quantum computer is, the easier is it to perform controlled operations between arbitrary qubits, which has many implications when performing quantum algorithms in practice — a major one being the simplification of circuit compilation. Low connectivity implies a high complexity for circuit compilation which generally means longer runtimes and less time for performing logical operations. Increasing connectivity is a complex hardware problem and much work is also being done for improving algorithms for qubit routing within quantum computers.

The scaling problem is one of a fine balance between improving certain aspects while not affecting the others. For example, simply increasing the number of qubits in a quantum computer can make the connectivity more challenging. Or increasing the connectivity can make increasing circuit depth harder. To get a quick overall estimate for the quality of a quantum computer, the number of qubits, the maximum circuit depth, and the level of connectivity in a quantum computer have been combined to have a single measure called the quantum volume. Personally I think quantum volume is not a completely fair measure given the vast differences in technologies between the various quantum computer implementations (e.g. superconducting vs. trapped ion), so I usually refer to papers using the quantum computers to perform a quantum algorithm to get an estimate of their quality. Overall, the scale required to perform non-trivial quantum algorithms very rapidly increases with the problem complexity and so much research is being dedicated to methods of scaling up quantum computers.

One of the approaches to scaling that I find very interesting is distributed quantum computing. As it was done with classical computing when scaling became an issue, the concept of networking smaller processors together in order to distributing a computational load was introduced. For quantum computing, the same idea applies: Scaling quantum computers up is an issue, and so one can consider networking smaller quantum computers together. Naturally, since quantum computing varies drastically from classical computing, designing networked quantum computers introduces challenges that do not exist in purely classical networks. To more clearly understand these challenges, it helps to first understand what exactly a distributed quantum computing architecture could be.

A distributed quantum computer is a collection of quantum computers, nodes, where each quantum computer in the collection has a number of qubits on which it can operate. The quantum computers are connected via a network with which they can transmit classical- and, more importantly, quantum bits of information between themselves. A key difference for distributed quantum computing is that a connection to other nodes via a classical network alone is not enough to perform quantum computing in general, and so there must also be connection via a quantum network as well. A quantum network is the solution to the first major challenge for distributed quantum computing: Performing multi-qubit controlled operations (e.g. a CNOT gate) between qubits that are not physically located on the same quantum computer.

Because multiple qubits can be correlated via quantum entanglement, performing controlled operations becomes even more challenging across distributed quantum computers. Naturally due to the properties of quantum systems, one cannot simply measure the control qubit and transmit the classical information to the other computer. Rather, one needs to introduce another method which doesn’t measure the control qubit but yet still transmits the control information. This is usually referred to as a “non-local control operation” and are a number of ways to achieve this, one being quantum teleportation. Each method has resource requirement trade-offs and other than directly transmitting the control qubit, each of the methods has something in common: To transmit control information, an entanglement resource must first be created. Recently an experiment performing a non-local CNOT gate using a flying qubit (i.e. a single photon) entangled with the control qubit to transmit the control information was performed. When the flying qubit arrives at the other quantum computer, it interacts with the target qubit of the CNOT gate, completing the first part of the CNOT gate. To completely perform a CNOT gate, one needs to be aware of the “phase kick-back” that results from the states potentially being entangled. The last step of the non-local CNOT protocol is to extract the phase information from the flying qubit which becomes entangled with the target qubit after interaction. Luckily, this can be done by measuring the flying qubit and transmitting the single bit. Using the bit as control, a phase flip on the control qubit is performed or not.

The next major problem to overcome is that to perform distributed quantum computing, one has to remap quantum circuits designed for monolithic quantum computers (i.e. one single quantum computer) to a distributed architecture, filling in any missing pieces like the non-local control operations with equivalent steps. This requires two things: 1) Remapping monolithic circuits to distributed circuits; and 2) Preparing a precise instruction-execution schedule so that the two quantum computers work properly together. This introduces yet another step into the already non-trivial problem of quantum circuit compilation. These two problems are addressed in depth in a recent article I’ve co-authored with Marco Ghibaudi and James Cruise, but I will briefly review the approach we took for remapping and scheduling.

In the above image, what we see is an example of the remapping from a monolithic circuit in (a) to an equivalent distributed circuit in (b). Here the red boxes indicate two networked quantum computers. This approach is not the only approach that can be used, and indeed there are others proposed, but for now we will stick with it since I know it best. The approach can be summarized as follows: Given an already optimized circuit designed for a monolithic quantum computer and the qubit topology of the distributed system, find any control gates that have control and target qubits not on the same quantum computer, and replace the local gate with its non-local equivalent — essentially a “find an replace”. There are some minor optimizations that I don’t describe, but that is the heart of it. One then feeds this distributed algorithm to a circuit scheduler.

To execute a distributed quantum algorithm, a precise execution schedule is required. In our article, we assume two different distributed topologies, the more straightforward in the below image. What the image shows is a network of quantum computers connected via a low-latency classical network, an entanglement network, and lastly an additional network which connects all of the quantum computers to a single controller. Such an architecture is common in mainframes for example, where a controller node dictates the programs to the computers in the cluster. Indeed we propose a similar idea. The single controller receives a circuit designed for the collection of quantum processing units (QPUs), or quantum computers, but designed assuming the n QPUs form monolithic system. The controller, knowing the distributed QPU topology, can perform the required remapping of the circuit to the distributed circuit. The next step, as already mentioned, is generating an execution schedule.

The execution schedule uses a straight-forward approach using the assumption that the QPUs are all time-synchronized. When constructing the the distributed quantum computing, the timing specifications for the hardware components such as the latency of the cable, the timing of the gates, the entanglement generation rate, etc. will all be known. Given the timing parameters, the scheduling algorithm simply lines up the executions in time to then instruct the quantum computers to perform any distributed operation synchronously. The output of the scheduler is a list of hardware commands with a timestamp which is then distributed to the cluster of QPUs to begin the execution. Once complete, all measurement results are sent back to the controller, processed, and sent back to the user as if the algorithm was executed on a single QPU.

In the article we analyze such a system and propose how this can be constructed as well as controlled using the Deltaflow.OS. What was left open from the work was a prototype of the proposed solution in simulation. In the next part of this post, I’ll discuss how we took the above ideas and translated them into a working simulation prototype.

Through the last two iterations of the Quantum Open Source Foundation’s mentorship program, Rhea Parekh, Ahmed Darwish, and I spent time working on developing a simulation platform for distributed quantum computing. The proposed solutions for distributing quantum circuits and scheduling from the work mentioned above were implemented and then simulating with parallel computation. We’ve dubbed this project “Interlin-q” and have now received supported by the Unitary Fund via their mirco-grant program.

Overall the plans for this project are to incorporate the various proposals and methods for performing distributed quantum computing into a simulator to show proof of concept. We moreover aim to study potential speedups that can be gained when taking particular quantum algorithms and putting them into a distributed and parallel setting. This beginning of this, we added in our arXiv write up of the current progress: Quantum Algorithms and Simulation for Parallel and Distributed Quantum Computing

Interlin-q is built on top of another framework called QuNetSim. QuNetSim is a quantum network simulator that simulates quantum network protocols up to the network layer. For more information about QuNetSim, there is a write up and a few YouTube videos as well. What Interlin-q does is it extends the network hosts of QuNetSim into two new objects, one which represents the controller of the overall system, and one that behaves purely as a controlled entity. These two objects behave like the components of network configuration of the image above.

The way a user interacts with Interlin-q is, they are expected to firstly define their distributed quantum computing architecture by setting the number of computing nodes in the system as well as how many qubits are on each node. One does this using the features of Interlin-q for building the distributed system. Next, the user programs their quantum circuit assuming all of the qubits in the distributed system exist on a single machine. To then start the simulation, the circuit is given to the controller node which performs the distribution mapping and creates a runtime schedule. The runtime schedule is distributed to the computing nodes and the simulation begins.

During the simulation, based on the execution schedule generated, the QuNetSim backend is triggered to send messages and generate entanglement between the computing nodes, as well as perform the logic gates in a synchronized fashion. At the end of the simulation, the computing nodes send all their measurement results back to the controller for processing and the user can then program what to do with the measurement results.

As a first non-trivial example of using Interlin-q, in the latest iteration of the mentorship program we implemented a parallized version of VQE much like the proposed approach in the Pennylane blog. One can review the Jupyter notebook of the example here. In a future post, I will go into detail of how this was implemented and the theory behind it.

Overall, we aim to continue our work with Interlin-q — tightening the screws, generating more examples, and implementing more examples from the literature. We hope to build up more interest in distributed quantum computing grow the community around it. The path to large scale quantum computing will inevitably make use of networked quantum computers and with that opens the door for many interesting questions!

Celebrating quantum open-source software contributors: Nominations open for the 2021 Wittek Quantum Prize for Open Source Software

Mon, 13 Sep 2021 00:00:00 GMT

Together with the Quantum Open Source Foundation, we are thrilled to open nominations for the 2021 Wittek Quantum Prize for Open Source Software. This US$4000 prize is dedicated to celebrating open source software contributors in the quantum computing space. The prize is named after the late Peter Wittek, a strongly vocal advocate for open source software in research.

Open source software tools are critical to basically all modern technologies, and quantum tech is no exception. Building an open-source-first stack for quantum development is essential to securing open access to this new technology, as well as accelerating progress across the field. Despite the central role that the open source software plays, the contributions of diligent individuals and hard work of maintainers are often not recognized by the wider community at the level they deserve.

In order to recognize the work of these unsung heroes, developers and maintainers, often unaware of the magnitude of the impact their work is having on the community, Unitary Fund is partnering with the QOSF in order to award a US$4000 prize to an open source software contributor / maintainer to help provide the recognition they deserve. The winner of the prize will be selected by the Unitary Fund’s advisory board, which kindly agreed to act as independent evaluation committee.

Last year, we were happy to award the inaugural prize to Roger Luo. If you want to learn about Roger and his work, please check out this video interview and Quantum Software Talk. Read more about the 2021 Wittek Quantum Prize on the award website. If you know individuals that you’d like to nominate, or you’d like to nominate yourself, please submit in this form.

A new version of the Mitiq white paper

Thu, 15 Jul 2021 00:00:00 GMT

About a year ago, in September 2020, we released Mitiq 0.1.0 and posted its associated white paper. This was the first “stable” version of an open-source Python package for quantum error mitigation on near-term quantum computers. Mitiq was officially born.

At that time, only one error mitigation technique was implemented in Mitiq: zero-noise extrapolation, which was (and still is) contained in the package module mitiq.zne.

Since then, Mitiq has developed at a rate of approximately one release per month. In this period, many new features have been added and many bugs have been fixed too :-). Some highlights include:

A new module (mitiq.pec), implementing an error mitigation technique known as probabilistic error cancellation. The workflow to apply probabilistic error cancellation is very similar to that of zero-noise extrapolation, as shown in this quickstart example.
A new module (mitiq.cdr), implementing a learning-based error mitigation method called Clifford data regression.
A new module (mitiq.interfaces), re-organizing all the integrations with other quantum software libraries. In particular, support for Braket circuits was recently introduced, in addition to the existing integrations (Cirq, Qiskit, PyQuil).

<div align="center"> <img src="https://res.cloudinary.com/dcz4ywuer/image/upload/v1690842757/vb4gypbxm9bslnlr92d1.png" style="width: 70%; height: auto;" /> </div>

Diagram visualizing the modules of Mitiq. Extracted from arXiv:2009.04417v2.

These new features, together with all the additional changes that are reported in the Mitiq changelog, provided a strong motivation for re-submitting a new updated version of the Mitiq paper on the arXiv server.

However, there was another important motivation too. We are excited to give proper credit to the many people, beyond the Unitary Fund team, that provided a significant contribution to the development of the library. In alphabetical order, they are:

Andre A. Alves,
Piotr Czarnik,
Mohamed El Mandouh,
Max H. Gordon,
Yousef Hindy,
Aaron Robertson,
Purva Thakre.

The re-submitted version has now 13 authors and, in the spirit of open-source projects, we hope that even more people will be involved in the future.

All Mitiq contributors are now proudly acknowledged in the README page of Mitiq, where you can also find the links to their GitHub accounts.

References

The second version of the Mitiq paper: arXiv:2009.04417v2
The first version of the Mitiq paper: arXiv:2009.04417v1
The documentation of Mitiq, pinned to the version (v0.9.3) associated to arXiv:2009.04417v2: https://mitiq.readthedocs.io/en/v0.9.3/

QuTiP's 10-year anniversary

Mon, 12 Jul 2021 00:00:00 GMT

QuTiP v. 1.0 was released 10 years ago, on July 29th, 2011. It began as the project of two postdocs in Franco Nori’s group, Robert Johansson and Paul Nation and has since been embraced by an ever larger community of users and contributors. QuTiP is the most used software package for the simulation of open quantum systems as it’s used daily by researchers worldwide and students alike.

To mark the 10 year anniversary, the QuTiP admin team would like to organize a online party to celebrate the project and its community of users and contributors: You are all invited to an online meeting on July 29th, 2021 at 1pm GMT (on Unitary Fund’s Discord server, see the Community Calendar to save the event in your agenda). We'll share recent updates on the project and everyone is welcome to add their own contribution.

. As a summary, some stats:

Over 13,000 downloads a month from the Python Package Index only and more than 350,000 downloads overall from the Conda Forge channel by Anaconda only.
As of June 2021, 7076 commits, in over 13 version releases by over 96 contributors.
The two QuTiP papers have been cited over 1500 times (according to Google Scholar).

There’s much more to discover and build with QuTiP and in QuTiP. We’d like to celebrate the collective achievements so far and discuss the future steps.

More than a Software Package

QuTiP contains a bundle of dynamical solvers – efficiently treating Lindblad master equations at the density matrix level as well as Monte Carlo trajectories, down to more specific solvers such as for non-Markovian dynamics in structured baths and oscillating drives in Floquet theory. Moreover, more features have been added, from a quantum circuit simulator and compiler (now with pulse-level noisy simulators on mock processors) to more specific features and integrations. In a recent code design choice, these features have been spun out of the core package and now populate a family of packages in the QuTiP organization on GitHub.

Over the years, the project has evolved. Beyond the updates of the first two major releases, that are documented in two research articles (QuTiP 1 and QuTiP 2), there have been two other major releases, and a QuTiP version 5 release is in the pipeline for later in 2021. Major updates will include a more flexible data layer structure and ways to make a quantum system evolve in time.

A Growing Community

The community continues to evolve. The team of lead contributors and maintainers has extended geographically and numerically, with 8 active members of the Admin Team overseen by a 5 member Advisory Board. A full list of contributors can be found on GitHub. In 2019 the first QuTiP developers’ workshop was organized, bringing together coders from different continents that had never met in person. Around the same year, QuTiP developers began engaging more and more with the wider scientific ecosystem of Python, such as SciPy Japan (Tokyo) and at EuroScipy 2018 (Trieste) and 2019 (Bilbao).

QuTiP has been supported over the years by various academic institutions, from RIKEN to Chalmers Technical University, to funding agencies in various countries and by non-profit organizations such as NumFOCUS, mainly through the Google Summer of Code program, and by Unitary Fund, as its first affiliated project.

Participation in the Google Summer of Code program, now in its third year, has been a huge success for QuTiP. Two of the previous years alumni remain highly active developers, and are on the admin team, and with three projects currently underway on a GPU-CuPy integration, a TensorFlow data layer, and a compiler for universal quantum circuit decomposition, it is an example of remote mentorship that works well for scientific open-source projects.

With the help of Unitary Fund, the QuTiP project has established a formal open-source governance and implemented a board and admin team that meets monthly to discuss software development and community actions. A series projects building upon QuTiP have been funded with Unitary Fund microgrants, such as:

QuNetSim, a quantum networks simulator by Stephen Diadamo, a PhD student at the Technical University of Munich
SQWalk, a stochastic quantum walk simulator by Lorenzo Buffoni, a PhD student at the University of Florence.
Krylov-based methods for optimal control and master equation solutions, currently being developed by Diego Wisniacki and collaborators from the University of Buenos Aires.

If you’d like to join the conversation, informal discussions are enabled by special channels on Unitary Fund’s Discord server, while the Google forum is active for support in debugging and other questions on physics. QuTiP recently participated in a distributed hackathon with paid bounties and swag organized by Unitary Fund, UnitaryHACK, which helped solve bugs, including an issue opened back in 2018 (!) and compensate both hackers and pull request reviewers. See you on July 29th!

Unitary Fund Q2 2021 Update: UnitaryHACK, new projects, Mitiq's new features

Wed, 07 Jul 2021 00:00:00 GMT

To the Unitary Fund community,

The quantum technology ecosystem continues to accelerate its growth with new investments [1][2] [3] and advancing technology [4][5][6]. At Unitary Fund we’ve continued to grow our existing programs around microgrants and mitiq and found exciting success with new experiments like unitaryHack. Decentralized, open communities are impressing and we believe we’ll see the same in quantum.

We continue to work hard to support the development of a vibrant, open quantum technology ecosystem. Thanks to all of you who have joined us in this mission.

New from Unitary Fund
Welcome Dan Strano and Vincent Russo to the Unitary Fund team! They’re working on a new (and so far un-announced) Unitary Labs project :)
About Mitiq:
We released versions 0.8.0 through 0.9.3 of Mitiq, adding many new collaborators from the community. Thanks for your contributions!
We implemented Clifford Data Regression, a new error-mitigation technique [arXiv] and further deployed probabilistic error cancellation in the code base.
We hosted unitaryHACK, our first decentralized hackathon with bounties on 19 open source quantum projects:
>35 hackers; 64 contributions in two weeks
50% of hackers new to Open Source, ~100% new to quantum open source
Special thanks to Xanadu, PASQAL, and DoraHacks for sponsoring extra bounties.
We reached almost 1,000 folks on the Unitary Fund Discord server
We’ve co-authored two new papers in quantum open source software: One on the new QuTiP’s features for pulse-level control of quantum circuits (arXiv:2105.09902) and one on Pulser, a new library to simulate Rydberg-atom quantum processors (arXiv:2104.15044).
We hosted Loïc Henriet in our Quantum Software Talks Series where he spoke about Pulser: an open source library for pulse simulation and design for neutral atoms
We spoke about Unitary Fund to many new communities! At OneQuantum Africa summit; QuBites; Codestories; Diversity in Quantum computing by QubitxQubit; Screaming in the cloud podcast; Portland Quantum Computing Meetup; Galileo Galilei Institute's Summer School on Quantum Computing and Sensing
We had some great digital swag for unitaryHACK and a Mitiq logo designed by Frances Poblete!
6 New Grants
To Lorenzo Buffoni, to develop SQWalk, A Stochastic Quantum Walk simulator based on QuTiP.
To Jonas Schwab and the ALF collaboration, to develop pyALF, the Python interface of the ALF project, a powerful and flexible package for Quantum Monte Carlo simulations of fermion systems.
To the teams at Orange Quantum Systems and Qblox, to develop Quantify Core, an open-source Python-based data acquisition and experiment control platform for quantum computing and solid-state physics experiments. It is built on QCoDeS and is a spiritual successor of PycQED.
To Reem Larabi to add more visualization improvements to the %debug tool in Q# by expanding its current set of controls.
To Diego Ariel Wisniacki, Martin Larocca, Emiliano Manuel Fortes to develop Krylov and K-GRAPE algorithms integrated with QuTiP. [arXiv]
To Alessandro Luongo and Armando Bellante to develop Quantumalgorithms.org an open-source web book collecting in an organized manner lectures notes around quantum algorithms for information processing, data analysis and machine learning.
News from UF Projects
The pyMatching project posted a new preprint and released a new version v0.3.0
Qubit by Qubit's virtual quantum computing workshops reached over 2,000 middle and high school students in 18 different states in spring 2021. After the workshops, 85% of students wanted to learn more about quantum computing!
QuNetSim had their paper accepted in IEEE Transactions in Quantum Engineering and the Interlin-q project posted a new preprint.
QWorld hosted Quantum Science Days, their first QSilver quantum programming workshop. and added new QCousins: QRomania, QEgypt, QIrelend, and QZimbabwe. They are organizing a global summer school between July 26 and August 8 and a new edition of their internship program.
QuTiP’s quantum information processing and quantum programming features are updated and bundled in a stand-alone library, qutip-qip, whose v. 0.1 is released on PyPI.
Quantum Community Updates
IBM hosted QC40: The Physics of Computation, a virtual conference commemorating the 1981 event which kicked off the field and ran the 2021 IBM Quantum Challenge.
QHack, the quantum machine learning hackathon took place with open talks and a competitive hackathon
Pennylane versions 0.15 and 0.16 were released with the latter including unitaryHack contributions
The Quantum Coalition Hack was hosted by Yale and Stanford student
Qiskit Aqua refactored its application modules and the Qiskit runtime was launched.
IEEE Quantum Week announced its program for 2021 that includes workshops/tracks on open quantum hardware, quantum intermediate representations, and quantum workforce & society that Unitary Fund is helping organize.

Best wishes to all of you,

Will and the Unitary Fund Team

Unitary Fund Q1 2021 Update: New grants and a Mitiq release driven by the community

Tue, 13 Apr 2021 00:00:00 GMT

Unitary Fund Q1 2021 Update: New grants and a Mitiq release driven by the community

Unitary Fund is a non-profit working to create a quantum technology ecosystem that benefits the most people.

13 April, 2021

To the Unitary Fund community,

It's been an amazing year at Unitary Fund so far: we've grown our microgrant program, launched a new streaming talk series, and opened up a Discord server for the community.

We continue to work hard to support the development of a vibrant, open quantum technology ecosystem. Thanks to all of you who have joined us in this mission.

New from Unitary Fund
We are running UnitaryHack, our first quantum open source hackathon with SWAG and BOUNTIES, on May 14-30th!
Welcome Olivia!** Our newest team member, Olivia has joined as our new Administration to help us grow and optimize Unitary Fund 's programs.**
Help wanted: We are hiring for technical staff positions. We’re not only interested in quantum experienced applicants, but also diverse applicants with full stack web experience.
If you missed it, read our 2020 Annual Report here.
About Mitiq:
We continue to develop in the open, and now at its 0.7.0 release on PyPI. You can join our community call on Fridays at 2:30pm ET on Discord ( discord.unitary.foundation)
Mitiq v.0.7.0 contains several contributions from the community! Thanks to @yhindy for adding a method to parametrically scale noise in circuit, to @elmahmoud for adding a factory for zero noise extrapolation, to @aaron-robertson and @pchung39 for adding Qiskit executors with depolarizing noise to the utils, to @purva-thakre for several fixes and improvements. Thanks also to @BobinMathew and @marwahaha for typo corrections.
We added probabilistic error correction (PEC) to the quantum error mitigation techniques.
Everyone can now contribute examples to the documentation directly with Jupyter Notebooks thanks to a new MystNB-based infrastructure.
We had more guests on Quantum Software Talks Series on Twitch, with recordings uploaded to Youtube.
We hosted Intro to QuTiP: A Quantum Toolbox in Python by Shahnawaz Ahmed and Intro to QuNetSim: A Software Framework for Quantum Networks by Stephen DiAdamo.
We hosted 3 research talks on Discord:
“Exponential Error Suppression for Near-Term Quantum Devices”, by Bálint Koczor.
Chen Wang, “Protecting a bosonic qubit with autonomous quantum error correction”, by Chen Wang.
AMA on gate tomography and randomized benchmarking, by Cassandra Granade.
Sarah from the Unitary Fund team gave an interview on quantum computing
Andrea and Ryan spoke on our error-mitigating research at the APS March Meeting
7 New Grants
To Goutam Tamvada and Douglas Stebila to develop VeriFrodo, an open-source package implementing a lattice-based quantum-resistant cryptographic algorithms in Jasmin within the Open Quantum Safe project.
To Owen Lockwood to develop a software package using classical deep reinforcement learning to improve quantum optimization, both for quantum simulations and hardware integration.
To Daniel Stilck França to develop a software package that will help benchmark the limitations of noisy quantum devices for solving optimization problems. [arXiv] [ QIP talk on the technique].
To Rhea Parekh and Stephen DiAdamo to further develop Interlin-q, a distributed quantum-enabled simulator integrated with QuNetSim.
To Dariusz Lasecki to build an open-source Python library that delivers easy-to-use high-quality pre-trained machine learning models to predict good QAOA starting parameters for selected classes of problems.
To Oscar Higgot, to continue developing and maintaining PyMatching, a Python package for decoding quantum error correcting codes with minimum-weight perfect matching (MWPM).
To Nicola Mosco, to develop HomodyneCT, a software package for medical diagnostics that uses a quantum-tomography-inspired technique for state reconstruction in order to reduce the radiation dose patients receive.
News from UF Projects
A new QuTiP related job posting: the position to join the QuTiP dev team can be fully remote for 2022!
QuTiP is also participating in Google Summer of Code 2021! Deadline for student applications is in one week.
https://quantumflytrap.com/ is growing with a new CNOT game and their first intern. They also posted a new blog post demoing interactive visualizations for qubits.
QRand has released v0.2.0
QWorld continues to expand globally and now has chapters in 14 countries!
PyZX is used in new papers on the WolframPhysics project on foundations and in quantum machine learning
Qubit x Qubit hosted a diversity in quantum computing conference
Quantum Community Updates
QHack was held from February 17th, 2021.
QOSF completed the second cohort of their mentorship program. Several Unitary Fund projects were involved.
Qiskit has launched a mentorship program
Unitary Fund advisor Michal Stechly started a new podcast "Noisy Intermediate-Scale Podcast".
IBM Quantum has released more open source software: qiskit metal for designing superconducting quantum hardware; active reset; and their new software roadmap.
QC40 will be held in May to celebrate 40 years of QC Research

Best wishes to all of you,

Will and the Unitary Fund Team

Announcing unitaryHACK 2021

Thu, 08 Apr 2021 00:00:00 GMT

It has been already a super busy year with tons of new grants, events, and friends joining our Discord, but we decided to do even more!

🥁 Announcing unitaryHACK 2021! 🥁

<div align="center"> <img src="https://res.cloudinary.com/dcz4ywuer/image/upload/v1690842430/nbupxcdy6lbcoggzdapd.png" style="width: 70%; height: auto;" /> </div>

Quantum computing isn’t just unitary, it’s open source!

The Unitary Fund is proud to host our first quantum open source hackathon with SWAG and BOUNTIES on May 14-30th!

Over $2K in bounties for tagged issues in quantum open source projects
Digital swag for all participants that make approved Pull Requests (PR)s
Random participants that make 1 quality Pull Request (PR)s to a participating open source project will receive a swag pack in the mail!*

SIGN UP HERE!

We'd like to thank our sponsors Xanadu and Pasqal for helping to make this event a reality 💖

Would you like to help us support more contributors and projects? [email protected]">Get in touch with us, and we would love to collaborate!

Unitary Fund Q4 2020 Update: Quantum Software Talks, Mitiq updates, and more grants

Fri, 05 Feb 2021 00:00:00 GMT

To the Unitary Fund community,

Last year we ended the year by awarding 20 micro-grants, of which five in Q4. We’re proud of the impact the program is making. You can read more about our milestones and activities in the 2020 Annual Report. We have lots of updates: We collaborated with the QOSF to inaugurate and award the Wittek Quantum Prize for open-source software, we inaugurated the Quantum Software Talks series on Twitch, and now there are more than 270 members on our Discord server.

We’ve kept developing Mitiq, the quantum error mitigation toolkit in Python developed at Unitary Labs, now with six contributors from the quantum ecosystem.

We continue to work hard to support the development of a vibrant, open quantum technology ecosystem. Thanks to all of you who have joined us in this mission.

New from Unitary Fund

Help wanted: We have put out an Administrator position job post: help us spread the word.
If you missed it, read our 2020 Annual Report here.
Mitiq: We continue to develop the library, now at its 0.4.1 release on PyPI. You can join our community call on Fridays at 2:30pm ET on Discord ( discord.unitary.foundation) Here is a video of Ryan LaRose’s talk on Mitiq, including ongoing work to implement probabilistic error cancellation (PEC)
We painstakingly reviewed nominations from a great pool of candidates and awarded the Wittek Quantum Prize for quantum open source software, in collaboration with QOSF. Congratulations to Roger Luo for winning, and for all the hard work they have put in to making the quantum open source ecosystem better! You can read the article from TQD on the Prize announcement and award.
We began streaming the Quantum Software Talks Series on Twitch, with recordings uploaded to Youtube. We hosted Daniel Strano (Qrack), Alex McCaskey (QCOR).
Read about our collaboration with Pasqal on Pulser, a pulse-level control software library for atom-based quantum processors.

New Grants

To the QWorld team, a follow-up grant to be incorporated as a non-profit organization and step up their activities. [arXiv]
To the team at Qubit By Qubit, to develop courses and materials to educate a diverse ecosystem of open source quantum contributors.
To Pedro Rivero Ramírez for QRand, a multi-platform quantum random number generator library integrated with numpy.
To Jacob Miller for a PyTorch toolbox for matrix product state models.
To Rochisha Agarwal and Natansh Mathur to create a Quantum Machine Learning Textbook with integrated code and visualization.

News from UF Projects

qRAM project: The package is officially available through Nuget.org
Talks at Portland quantum computing meetup and at the University of Technology Sydney
QSurface (formerly OpenSurfaceSim) released
QWorld adds new chapters and incorporates as a non-profit
Quantum Flytrap launched by Piotr and Klem
Qrand launches first version

Quantum Community Updates

Podcast from Travis Scholten from the IEEE Quantum Week
QHack will be held from February 17th, 2021

Best wishes to all of you,

Will and the Unitary Fund Team

Celebrating quantum open-source software contributors: Announcing the 2020 Wittek prize winner with QOSF

Mon, 01 Feb 2021 00:00:00 GMT

Celebrating quantum open-source software contributors: Announcing the 2020 Wittek prize winner with QOSF

1 February, 2021
Unitary Fund Team

Over the past six months, we have collaborated with the Quantum Open Source Foundation (QOSF) to help them design, roll-out and award the 2020 Wittek quantum prize to an individual making, with their work, exceptional contributions to the quantum open-source software ecosystem. We are glad to share the announcement of the 2020 Wittek quantum prize, which is awarded to Roger Luo.

A video inteview can be found here. Roger will also be interviewed live on 11 February, 2021, at 9am PST/12pm EST, on Unitary Fund's Twitch channel, tune in to ask questions in the chat.

We'd like to thank the Unitary Fund Advisory Board, which has been volunteering time to review nominations, together with the Tech Team, from an exceptional pool of candidates. This prize acknowledges the importance of the impact that individuals can have on the open-source ecosystem, for the benefit of the whole quantum science community.

Advancing open science with Pasqal's atom-based quantum computers

Fri, 22 Jan 2021 00:00:00 GMT

Author links: Peter Karalekas and Nathan Shammah

We are glad to announce that last year Unitary Fund provided technical advisory to the Pasqal quantum software team, on their freshly released Pulser package, an open-source toolkit to emulate atom-based pulse-level quantum systems. Pulser is powered by and integrated with QuTiP – and will soon provide pulse-level access to atom-based quantum processors from the cloud. You can read more about it in Pasqal’s press release.

Unitary Fund 2020 Annual Report

Mon, 18 Jan 2021 00:00:00 GMT

Unitary Fund 2020 Annual Report

18 January, 2021

To the Unitary Fund community,

While 2020 was a challenging year in many ways, we're glad of the progress that we made helping the quantum tech ecosystem grow faster, better, and to the benefit of more people.

As reviewed in our 2020 annual report, last year:

We supported 20 more projects with microgrants, spanning from software to education and new community development.
We set up our advisory board with 15 amazing volunteers that review and mentor our projects
We created Unitary Fund’s technical team, hiring six top experts in open-source quantum software.
We built and released Mitiq, the world’s first error-mitigating quantum compiler. It is now integrated with most existing frameworks and already used for two research papers.
With QOSF, we launched the Wittek Prize for open source software
We launched our discord and quantum software seminar
QuTiP became our first affiliated project, and we helped support it's new governance model

We’ve been impressed by the resilience of the quantum open-source community and the effectiveness of our operating model.

How can you help? Help spread the word about Unitary Fund and our microgrant program to new communities across the world. We could especially use help reaching out to communities that are typically underrepresented in quantum technology.

We're always happy to receive feedback on our programs or to answer questions. Send an email to [email protected]">[email protected].

Thanks to all of you for your commitment, excitement, and support.

Looking forward to 2021!

-Will and the Unitary Fund Team

Unitary Fund partners with IBM Quantum to provide hardware access to Unitary Fund awardees

Tue, 24 Nov 2020 00:00:00 GMT

Unitary Fund is pleased to announce IBM Quantum has granted special quantum computing access to the Unitary Fund community. Thanks to this partnership, recipients of a Unitary Fund micro-grant will receive the following benefits:

A larger share of the queue on open IBM Quantum systems.
Access to additional, non-open systems.
The ability to book dedicated time on a system.

These benefits will spur further innovation in the quantum computing space, and directly enables Unitary Fund's mission of helping create a quantum technology ecosystem that benefits the most people. We are particularly pleased to be able to extend these benefits to the explorers in quantum technology who do not have a formal academic affiliation.

Moreover, through this partnership, our technical team at Unitary Labs will further benchmark Mitiq, our open-source quantum error mitigating compiler, on real quantum hardware.

The Unitary Fund team would like to thank IBM Quantum for their support, in particular Sebastian Hassinger, IBM Quantum Research & Ecosystem Partnerships Lead.

Unitary Fund Q3 2020 Update: Mitiq and new grants

Sat, 03 Oct 2020 00:00:00 GMT

To the Unitary Fund community,

We are growing and evolving! This quarter we launched Mitiq - the first open source project incubated at Unitary Labs - and funded six new projects ranging from new educational platforms to optimal quantum compilers and software for quantum RAMs. We saw more micro-grant applications this quarter than ever before and are thrilled to see the interest in our program continue to grow.

We continue to work hard to support the development of a vibrant, open quantum technology ecosystem. Thanks to all of you who have joined us in this mission.

New from Unitary Fund
Two articles covering our work in The Quantum Daily. [short article] [longer article]
We launched the first version of Mitiq, our open source error mitigating compiler. [arXiv] [github] [video overview]
We spoke about Mitiq and Unitary Fund at several venues.
Our paper on Digital Zero Noise Extrapolation was accepted to IEEE Quantum Week.
With help from our supporters at Strangeworks we upgraded our website: https://unitary.foundation/
We launched our YouTube channel.
Peter Karalekas and Sarah Kaiser joined the UF team!
New Grants
To Olivia De Matteo and Sarah Kaiser to build and optimize an open source Q# library for quantum RAM. [github]
To Lia Yeh and the fullstackquantumcomputation.tech team to build community-driven open-source educational resources for quantum computing. [site] [discord]
To Daniel Tan to develop and open source the Optimal Layout Synthesizer for Quantum Computing, OLSQ. This compiler beats other benchmarks on optimal layout of computational qubits onto physical qubits. [arXiv] [ arXiv]
To Spencer Churchill to write Quantum Tales, short stories with code where quantum algorithms are applied to solve tasks.
To Mark Cunningham to explore applications of quantum computing to medical imaging.
News from UF Projects
The NYCQuantum Meetup hosted talks from several UF projects from around the globe.
YaoLang released support for its first circuit optimization pass based on ZXcalculus with help from the other unitary fund project PyZX.
QuNetSim released a new video overview on quantum network simulation
Toqito released a new video overview along with new features for state distinguishability scenarios and tools to detect whether a given state is entangled or separable. More details here.
Sarah Kaiser spoke about the qRAM in q# project
Quantum Programming Studio adds support for Amazon Braket
"Robust data encodings on quantum classifiers" from the NISQAI project was published in Physical Review A
The fsqc.tech launched their website for open-source quantum science and quantum computing education, and Discord server for anyone interested in Quantum Universal Education. [contributor form] [recent workshop on applying to graduate programs]
Misc
IEEE Quantum Software Workshop - Several talks from UF folks and advisors in this session. This will be virtual so hopefully many of you can attend!
UF Advisors spoke on podcasts [Travis Scholten on IEEE podcast] [Michal Stechly on QC Now]

Best wishes to all of you,

Will and the Unitary Fund Team

Quantum Computing Resources for High School Students

Tue, 21 Jul 2020 00:00:00 GMT

Over the past few years, interest in the field of quantum computing has grown dramatically, especially in communities of high school students! While lots of quantum-related educational material is scattered around the Internet, it is oftentimes difficult to find curated, accessible, and high-quality resources. This blog post aims to (hopefully) provide a comprehensive list of quantum computing-related resources and opportunities for high-schoolers. For some context, I just graduated from high school, and have been interested in quantum computing for about two years now. I have a lot of personal experience self-studying the field, and I have used/participated in some of the resources listed below!

Unfortunately, many of the programs that will be discussed have already closed their registration, or have already concluded for this year. However, many will likely end up taking place annually, so be sure to keep an eye out for any announcements or further information about next year’s cohorts!

Programs
QCSYS @ the Institute for Quantum Computing

The Quantum Cryptography School for Young Scientists (QCSYS) is a program run by the Institute for Quantum Computing in Waterloo, Ontario that teaches high school students the basics of quantum cryptography and quantum computing.

Course material from QCSYS is also available online.
ISSYP @ the Perimeter Institute

The International Summer School for Young Physicists is a program run by the Perimeter Institute for Theoretical Physics, also located in Waterloo. For two weeks, ISSYP teaches high school students the basics of many concepts in modern physics (not all relating to quantum computing). I participated in this program last summer, and I had an amazing experience. I really can’t recommend it enough!

Like QCSYS, a lot of ISSYP's course material is available online.
Quantum for Anybody

This course introduces the essential concepts used in quantum computing and explains how it's different from regular computing. Made by Brian Ingmanson, a former middle school teacher, you will learn what quantum computers can (and can't) do right now and guide you through running code on a real quantum computer. This is a true beginner level course, so no linear algebra or tough equations will be used. That being said, you will not have enough background to go get a job after this course! You'll be able to understand what quantum computing is, and know where to go if you want to learn more.
The QOSF Mentorship Program

This is a program run by the Quantum Open Source Foundation where participants are paired with quantum computing experts, and, under their supervision, complete a project relating to quantum computation. While the program isn't specifically targeted towards high school students, they certainly can participate.
MIT/Coding School Course

MIT and Coding School recently launched a summer school targeted towards high school and first-year university students, with the goal of exposing the participants to introductory quantum theory, as well as practical ideas in quantum computation.
Qiskit Summer School

The Qiskit Summer School is an online two-week program that includes lectures and virtual labs, focusing on many areas of quantum computation, from quantum algorithms to quantum hardware.
Q-Munity QuBes Camp

The QuBes Camp is a 2-week virtual summer camp specifically targeted towards high school and undergraduate students who want to begin learning about quantum programming.
Shabani Lab Mentorship Program

This is a virtual program run by NYU, open to high school and undergraduate students. The program aims to teach the participants the basic theory behind quantum devices and quantum programming.
QWorld QJunior

QWorld (a Unitary Fund grant winner!) runs workshops that teach high school students the basics of quantum programming.
University of Maryland Advanced Summer Girls Program

The University of Maryland offers a summer physics summer program targeted towards high school girls.
Educational Resources
FermiLab Material

FermiLab has released education material and other resources on the basics of quantum computing, at a high school level.
The Qiskit Textbook

The Qiskit textbook is an online textbook that teaches quantum computation through writing code with Qiskit. The subjects that the book dives into are very broad, ranging from basic linear algebra for quantum computing, to the basics of quantum algorithms, to near-term algorithms, quantum machine learning, and quantum hardware.
The PennyLane QML Gallery

The PennyLane QML Gallery is a collection of tutorials, all relating to concepts in near-term quantum algorithms and quantum machine learning. In addition to this, there are sections of the website that dive into the basics of QML and variational quantum algorithms, which are fantastic resources for students who are taking their first steps into the field.
The Brilliant.org Quantum Computing Course

This course, available through Brilliant.org, was created by Microsoft Quantum and X, the Moonshot Factory, to teach people the basics of quantum computation, quantum programming, and even some advanced concepts near-term algorithms and quantum machine learning. I have not taken this course, but I love Brilliant, so I recommend checking this out!
FutureLearn Quantum Computing Course

This is an online course run by Keio University, with the aim of teaching participants the basics of quantum computing in an accessible, mostly non-mathematical way.
The Quantum Atlas

The Quantum Atlas is organized like a glossary, but it offers more than just definitions. It features cartoons, animations, interactive elements and short podcasts—a multimedia approach intended to enrich your exploration of the quantum world.

Some Final Advice

The best personal advice that I can give to a quantum-curious high school student is to be active in the learning process. Absorbing information through reading/listening/watching is great, but to gain an even greater depth of understanding, it is very important to engage the material through critical thinking and problem solving. A fantastic way to "engage" when learning about quantum computing is to use the amazing quantum software tools that exist, like Qiskit, Forest, Q#, PennyLane, Cirq, and more, to simulate different quantum algorithms. You can even run your algorithm on real quantum devices for free! The courses and resources above are all amazing, and convey ideas with great clarity and accessibility. If you combine this with building things, solving tough problems, and maybe even simulating a few quantum circuits, not only will you learn more, but you’ll have much more fun while doing it!

Unitary Fund Q2 2020 Update: New advisory board and new grants

Tue, 07 Jul 2020 00:00:00 GMT

To the Unitary Fund community,

We’re excited to share new updates and developments from Unitary Fund this quarter. As many of us settle into working remotely, we’re grateful that our decentralized model has been robust. We’re especially glad to have been able to make a microgrant award to support a student in Hong Kong whose summer research support was lost when COVID shut down their university.

We continue to work hard to support the development of a vibrant, open quantum technology ecosystem. Thanks to all of you who have joined us in this mission.

This quarter we welcomed a fantastic expert advisory board, submitted our first research preprint from Unitary Labs, and made micro-grant awards to 5 new projects.

New from UF.
We welcomed our 15 member advisory board. They will be helping review grant applications, mentor projects, and advise on our research program. Thanks to all of them!
We posted our digital Zero-noise extrapolation paper to arXiv https://arxiv.org/abs/2005.10921
Will Zeng gave an invited talk on the Digital Zero-noise extrapolation work at QRE 2020.
Nathan Shammah spoke about our work at Le Lab Quantique and QWorld.
New Grants.
To Mark Shui Hu to further develop OpenSurfaceSim, a simulator package for surface codes. The grant will improve visualization methods and facilitate the collaboration of an open, modular platform for surface code simulations.
To Roger Luo to continue the development of Yao.jl, a software for solving practical problems in quantum computation research. The grant will support Yao's new DSL compiler development, which includes an extensible DSL infrastructure, Julia-based frontend, Julia AST and QASM code generator, and a quantum circuit simplification infrastructure based on pattern matching.
To Dariusz Lasecki to build an open source QAOA library and examples using Q#.
To Muhammad Usman Farooq for a research project at the intersection of quantum information theory and quantum communication complexity supervised by Prof. Penghui Yao.
News from UF Projects.
https://github.com/Quantum-Game/bra-ket-vue released by Klementyna Jankiewicz and Piotr Migdal. This is working in the new beta release of https://quantumgame.io/. Check out also Piotr’s demo article in RMarkdown Distill.
QuTIP minor release 4.5.0 (January 2020) introduced the major update of the qip.noise module for pulse-level quantum circuits and several enhancements. The micro update 4.5.1 (May 2020) fixes several bugs.
Misc.
Quantum Computing Now is a new podcast with Ethan Hansen that’s great for folks new to the field and looking to learn more. With Unitary Fund’s support, Ethan has upgraded his podcasting setup and we encourage you to reach out if you’d be interested in being on the podcast.
IEEE QC for renewable energy workshop.
IEEE Quantum Software Workshop - Several talks from UF folks and advisors in this session. Likely this will be virtual so hopefully many of you can attend!

Best wishes to all of you.

Be well,

Will and the Unitary Fund Team

Unitary Fund Welcomes New Advisory Board

Mon, 22 Jun 2020 00:00:00 GMT

Unitary Fund has grown quickly since its inception as a small microgrant program. We’ve now awarded more than 22 project grants across 14 countries and 4 continents, resulting in 6 publications, more than 11 open source libraries, a venture funded startup, and several folks working full time in the field who got their start with a Unitary Fund grant. Open source projects supported by Unitary Fund have more than 31 contributors, 570 stars and 95 forks on github. All this has happened on just the $40k so far granted.

We believe that these results speak for themselves, and we’re ready to grow them further. To help with this, we have invited 15 members of the quantum technology community to join our volunteer advisory board. Many of them have already been helping behind the scenes at Unitary Fund, reviewing applications and mentoring projects. The group also includes Ntwali and Michał, who themselves were some of the first of our grant winners.

They are all experts in their fields, and they bring experience across the quantum technology stack: various hardware, programming languages etc. They work at academic research centers, national labs, corporate research divisions, and startups, both collaborating on large open source projects and having authored personal projects. Importantly, they all share our commitment to growing the community of open science and technology.

The advisory board will help source and review grant applications, mentor projects, and provide technical advice on Unitary Fund’s research program.

We are grateful for their help and are excited to bring them on board to recognize their contribution.

The Unitary Fund Advisory Board:

Alex McCaskey is a research scientist in the Computer Science and Mathematics Division at Oak Ridge National Laboratory. He serves as the Software Lead for the Quantum Computing Institute at ORNL and is the Project Lead for the XACC quantum framework and the QCOR quantum-classical C++ compiler. He received his Masters in Physics from Virginia Tech and BS degrees in Physics and Mathematics from the University of Tennessee.

Amy Brown is a PhD student in quantum computing at USC. She was formerly lead quantum solutions engineer at Rigetti Computing, where she supported and developed the open source quantum programming community. She has spoken on quantum programming at many hackathons and workshops in our community.

Cassandra Granade is a senior research software development engineer on the Microsoft Quantum team, where she leads the libraries effort for the Quantum Development Kit. After completing her PhD in quantum computing at the University of Waterloo, Cassandra worked as a postdoctoral researcher at the University of Sydney before joining Microsoft in 2017.

Christa Zoufal is a pre-doctoral researcher in the Quantum Technology group of the Science & Technology department at IBM Research-Zurich. She received an MSc in Physics from ETH Zurich in 2018. Her current research focuses on the exploitation of quantum information theory within the context of machine learning and optimization problems.

Josh Izaac is a physicist at Xanadu Quantum Technologies Inc., where he is a lead developer of the open source libraries PennyLane and Strawberry Fields. He received a PhD in quantum computation from the University of Western Australia. His research interests mainly lie in the characterisation and applications of quantum walks, with specific focus on network analysis algorithms.

Mark Fingerhuth is the co-founder and head of R&D at ProteinQure, a startup using machine learning and quantum computing for the computational design of protein-based drugs. He is co-founder of the Quantum Open Source Foundation (QOSF) and a graduate, as quantum entrepreneur, of the Creative Destruction Lab.

Michał Stęchły is a quantum software engineer at Zapata Computing where he works on research and software tools for variational quantum algorithms. He is also involved in education and popularization of QC through his blog Musty Thoughts and engagement with the Quantum Open Source Foundation.

Nathan Killoran is the Head of Software & Algorithms at Xanadu Quantum Technologies, where he leads the development of the open-source software libraries PennyLane and Strawberry Fields. He received a PhD in Physics from the Institute for Quantum Computing at the University of Waterloo, and served postdoc terms in the fields of quantum computing and deep learning.

Ntwali B. Toussaint is a quantum software engineer at Zapata Computing. He is working on making quantum computers available to masses and easier to use for practitioners by creating programming languages for quantum computers. At Zapata, he works on the platform, compilers, and low-level software to help improve algorithm performance.

Peter Karalekas is a quantum software engineer and was previously the quantum software team lead at Rigetti Computing, during which he maintained the open-source library pyQuil and managed development of the Quantum Cloud Services platform. He has been working on quantum software since studying Physics and Computer Science at Yale.

Xiu-Zhe (Roger) Luo is a graduate student at the University of Waterloo and Perimeter Institute Quantum Intelligence Lab (PIQulL), Canada. His research interest lies in the intersection of machine learning and quantum physics with numerical approaches. He is also one of the creators of the open-source quantum software library Yao.

Shahnawaz Ahmed is a graduate student at the Wallenberg Center for Quantum Technology at Chalmers University, Sweden. His research interest lies in the intersection of machine learning and quantum computing. He also works on numerical approaches to solve problems in open quantum systems and is a member of the open source quantum toolbox in Python QuTiP development team.

Sukin Sim (Hannah) is currently a PhD student in Professor Alán Aspuru-Guzik’s research group at Harvard University and an intern at Zapata Computing. Hannah’s research interests lie in improving the performance of variational quantum algorithms.

Tomas Babej is co-founder and CTO at ProteinQure and one of the founders of the Quantum Open Source Foundation (QOSF). He is a contributor to several open-source libraries in science, such as Astropy, and has worked as a software engineer for RedHat.

Travis L. Scholten is a quantum computing applications researcher at IBM Quantum, where he also works on collaborations for the IBM Quantum Network. He received his PhD on quantum characterization, validation, and verification from University of New Mexico and a BS in Physics from Caltech. He has been advising the Unitary Fund's grant program since its inception.

Unitary Fund Q1 2020 Update: new team members and new grants

Thu, 02 Apr 2020 00:00:00 GMT

Dear Unitary Fund community,

These are trying times for everyone and we send well wishes to all of you. Hopefully, we can brighten your day with a bit of good news from developments in the Unitary Fund community this quarter.

We continue to work hard to support the development of a vibrant, open quantum technology ecosystem. Thanks to all of you who have joined us in this mission.

This quarter we greatly expanded the Unitary Fund team, welcoming the first members of our Unitary Labs group. We funded new projects and helped run the 2020 version of the quantum open source workshop at FOSDEM. You can read more about all these updates in the following links:

Unitary Labs. Our blog post on our new Unitary Labs research team: Nathan Shammah, Andrea Mari, and Ryan LaRose. We are grateful to the US Department of Energy and IBM for helping support our research work. We’re working on open source tools to make quantum programs more robust to noise. More on this to come.
New grants.
- To Vincent Russo to support toqito, an open source Python toolkit for quantum information theory with extra functionality to study non-local games. [Github]
- To Klementyna Jankiewicz and Piotr Migdal to develop widgets that embed visualizations of quantum states and ops into blog posts, interactive textbooks, and explorable explanations. These are extensions from their work on a new version of QuantumGame. [ Github]
- Two other soon to be announced grants.
QuTiP. The Quantum Toolbox in Python is one of the most used and most useful quantum software packages out there. Further it is developed as an independent open source project. With Nathan, one of QuTiP’s lead developers, joining the Unitary Fund team, we are excited to support it. We’re starting by offering support to suggested projects that contribute to QuTiP. You can read more about these projects on our website.
FOSDEM 2020. We again partnered with the Quantum Open Source Foundation to run a quantum open source workshop at FOSDEM 2020. All the talks, including 5 by Unitary Fund grant winners, are available online here.
News from UF Projects.
- Carlos Bravo-Prieto’s et al. paper, “Scaling of variational quantum circuit depth for condensed matter systems” was put on the arXiv. His was the first project ever funded by Unitary Fund!
- QRack updated their benchmarks and demonstrate impressive performance. They also include some very interesting results on simulating supremacy-style circuits.
Q4Climate. We became early supporters of the Q4Climate initiative.

Best wishes to all of you.

Be well,
Will and the Unitary Fund Team

Introducing the Technical Team: Unitary Labs

Tue, 24 Mar 2020 00:00:00 GMT

24 March, 2020
Author: Nathan Shammah

I’m thrilled to be joining the team at Unitary Fund. This announcement gives me an opportunity to share my journey here and introduce the rest of the team.

Around three years ago I was introduced to the development of open-source software in science and have since fallen in love with it, finding in its inherently collaborative structure a strong motivation that reframed my research modus operandi.

I would have never imagined I’d become a core developer of QuTiP, the Quantum Toolbox in Python, a popular library launched in 2012. I’m a theoretical quantum physicist interested in many-body dissipative quantum systems and the description of noise in realistic devices. For me, QuTiP is indeed a quantum optician’s Swiss Army knife.

In the Summer of 2017, I began writing some numerical simulations exploiting permutational symmetries to avoid the exponential increase in computational resources that is typical of many-body quantum systems. Together with Shahnawaz Ahmed, while we were both in Franco Nori’s group at RIKEN, we developed some code that evolved into a full-fledged open-source library that has since become a popular module in QuTiP.

I then moved on to help coordinate the community project in many directions, joining the small but devoted team of maintainers and discovering a wider and supporting community of users. I’ve since realized that by engaging with other communities in science and engineering we can accelerate the adoption of open-source software and make its ecosystem more sustainable.

These experiences have convinced me that we’re witnessing the rise of communities over products or other deliverables. I’d been looking for ways to pursue both my passion for quantum technologies and open source community building.

I was thus delighted by the opportunity to join Unitary Fund. Unitary Fund was launched as a way to support open-source software in quantum computing, with a no-strings attached micro-grant program that anyone can apply to. This is a blessing in an academic world that is experiencing skyrocketing bureaucracy.

Having worked with the QuTiP community, I saw the value of open-source software and gained the skills to contribute it. Unitary Fund gives me a platform to do this on a broader scale.

Moreover, Unitary Fund is now developing its own in-house research, Unitary Labs. We’re doing cutting-edge research with a multi-year timeline. The Unitary Labs team is proudly delocalized: working remotely may very well be the future of many jobs, and is especially suited in software-based research that aims at attracting top talent. Let me introduce the amazing new team at Unitary Labs, Ryan and Andrea, who I am honored to start working with.

Ryan LaRose is pursuing a dual degree PhD at Michigan State University. He previously interned at NASA Ames, IBM Research and Los Alamos National Laboratory, and is now also a resident at X – The Moonshot Factory. With both academic independence and creativity, Ryan is very active in the field of quantum software: I recommend his 2019 Quantum paper, which provides a comparative analysis of different open-source programming languages and libraries providing quantum computing simulators or hardware in the back-end. He contributes to various open-source libraries and is the creator of NISQAI, a project that previously received a Unitary Fund microgrant.

Andrea Mari is a polyhedric quantum physicist who, with over 40 publications under his belt, has made important contributions to the field of quantum information theory and quantum optics. For example, during his PhD at the University of Potsdam, together with Jens Eisert, Andrea derived a generalization of the Gottesman-Knill theorem to continuous-variable systems. Later on, as a research fellow at the prestigious Italian academic institution, Scuola Normale di Pisa, Andrea focused on quantum Gaussian channels and quantum thermodynamics, together with Vittorio Giovannetti and collaborators. Most recently, Andrea has been tinkering with open-source libraries and quantum machine learning, and while working remotely with Xanadu Inc., a Toronto-based startup, he has been developing new concepts and applications for hybrid classical-quantum neural networks, such as introducing in that context the idea of quantum transfer learning.

With complementary skills and experience, Ryan, Andrea, Will and I are working on in-house research to help the whole ecosystem. **Our mission is to build an open and inclusive quantum ecosystem. If you’d like to join us – we’ll all be reviewing micro-grant applications – you can apply here.

Unitary Fund Launches New Quantum Micro-Grant Program and Five-Year Research Collaboration funded by the DOE

Thu, 21 Nov 2019 00:00:00 GMT

Unitary Fund Launches New Quantum Micro-Grant Program and Five-Year Research Collaboration funded by the DOE

This blog post is hosted on Will Zeng's Medium blog. Read the original blog post here.

Open source quantum software at FOSDEM 19

Thu, 07 Feb 2019 00:00:00 GMT

Open source quantum software at FOSDEM 19

This blog post is hosted on Will Zeng's Medium blog. Read the original blog post here.

Unitary Fund: The first quarter

Tue, 16 Oct 2018 00:00:00 GMT

Unitary Fund: The first quarter

This blog post is hosted on Will Zeng's Medium blog. Read the original blog post here.

The Unitary Fund: Get $2,000 for your open source quantum computing project

Tue, 16 Oct 2018 00:00:00 GMT

The Unitary Fund: Get $2,000 for your open source quantum computing project

This blog post is hosted on Will Zeng's Medium blog. Read the original blog post here.