pyramaterised is a framework for creating and measuring Parameterised Quantum Circuits (PQCs) in Python, by acting as a wrapper around the QuTIP library. A series of PQCs from the literature have been implemented using the framework alongside various collated capacity measures.

Simply run in your current (virtual) environment:

pip install pyramaterised

Check out example.py or tests.py for examples of the framework in action. To run tests,

python tests.py

A diagram of some of the circuits available in the library (custom circuits can be easily constructed). NPQC diagram from [1], XXZ and TFIM circuits adapted from [2] and fermionic circuit diagram from [3].

Capacity measures tell you how well an aspect of a PQC is performing, e.g, entanglement measures the amount of entanglement generated by the circuit, expressibility describes how well an N qubit circuit explores the N qubit Hilbert space.

• Entanglement
• Expressibility
• QFIM
• Effective Quantum Dimension
• Rényi Entropy of Magic
• GKP Magic
• Effective Hilbert Space - new measure based on finding the subspace that minimises a circuit's expressibility.

• Python: de-facto scientific programming language, interoperability with QuTIP important.
• Object oriented: circuits being comprised of layers of gates with similar shared behaviours seemed a good fit.
• Designed to allow users to create PQCs more easily than writing every gate by hand in QuTIP or similar program.

Thanks to the numpy, scipy, matplotlib and QuTIP libraries. Thanks to F. Roberts and T. Haug for their help.