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QONTOS

QONTOS Benchmarks

Reproducible evidence, methodology, and regression validation for the QONTOS platform.

The public proof layer for correctness claims across the SDK, simulator, and modular execution stack.

Visibility: Public Track: Evidence Status: Pre-release CI

Overview · Installation · Quick Start · Docs Hub · Benchmark Suite · Methodology · Report Format


Overview

QONTOS Benchmarks is the public evidence repo for the QONTOS platform. It contains benchmark definitions, execution methodology, report schemas, and reproducible outputs used to validate correctness, performance, and regression behavior across the public QONTOS stack. This repository is the reference point for public technical claims made by QONTOS.

Start with docs/index.md for the lightweight docs hub and the key benchmark evidence pages. For the canonical install and release policy across the public repos, use the shared policy.

Installation

Pre-release (current)

pip install "qontos-bench @ git+https://github.com/qontos/[email protected]"

Note: Once published to PyPI, this will simplify to pip install qontos-bench.

For contributors (local development)

git clone https://github.com/qontos/qontos-benchmarks.git
cd qontos-benchmarks
pip install -e ".[dev]"
pytest

CI validates both paths: the released-tag install (on main push) and the local-checkout install (on every PR).

Quick Start

# Run the full benchmark suite
python -m qontos_bench

# Run a specific benchmark
python -m qontos_bench --benchmark bell_pair

# Generate a report
python -m qontos_bench --report json --output results.json

Benchmark Suite

Benchmark Circuit Qubits Expected States Fidelity Threshold
Bell Pair H + CNOT 2 |00>, |11> >= 0.85
GHZ-3 H + 2 CNOT 3 |000>, |111> >= 0.85
GHZ-5 H + 4 CNOT 5 |00000>, |11111> >= 0.85
QFT-4 H + CU1 + SWAP 4 Uniform (16 states) >= 0.85
Bernstein-Vazirani H + CNOT oracle 4 |101> >= 0.85
H2 VQE Ansatz RY + CNOT + RY 2 All 2-qubit states >= 0.85
Random 5Q Mixed (depth=10) 5 All 5-qubit states >= 0.85

Methodology

Each benchmark is executed through the full QONTOS pipeline:

  1. Circuit normalization via CircuitNormalizer
  2. Execution via LocalSimulatorExecutor (Qiskit Aer)
  3. Fidelity computation: F = (expected state counts) / total_shots

Pass threshold: 0.85. Default shot count: 8,192.

What the benchmarks prove

These benchmarks validate pipeline correctness — that the ingest-normalize-execute path preserves circuit semantics. They are designed to detect regressions, not to measure hardware noise characteristics.

Measurement conditions

  • Backend: Qiskit Aer AerSimulator (noiseless statevector)
  • Shot count: 8,192 (configurable)
  • Fidelity definition: fraction of shots landing in expected states
  • All results are simulator-based until hardware QPU integration

Report Format

{
  "timestamp": "2026-03-23T12:00:00Z",
  "backend": "aer_simulator",
  "shots": 8192,
  "benchmarks": [
    {
      "name": "bell_pair",
      "qubits": 2,
      "fidelity": 1.0,
      "passed": true,
      "counts": {"00": 4096, "11": 4096}
    }
  ]
}

Related Repositories

Repository Description
qontos Flagship Python SDK
qontos-sim Simulators and digital twin
qontos-examples Tutorials and examples
qontos-benchmarks Benchmark evidence
qontos-research Research papers and roadmap

License

Apache License 2.0


Built by Zhyra Quantum Research Institute (ZQRI) — Abu Dhabi, UAE

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Reproducible evidence, methodology, and regression validation for the QONTOS platform.

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