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.
Overview · Installation · Quick Start · Docs Hub · Benchmark Suite · Methodology · Report Format
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.
pip install "qontos-bench @ git+https://github.com/qontos/[email protected]"Note: Once published to PyPI, this will simplify to
pip install qontos-bench.
git clone https://github.com/qontos/qontos-benchmarks.git
cd qontos-benchmarks
pip install -e ".[dev]"
pytestCI validates both paths: the released-tag install (on main push) and the local-checkout install (on every PR).
# 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 | 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 |
Each benchmark is executed through the full QONTOS pipeline:
- Circuit normalization via
CircuitNormalizer - Execution via
LocalSimulatorExecutor(Qiskit Aer) - Fidelity computation:
F = (expected state counts) / total_shots
Pass threshold: 0.85. Default shot count: 8,192.
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.
- 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
{
"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}
}
]
}| 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 |
Built by Zhyra Quantum Research Institute (ZQRI) — Abu Dhabi, UAE