Quantum Validation
Your quantum computer gave you an answer.
Is it right?
A structural post-processing layer for quantum output validation. Complements existing QCVV methods (Hellinger, XEB, RB) with additional structural metrics. Designed as a trust filter for individual circuit runs — not a replacement for system-level benchmarking.
Tested across 7 circuit types, 6 noise models, up to 16 qubits. Detects errors at 0.5% gate error rate.
The quantum verification gap
Classical simulation dies at ~50 qubits
The whole point of quantum computing is doing what classical can't. So how do you verify the answer if you can't simulate it?
Running it again doesn't help
Same noisy hardware, same noise. Repeating a broken experiment on a broken machine gives you two broken results.
Multi-backend makes it worse
Run the same circuit on IBM Eagle and IonQ Aria. Different answers. Is it the algorithm or the hardware? Current tools can't tell you.
There is already a comprehensive ecosystem of methods for quantum system characterization, benchmarking, and validation (RB, XEB, Quantum Volume, Hellinger fidelity). Our approach complements these as a structural post-processing layer — designed to assess the reliability of individual output distributions at the circuit-run level, where system-level benchmarks provide no per-shot guidance.
What structural validation detects
| Error Type | Detection | Verified Result |
|---|---|---|
| Stuck qubit | Instant | Fidelity drops 0.94 → 0.43 (one stuck qubit) |
| Gate calibration error | At 5% over-rotation | Fidelity 0.962, monotonic gradient |
| Depolarizing noise | At 0.5% error rate | Clear separation from shot noise |
| Wrong algorithm | Instant | 0.670 gap between correct and wrong circuits |
| Calibration drift | Continuous | Alarm at 1% error rate, monotonic degradation |
| Noise type | Per-run classification | 6 noise types distinguishable (0.260 cosine range) |
Try it yourself
Pre-computed quantum circuit outputs (Qiskit Aer simulator). Select a configuration and validate against a noise-free calibration reference. All analysis runs server-side via our API.
Who needs this
Quantum cloud providers
Route circuits to IBM, IonQ, Rigetti through your platform. When customers get different results from different backends, structural comparison tells you if it's the algorithm or the hardware.
Pharma & chemistry
Molecular simulation on quantum hardware. Wrong answer = wrong drug candidate = $100M wasted. Structural validation catches errors before wet-lab experiments begin.
Financial optimization
Portfolio optimization, risk analysis. Validate that the quantum output has the structural properties expected of a valid solution — before acting on it.
Quantum hardware vendors
Daily calibration monitoring. Continuous structural health checks. Automated alerts when hardware drifts. Noise type identification for targeted maintenance.
API
POST /v1/quantum/validate
{
"counts_reference": {"000": 4012, "111": 4180},
"counts_test": {"000": 3856, "111": 3901, "001": 142},
"n_qubits": 3
}
Response:
{
"verdict": "DRIFT",
"metrics": {
"cosine": 0.847,
"extended_fidelity": 0.841,
"coherence_score": 0.932,
"kl_divergence": 0.094,
"l2_distance": 0.0231,
"rank_overlap": 0.85
}
}Three endpoints: /validate (single run), /drift (sequential monitoring), /fingerprint (multi-backend comparison). Also available as MCP tools.
Pricing
Monitor
- Single-machine drift monitoring
- Sanity check per run
- Alert dashboard
- API + MCP access
Validate
- Everything in Monitor
- Cross-backend comparison
- Noise type fingerprinting
- Priority support
Enterprise
- Everything in Validate
- Embedded in your pipeline
- SLA guarantee
- Dedicated support
Get started
Send us a quantum circuit or measurement counts. We'll send back the structural report.