Trust · measure & certifyAT-005

Measure the budget. Certify what's real.

Characterization, monitoring & certification engine

Every quantum vendor grades its own homework, and every buyer takes the results on faith. Our engine measures hardware the way an operator measures a fleet — and answers the question the field keeps fighting about: is this device performing to spec, and is this workload genuinely hard for a classical machine?

We replace the one number with a diagnosis. For every classical explanation of what the device did, we weigh the two prices the diagram plots — cost, the classical resource it must spend (including the hidden bookkeeping a classical model has to invent), and distortion, the error that explanation has to accept. Where the cheapest classical explanation lands against the budget sorts the device into a four-way verdict: healthy and in spec, near a limit, drifting, or genuinely quantum. That last verdict has a hard backstop — once a device violates a Bell test, no classical model can match it, and the result can't be argued down.

The output of this assessment is the product: a four-way health read with a live drift monitor, and a signed certificate that a workload was hard for a classical machine. It's vendor-agnostic and runs on the data the hardware already emits.

THE TRUST DIAGNOSIS The two prices of explaining a device with a classical computer. cost — classical resource it must spend ↑ (incl. hidden bookkeeping) distortion — error a classical explanation must accept → capacity ceiling tolerance trustworthy budget proven-quantum line 1 Healthy / in spec 2 Near a limit 4 Drifting 3 Genuinely quantum CERTIFIED hard for a classical machine signed Vendor-agnostic · uses the data the hardware already emits · live drift monitoring.

Provisional filed (App. 64/070,738).

Inside the trust engine

The cost–distortion frontier.

For any quantum interface we compute two numbers: the cost of reproducing it with a classical (Boolean) model, and the distortion that model introduces. Plot them, and the hardware lands in one of four regimes. Inside the admissible rectangle — low cost, low distortion — a classical machine can keep up. Outside it, the device is doing something genuinely quantum. The verdict comes with a signed margin, so it's robust to calibration jitter, not a coin-flip at the boundary.

admissible classically reproducible distortion δ classical-embedding cost κ CΓ budget τΓ tolerance Pareto frontier genuinely quantum

From observability to certification.

The same engine runs as a live monitor. It watches a device's operating telemetry with anytime-valid statistics — alerts that stay sound no matter when you look — flags drift before a run is wasted, and decomposes an excursion into why it happened. Run it across many machines and you accumulate the one asset no one else has: comparative, cross-fleet measurement. That corpus is what turns observability into the neutral certification authority — the "UL / Moody's for quantum compute."

Datacross-fleet Trusttrack record Certifyneutral stamp you cannot certify hardware you have never measured
The science

Built on published math; already running on real data.

The cost-distortion frontier, the four-regime verdict, the classical-embedding test, and the anytime-valid wrapper are grounded in the company's published technical papers. The engine already exists inside our verification codebase, and an MVP runs daily against publicly accessible hardware — productizing it is consolidation, not invention from zero.

Reference E. S. Brooke, "Quantum Structure from Finite Enforceability: Hilbert Space and the Born Rule" — Technical Supplement (2026), Zenodo DOI 10.5281/zenodo.18439433. Cost–distortion frontier, Boole-polytope classical-embedding test, and martingale-safe sequential monitoring.
Patent-pending · provisional filed Engine partly built MVP running on public hardware data
Work with us

Want to measure — or verify — quantum hardware?

Design-partner pilots open now; certification follows the data.
ethan@admissibletech.com