PRISM-Q · Research programme

Quantum, honestly.

We keep a quantum research lane open, we evaluate it under protocols fixed before the run, and we publish the result either way. Most of what we have published about quantum is negative. That is the point.

The position

A research lane, not a headline.

Quantum computing is real, and the marketing around it is mostly not. A firm that sells you a quantum claim today is selling you a hope. We would rather sell you the engine that works and tell you the truth about the rest — including when the truth is that our own quantum results lost.

What we do not claim

No quantum speedup or quantum advantage claim, today, on any workload.
No production result on this site comes from a quantum device. Production is classical.
No quantum device or simulator we have measured has cleared our bar on a customer-class problem.
Hardware frontier · vendor-published specifications, April 2026

The arithmetic anyone can check.

The most useful thing we can publish is not an opinion — it is subtraction. Below are qubit counts and two-qubit gate fidelities as published by the vendors themselves. The practical-size column is arithmetic on those figures under the standard one-qubit-per-name encoding: finite gate fidelity bounds how much circuit you can run before the signal is gone.

SystemKindQubits2-qubit fidelityPractical universe
IonQ Fortegate-model3299.5%≤ 20 names
Google Willowgate-model10599.7%≤ 25 names
IBM Eagle r3gate-model12799.5%≤ 30 names
IBM Heron r2gate-model13399.9%≤ 35 names
D-Wave Advantage2annealern/an/an/a

Qubit counts and fidelities are the vendors' own published figures, recorded April 5, 2026, and will drift as hardware improves. The practical-universe column is derived arithmetic on those recorded figures, not a measurement of anyone's machine. D-Wave Advantage2 is an annealer: it uses a direct one-qubit-per-name embedding with no two-qubit gate depth, so the gate-model arithmetic does not apply to it and we do not print a specification we cannot source.

The subtraction. A selection problem over a universe of 64 names needs 64 qubits under the standard encoding. The strongest gate-model system in the table above is practical to roughly 35. Every gate-model system listed is therefore short by 29 to 44 names — before anyone argues about algorithms. A real portfolio is not 64 names; it is thousands. That gap is the whole story, and it is not close.

The scorecard

We pre-register, then we publish the loss.

Our quantum programme has run a series of controlled evaluations against classical controls, with the success criterion written down before the run. Every arm shares the same problem, the same decoding, and the same scoring, so a win cannot come from the plumbing. Here is where that landed.

Outcome

One bounded positive

A single quantum arm produced a genuine, audited quality edge over a strong classical control at small universe sizes — measured, paired, and survivable under re-audit.

Outcome

It did not survive the product boundary

Carried one layer further — to the place it would have to earn its keep for a customer — that same edge ties or loses to the classical control, and costs more per solve to obtain.

Outcome

The rest are clean negatives

Independent lines of attack were each taken to a pre-registered decision point. They tie classical methods at matched cost, add nothing measurable, or do not fit a production latency budget at all.

We report these the same way we would report a win. A negative result that was pre-registered is worth more than a positive one that was not: it is the only kind of evidence that cannot have been fitted after the fact.

What this buys you

The engine is classical. The lane stays open.

Everything we sell today runs on classical hardware and is measured as such. The quantum programme exists so that the day a device is genuinely ready for a problem shaped like yours, we will know it on evidence rather than on a vendor's slide — and so will you, because we will have published the losses on the way there.