A quantum processor fails in five different places: gates drift under control error, neighboring qubits crosstalk, error correction stalls before it scales, results can't be trusted, and the hardware itself degrades at the nanoscale. We hold a filed provisional patent at each. They aren't five unrelated bets — each protects the same thing, the integrity of a quantum state, at a different point in the machine, from the gate operation down to the vacuum boundary. Two are near-term software that runs on any vendor's hardware; two are the hardware core; one is the frontier.
Each patent protects the integrity of a quantum state at a different point in the machine. All five are filed provisional applications.
| Layer | What breaks | Our IP — what it does | Stage |
|---|---|---|---|
| GateAT-001 | Control pulses miss; the gate angle drifts. | Winding-class holonomic gate — the gate angle is set by an integer winding number, not pulse shape. | Patent pending hardware core |
| Control & scalingAT-002 | Flux bias crosstalks; calibration grows with the chip. | VPT solenoid bias — confines the field; near-diagonal crosstalk, ≥300× lower. | Patent pending hardware core |
| Error correctionAT-003 | Error correction stalls before it scales. | The Saturation Monitor — forecasts logical failure from the budget map and steers correction. | Patent pending near-term software |
| TrustAT-005 | You can't verify a result or catch drift. | Cost-distortion diagnosis — a four-way verdict and a "hard for a classical machine" certificate. | Patent pending near-term software |
| VacuumAT-004 | Nanoscale stiction; no native entanglement source. | TI–Casimir boundary — repulsive-force gap control and a fermionic-DCE entangled-pair source. | Patent pending frontier |
Every quantum gate in service today is a precisely shaped microwave pulse — and the precision is the problem. Amplitude that's off by a percent, phase that has drifted since the last calibration: each feeds straight through into gate error, which is why so much of running a quantum processor is recalibrating control electronics that won't hold still.
We move the operation out of the pulse and into the circuit. The gate angle is fixed by an integer winding number — how many times the superconducting phase winds through a physical loop — carried out as a Wilczek–Zee holonomy in a zero-energy "dark" subspace. Because the result depends only on that integer, it shrugs off the exact shape and amplitude of the control waveform: a whole class of control error that the pulse-shaped approach has to calibrate away cancels here by construction. An integer is hard to get a little bit wrong.
This is a different robustness axis from chasing ever-higher pulse fidelity — winding-class robust, not topologically fault-tolerant: the winding still has to be enforced by the control electronics, and adiabaticity and fabrication tolerances still matter. And it runs on clean flux bias, which is exactly what the quiet coil delivers — so the advantage holds as you pack qubits together instead of drowning in crosstalk.
Provisional filed (App. 64/017,790). Analytically derived and simulation-validated; not yet silicon-proven.
Flux-tunable superconducting chips don't scale cleanly, and the reason is mundane: every flux-bias line is a little antenna that talks to its neighbors. Add qubits and it compounds — each new bias line can disturb every qubit already on the chip, so the calibration burden grows faster than the chip itself. You end up tuning the whole chip against itself.
Our control wiring confines the field instead of broadcasting it. A coaxial solenoid delivers the flux a qubit needs while a matched return cancels the stray field by geometry — an exact, first-order cancellation — so the bias stays local. The crosstalk matrix goes near-diagonal: each qubit feels its own line and almost nothing from anyone else, which turns calibration from a chip-wide fight into N independent jobs you can run in parallel.
Against a conventional bias wire that's a ≥300× reduction in crosstalk, validated in field solvers. It's also a manufacturing non-event — the solenoid is wound in the standard trilayer process with no extra mask steps. To be precise about scope: this confines uniform, laboratory flux noise; it isn't a fix for surface-spin, dielectric, or quasiparticle noise, and it's validated in simulation, not yet silicon.
Provisional filed (App. 64/022,566), eight related inventions. EM/field-solver validated; not yet silicon-proven.
Adding qubits is the industry's answer to almost everything, but it only works if you're truly below the error-correction threshold everywhere on the chip. Real processors aren't uniform — a few bad couplers or one noisy region pull the effective threshold down, by roughly 25% in our simulations. And what trips a logical qubit isn't the chip's average error rate; it's the weakest path through the code. Hot spots make that path far worse than the average, so a chip can clear the "below threshold" bar on its average while the path that actually decides the outcome is already over the line. Add qubits expecting the exponential payoff, and the logical error rate flattens instead of falling — qubits spent, no return.
The miss is in what gets measured. A logical failure isn't "a lot of errors" — it's a connected error chain spanning the code, and average error rates and raw defect counts can't see one forming. We model every interface as a finite budget, capacity against load, and watch the saturation map: where the correction burden is concentrating. That signal flags a forming failure earlier than raw defect count does — in time to steer correction toward the interfaces nearest the line.
It's vendor-agnostic control-plane software that runs on the syndrome and decoder data a code already produces, on superconducting, ion-trap, or neutral-atom hardware. It doesn't wait on our own chips to ship.
Provisional filed (App. 64/070,628). Results are simulation-validated, not yet silicon-proven.
The whole point of a quantum computer is that a classical one can't keep up — which makes it challenging to audit its work. Every answer it returns carries two unanswered questions: is the hardware still behaving the way it should, and did it actually do something a classical machine couldn't? Today both collapse into a single fidelity score — a headline number that says "good enough" but hides the breakdown: where the errors actually are, whether the device has drifted or hit a limit, and whether the result was beyond classical at all.
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.
Provisional filed (App. 64/070,738).
The deepest layer of the same idea is the vacuum boundary. A topological-insulator surface carries a protected sea of Dirac electrons; place a switchable magnetic boundary on it and you can shape the quantum vacuum right at that surface. We hold a provisional on two modes of one platform — and we're candid that this is the exploratory edge of the program.
Driven — the magnetic boundary oscillated by a piezo — the surface emits pairs of frequency-entangled electrons: a fermionic dynamical Casimir effect, predicted to run orders of magnitude faster than its photonic cousin, which makes it a candidate on-chip entanglement source. Held static, the same surface produces a repulsive Casimir force: a self-correcting gap that resists nanoscale stiction, useful for keeping MEMS/NEMS structures and processor gaps from collapsing.
The novelty rests on the entangled-pair source, where the prior art is thinnest; the static repulsive effect sits closer to the recent literature. This is option-value IP, not a near-term product — but it carries the same strategy, protecting the quantum state, all the way down to the vacuum.
Provisional filed (App. 64/070,728). Exploratory; physics is analytical, no device built.
The strategy is grounded in the company's technical work; the mechanisms are derived analytically and confirmed in simulation and field solvers. The performance figures are theoretical and validated in those tools — not yet proven in silicon. Two of the five families are near-term software that runs on hardware shipping today; the vacuum layer is an open frontier, and we say so.