Calibration loops are essential for maintaining cryogenic quantum devices under drift, stochastic readout variation, and device mismatch.This study presents an embedded closed-loop calibration architecture using a singleton Sugeno fuzzy controller with fixed-size arithmetic, bounded updates, and a lightweight telemetry interface.The emphasis is deterministic local execution rather than host-side optimization: each iteration performs measurement accumulation, probability estimation, error computation, fuzzy inference, and parameter update along a repeatable path.An executable Verilog-based evaluation model is used to evaluate convergence behavior, monitor-mode operation, and sensitivity to injected drift.The measured results show fast transition into monitor mode, fixed calibrated-parameter retention after convergence, and observable monitor-metric shifts under positive and negative perturbations.These results support the feasibility of compact embedded calibration for cryogenic quantum devices while keeping the controller structure simple, interpretable, and implementation-oriented.
Calibration loops are essential for maintaining cryogenic quantum devices under drift, stochastic readout variation, and device mismatch.This study presents an embedded closed-loop calibration architecture using a singleton Sugeno fuzzy controller with fixed-size arithmetic, bounded updates, and a lightweight telemetry interface.The emphasis is deterministic local execution rather than host-side optimization: each iteration performs measurement accumulation, probability estimation, error computation, fuzzy inference, and parameter update along a repeatable path.An executable Verilog-based evaluation model is used to evaluate convergence behavior, monitor-mode operation, and sensitivity to injected drift.The measured results show fast transition into monitor mode, fixed calibrated-parameter retention after convergence, and observable monitor-metric shifts under positive and negative perturbations.These results support the feasibility of compact embedded calibration for cryogenic quantum devices while keeping the controller structure simple, interpretable, and implementation-oriented.
A companion paper reported a fail-closed estimator — the Quantum Control Kernel (QCK) — that detects the precursor of systematic bias drift in cryogenic quantum control before actuator saturation, validated in simulation and against live, publicly accessible IBM hardware-calibration data. This paper reports what the estimator is for: the Quantum Control Architecture (QCA), a governed measurement-and-control layer in which the demonstrated kernel is the sensing floor of a larger construction. The construction is not free design. It is the quantum instantiation of a result established generically in the Finite Cognition series: a finite observer serving both a committing execution demand and a wide-field vigilance demand is forced to partition the two and re-couple them at the point of finalisation, so that no output is committed that vigilance has not verified. We show that quantum control information forces exactly this construction — telemetry is consumed by every layer of the control stack yet governed by none of them; observation of a quantum plant must be non-perturbative by discipline, not by hope; and an estimator that is fluent but ungoverned reproduces, on the control substrate, the same confident-and-blind failure the series identified generically. We then state the architecture that discharges the constraint, in its public units: a non-perturbative observer (NPO); the QCK detection floor; fail-closed gates that allow, abstain, or refuse; a state-coherence and equilibrium discipline over commits; provenance-checked memory that refuses known-failure patterns; a lifecycle and loop supervisor; a measurement plane of stability, coupling, margin, and cost features; and an integrity plane that audits the architecture’s own calibration model and gates its portability to new hardware on provably leak-free relocation. We are explicit about maturity throughout: the kernel is demonstrated at Technology Readiness Level 4 under published bounds; the architecture beyond it is compile-ready geometry — derived, specified, and internally consistent, not validated as live middleware on partner hardware. The architecture is advisory by construction: the operator owns the plant at every depth.
We introduce two classes of lightweight, adaptive calibration protocols for quantum computers that leverage fast feedback. The first enables shot-by-shot updates to device parameters using measurement outcomes from simple, indefinite-outcome quantum circuits. This low-latency approach supports rapid tuning of one or more parameters in real time to mitigate drift. The second protocol updates parameters after collecting measurements from definite-outcome circuits (e.g.~syndrome extraction circuits for quantum error correction), balancing efficiency with classical control overheads. We use numerical simulations to demonstrate that both methods can calibrate 1- and 2-qubit gates rapidly and accurately even in the presence of decoherence, state preparation and measurement (SPAM) errors, and parameter drift. We propose and demonstrate effective adaptive strategies for tuning the hyperparameters of both protocols. Finally, we demonstrate the feasibility of real-time in-situ calibration of qubits performing quantum error correction, using only syndrome data, via numerical simulations of syndrome extraction in the [[5,1,3]] code.
A companion paper reported a fail-closed estimator — the Quantum Control Kernel (QCK) — that detects the precursor of systematic bias drift in cryogenic quantum control before actuator saturation, validated in simulation and against live, publicly accessible IBM hardware-calibration data. This paper reports what the estimator is for: the Quantum Control Architecture (QCA), a governed measurement-and-control layer in which the demonstrated kernel is the sensing floor of a larger construction. The construction is not free design. It is the quantum instantiation of a result established generically in the Finite Cognition series: a finite observer serving both a committing execution demand and a wide-field vigilance demand is forced to partition the two and re-couple them at the point of finalisation, so that no output is committed that vigilance has not verified. We show that quantum control information forces exactly this construction — telemetry is consumed by every layer of the control stack yet governed by none of them; observation of a quantum plant must be non-perturbative by discipline, not by hope; and an estimator that is fluent but ungoverned reproduces, on the control substrate, the same confident-and-blind failure the series identified generically. We then state the architecture that discharges the constraint, in its public units: a non-perturbative observer (NPO); the QCK detection floor; fail-closed gates that allow, abstain, or refuse; a state-coherence and equilibrium discipline over commits; provenance-checked memory that refuses known-failure patterns; a lifecycle and loop supervisor; a measurement plane of stability, coupling, margin, and cost features; and an integrity plane that audits the architecture’s own calibration model and gates its portability to new hardware on provably leak-free relocation. We are explicit about maturity throughout: the kernel is demonstrated at Technology Readiness Level 4 under published bounds; the architecture beyond it is compile-ready geometry — derived, specified, and internally consistent, not validated as live middleware on partner hardware. The architecture is advisory by construction: the operator owns the plant at every depth.
Scalable quantum processors require control, readout, feedback, calibration, and error correction to coexist under bounded latency and shared-resource constraints, whereas existing platforms typically optimize only a subset of these capabilities. This article presents QCORE (Quantum-Control-Oriented Real-Time Execution), a QPU-side digital control reference architecture positioned between the Host and a platform-specific analog/mixed-signal front end. QCORE separates task management, shared resources, hard-real-time execution, and long-timescale services into four hardware partitions. A fast-result sideband closes same-round feedback, a Measurement Packet provides a traceable measurement and service interface, and a common service-control skeleton, Tile-local QEC, and versioned safe-point commit organize calibration, error correction, and long-term state updates. Transaction-level, event-driven, and quantum-behavioral models are used for evaluation. At a background load of 0.8, the P99 latency of the shared Measurement Packet/Event feedback path is (1.984±0.004)Lmax. Closed-loop operation reduces the mean frequency error by 83.2%±0.8% and lowers the state-assignment error at maximum readout drift from 10.39%±0.54% to 5.37%±0.29%. No unsafe acceptance or mixed-version observation is observed in 100,000 configuration transactions, and Tile-local QEC reduces modeled global-boundary demand and yields a 2.08× capacity-normalized scaling estimate.
In superconducting devices running variational workloads, gate and readout fidelities drift on hour timescales, while existing runtime schedulers treat backend quality as static. The temporal dimension of calibration remains unresolved. We formulate runtime calibration as a state-trajectory feedback-control problem under a fixed wall-clock budget, and investigate whether spending time on calibration now can improve the future optimization trajectory. Calibration quality proxy is represented as a drifting equivalent-age state, recovery action is modeled as costly state reset, and policies are evaluated by time-integrated optimization gap over the full execution window. Using a finite-horizon rollout controller, we compare feedback calibration against a strengthened family of open-loop baselines across three latency regimes: cloud-like (25 ms), local-millisecond (1 ms), and tight-loop (4 μs). The results show a clear ordering: cloud-like feedback is generally uncompetitive, while local-ms and tight-loop regimes open a positive-gain region that grows with workload quality-sensitivity and initial calibration age. Crucially, the gap between local-ms and tight-loop control is modest for single-target recovery. The advantage of tight-loop integration emerges under capacity pressure, when many calibration targets must be processed within the same control window.
Cryogenic control electronics for quantum hardware accumulate systematic, non-zero-mean bias that integrates in a feedback loop until the actuator saturates; a threshold controller detects this only after saturation. We present a precursor estimator that detects the onset of systematic drift from the dynamics of the control signal, built as a finite observer (declared error budget, explicit competence boundary, fail-closed abstention) in the sense of a companion paper on the physical limits of finite observation. It uses path-functional invariants (a Fisher–Rao metric stability bound, a maximum-likelihood bias decoder, a cumulative-damage functional) rather than eigenvalue analysis, which we show is neither necessary nor sufficient for finite-time survival. In simulation, across 30 seeds × 7 sensor-environment conditions (including a 1/f dephasing spectrum), it detects 96.7% of drift-collapse scenarios before saturation at a 12 s median lead with 0% false positives over 210 healthy runs. On real data, the same governed outlier-and-drift detector, applied to live publicly accessible IBM quantum-hardware calibration time-series (a 156-qubit IBM Heron device), flags genuinely degraded qubits and catches a real relaxation-time decline (one qubit's T1 falling 88.0→19.1 µs, −78%, over 43 days) while staying silent on a qubit that is poor but stable and on the other 155 — detection of change, not of mere badness. The work is TRL 4: an advisory detection layer, not a deployed controller, and it does not emulate entanglement, non-local correlation, or contextuality. The contribution is the integrated, calibrated estimator and its operating discipline, demonstrated in simulation and against real hardware-calibration data.