Continuous quantum error correction depends on which parts of a measurement record remain available to the controller at recovery. We study this temporal access using continuous strategic codes, formulated as open continuous process tensors contracted with causal instruments and conditional recovery. For monitored stabilizer codes, a common-optimal-correction criterion identifies when records can be merged without loss and yields a factorization for separated CSS inference. Terminal decision labels and causal persistent memory carry different costs: five persistent classical states reach the complete-record optimum in a finite-strength counting model, whereas its two-window diffusive counterpart has nine terminal decision labels and requires unbounded memory for exact causal recovery. Uniform lower and constructive upper bounds establish an optimal fidelity deficit of order $m^{-2}$ for $m$ persistent states in the diffusive model. Counting and diffusive stability bounds translate open-process approximation into guarantees for deployed-controller performance and retained access advantages, quantified by explicit quantizers and model-mismatch curves. The same process--instrument framework connects storage with persistent environments and irreversible noise to spacetime interrogation and record-selected paths for a logical $T$ gate. These results specify which record distinctions recovery needs, the memory cost of approximating them, and the logical protection retained under model error.
Continuous quantum error correction depends on which parts of a measurement record remain available to the controller at recovery. We study this temporal access using continuous strategic codes, formulated as open continuous process tensors contracted with causal instruments and conditional recovery. For monitored stabilizer codes, a common-optimal-correction criterion identifies when records can be merged without loss and yields a factorization for separated CSS inference. Terminal decision labels and causal persistent memory carry different costs: five persistent classical states reach the complete-record optimum in a finite-strength counting model, whereas its two-window diffusive counterpart has nine terminal decision labels and requires unbounded memory for exact causal recovery. Uniform lower and constructive upper bounds establish an optimal fidelity deficit of order m−2 for m persistent states in the diffusive model. Counting and diffusive stability bounds translate open-process approximation into guarantees for deployed-controller performance and retained access advantages, quantified by explicit quantizers and model-mismatch curves. The same process--instrument framework connects storage with persistent environments and irreversible noise to spacetime interrogation and record-selected paths for a logical T gate. These results specify which record distinctions recovery needs, the memory cost of approximating them, and the logical protection retained under model error.
The uncontrolled endpoint channel can conceal how well a quantum process can protect a logical task under time-resolved control. We formulate a fixed-task resource theory of continuous process tensors with physical access interfaces, entrance-erasing free objects, and budgeted free conversions. Complete-record total-variation error measures performance; the calibrated capability is monotone under conversions that preserve a common free baseline. For unknown-state transmission the baseline is exactly 1−d−2. Two qubit processes with the same endpoint channel have optimal errors 0 and p=sin2(2gh) at the same finite pulse budget in an ideal-transparent system-only window architecture, forcing any endpoint-only predictor to err by at least p/2 on one of them. An exactly solvable family shows how the allocation of a fixed interaction phase around a control window sets the attainable error, and a nontrivial perfect echo requires and attains total control action π in that architecture. The separation extends directly to every qubit unitary target at a budget that includes its boundary gate, while unitary tasks in any dimension have baseline 1−d−2 whenever a budget-feasible free realization gives the depolarizing output. Complete-record implementation bounds quantify coherent and dissipative control imperfections. Continuous-process randomized compilation supplies physical instrument pullbacks; compatible completion conditions extend their action, and certified dynamical bounds yield achievable task-error and capability guarantees. The resulting theory identifies temporal structure and control investment that endpoint characterization alone cannot resolve.
What must a quantum error-correction decoder know about temporally correlated noise, and what does it cost to learn? We study this question for fixed stabilizer memory experiments with known system-environment interactions. We formulate calibration in terms of the fidelity differences that select a Pauli recovery and relate missing information to the resulting fidelity loss. Our main example uses weak coherent X rotations in a class of CSS codes including Shor, Steane, and odd-distance rotated surface codes. All physical qubits share a sign either fixed throughout a run or independently redrawn each interval. The two models have identical syndrome statistics and the same spatiotemporal Pauli process (SPP), obtained by Pauli-twirling every noise interval. Yet at suitable storage times, they require different logical corrections. In the weak-noise limit, each model is almost perfectly correctable when known. Without model information, even the best final recovery has a worst-case fidelity loss approaching 1/2 relative to the noise-aware optimum, despite access to the full syndrome record. For this pair of models, at fixed code and fixed positive target loss below 1/2, we prove matching calibration bounds. With logical preparation and final readout, complete QEC cycles require a number of noise intervals scaling as the inverse rotation angle raised to the code's X distance. Allowing two uninterrupted intervals before one extraction reduces the optimal cost to inverse-square scaling. Physical Pauli twirling of every noise interval changes both recovery performance and its information requirements. Discarding the record of applied random Pauli operations makes the SPP sufficient for optimal recovery. Keeping this record can improve the attainable fidelity, but reaching that optimum may require additional noise information.
Traditional discrete randomized compiling (RC) tailors errors with random control frames at logical-gate boundaries, but fails to capture intra-instrument control evolution or persistent system-environment coupling. In memory-bearing environments, errors correlate across times, not just single gates. We build continuous-process randomized compilation (CPRC) in the continuous process tensor (cPT) framework, unifying random unitary control trajectories, pointwise-covariant finite-duration instruments, and environmental dynamics on one time axis. We study four protocols: fixed Pauli refresh, bounded Cayley paths, unitary Brownian motion, Ornstein-Uhlenbeck driving. We obtain three key results: (1) Pointwise covariance ensures each trajectory exactly reproduces the target logic without system-environment coupling; a closed-frame counterexample proves endpoint-only compensation causes first-order instrument errors. (2) Independent Pauli conjugations over full intervals diagonalize error histories at boundaries, but classical labels retain environment-induced correlations, confirmed by an exact static-bath solution. (3) We derive a total-variation error bound for full adaptive output records under bounded centered coupling and mixing conditions. We prove the Fock norm convergence of the entire trajectory-averaged cPT for finite non-Gaussian environments and Gaussian baths with time-integrable covariance, including the uncut Drude spectrum. We numerically validate the theory in a qubit model via output probabilities, operator conditional mutual information, and all two-particle coefficients for both qubit and thermal Drude baths. This work extends RC from discrete circuits to continuous-time memory-bearing quantum processes, offering a unified framework, quantitative tools, implementable schemes, and benchmarks for non-Markovian error tailoring.
This preliminary research preprint presents a reproducible numerical study of history-conditioned quantum error correction under temporally correlated noise. We consider a three-qubit phase-error code subject to a synthetic Pauli noise model with a persistent hidden noise regime. A noisy classical monitor and the accumulated syndrome/measurement history are used to estimate that regime through standard Bayesian hidden-Markov filtering, and recovery operations are selected by a causal maximum-a-posteriori rule. The central question is whether accessible temporal information can extend the finite interval over which encoded quantum information remains reliable. In 100,000 matched synthetic trajectories, survival through 20 correction rounds increases from 0.74406 for a snapshot MAP decoder to 0.91455 for the history-conditioned decoder. Under a 90% no-logical-fault survival criterion, the empirical computational-memory window increases from 6 to 25 rounds, with a simultaneous 95% lower confidence band supporting 23 rounds for the history-conditioned policy. Control experiments show that the advantage disappears when temporal predictability is removed: when the hidden regime becomes independent from round to round, the history-conditioned and snapshot policies coincide. Additional monitor and model ablations demonstrate that the benefit depends on correction-relevant temporal correlations, informative side information, and adequate calibration. The work also formulates finite-horizon survival criteria and sufficient error-budget bounds without assuming independent logical faults, while explicitly separating classical filter stability from preservation of quantum information. This study does not claim a new Bayesian filtering method, superiority over existing temporal quantum-error-correction decoders, a scalable fault-tolerance threshold, or demonstrated room-temperature quantum-computing hardware. Rather, it provides a concrete operational specialization of the broader TrinityLabo history-first framework and a small, reproducible benchmark showing how temporal inference can condition quantum recovery under specified noise assumptions. Ambient-temperature operation remains a future experimental application requiring calibrated device-level noise models, fault-prone syndrome extraction, hardware latency analysis, and comparison against established temporal decoders.
When does a readable record survive the actual physical process, and when does memory change that survival? Present readability, temporal label retention and process memory answer separate questions. Their analysis requires a physical carrier, an identity-relevant record quotient and its actual continuation. We develop their common reduction architecture and derive an explicit memory correction to temporal record certificates. On a classical record quotient, the channel defect equals the largest class re-identification error. Its additive composition bound holds for the actual composed quotient process; it need not hold for individually calibrated steps whose preparations erase the correlations reached in a real run. A two-CNOT construction makes every freshly calibrated step preserve the record perfectly while the actual two-step continuation erases it. The missing term is a process-composition gap, which we define and bound by discrepancies between actual joint preparations and the preparations used by a reduced model. The same construction identifies a memory sector that must be retained to obtain a faithful record continuation. We also prove that decoherence and broadcasting do not fix temporal record identity; that CP-divisibility depends on the carrier and preparation; and that memory can be irrelevant to a protected identity register. A finite dephasing model has no trace-distance backflow on its declared interval yet changes record retention under a correlation-severing intervention. These results separate memory magnitude, causal record relevance and Constitution change. The derivations use unchanged finite-dimensional quantum dynamics and retain explicit scope conditions for every identity claim.
This preprint studies operational equivalence and recovery in a twenty-dimensional residual system with a fixed four-sector representation of dimensions 8, 8, 2 and 2. It distinguishes what a declared observation algebra can detect, what a channel preserves, and what a retained classical record makes recoverable. Record-resolved criteria separate useful reversible-error records from unrelated labels and measured-sector records, even when the discarded channel is the same. For a specified coarse-record model, the work identifies exactly recoverable observable algebras and proves an optimal entanglement-fidelity expression on a fixed four-state orbit code. Preparation-aware recovery is then classified over all one-use isometric subspaces in the stated family. An explicit ten-dimensional marker code attains exact recovery under a specified stochastic record where the whole-sector support restriction permits only eight dimensions. Its encoding, nonbaseline marker measurement, and conditional inverse operations remain supplied resources. Scoped Lean evidence verifies the explicit arbitrary-complex-matrix recovery construction and related finite identities; it does not formalize the general complete-positivity/reference framework or optimal-dimension theorem. The recorded-error model is not derived from the companion exchange-timing model, and no protection of its long pulse sequence is claimed.