This paper reframes logical-qubit benchmarking from a scalar error-suppression problem into a branch-resolved logical-state maintenance problem. Conventional quantum error-correction reporting focuses on logical error rates, better-than-physical comparisons, code-distance scaling, decoder performance, and accepted-stream outcomes. These metrics are essential, but they do not by themselves reveal which stabilization mechanism produced the improvement, whether the result depends on active correction or detection-assisted filtering, how much acceptance overhead was paid, or which branches remain underdetermined because raw timing, reset, syndrome, leakage, or feed-forward records are unavailable. The central contribution is QHOME-RETROFIT, a branch-resolved diagnostic framework that operationalizes the Quantum-State Homeostasis condition of Paper 22 on published quantum error-correction records. The framework converts logical-state maintenance into normalized engineering margins, evidence-status labels, tiered verdicts, limiting-branch reports, and a reproducible CSV-first evaluation workflow. It separates restoration capacity, logical-basis sharpness, protected-mode occupation, source-sink coupling, logical gain, acceptance overhead, and repeated-round stability instead of collapsing them into a single logical-error-rate claim. QHOME-RETROFIT is not a new quantum processor, error-correcting code, decoder, or threshold theorem. It does not claim raw shot-level access where such records are not publicly available, and it does not treat detection-assisted post-selection as equivalent to full real-time source-sink closure. The core operating rule is: score only the branch supported by the released evidence, label what is weakly proxied, and leave underdetermined what the public record cannot decide. The manuscript is a systems-code and reproducibility-layer paper, not a hardware demonstration. It defines a diagnostic grammar, evidence classes, tier gates, reproducibility plans, raw-record replay boundaries, and package-level audit artifacts. Its companion package provides fixed CSV inputs, generated outputs, dashboards, tests, and manifest checks so that the branch verdicts can be inspected rather than accepted as prose claims. Before scaling claims about fault-tolerant quantum computing, this paper argues, researchers should test logical-state maintenance: whether a reported improvement is correction-driven, detection-assisted, acceptance-limited, repeated-round stable, source-sink supported, and sufficiently evidenced to justify the engineering claim being made. Keywords: QHOME-RETROFIT, quantum error correction, logical qubits, fault-tolerant quantum computing, logical-state maintenance, branch-resolved diagnostics, source-sink architecture, post-selection, accepted-stream filtering, reproducibility, systems code, evidence-status labels, tiered verdicts, logical error suppression.
This paper reframes logical-qubit benchmarking from a scalar error-suppression problem into a branch-resolved logical-state maintenance problem. Conventional quantum error-correction reporting focuses on logical error rates, better-than-physical comparisons, code-distance scaling, decoder performance, and accepted-stream outcomes. These metrics are essential, but they do not by themselves reveal which stabilization mechanism produced the improvement, whether the result depends on active correction or detection-assisted filtering, how much acceptance overhead was paid, or which branches remain underdetermined because raw timing, reset, syndrome, leakage, or feed-forward records are unavailable. The central contribution is QHOME-RETROFIT, a branch-resolved diagnostic framework that operationalizes the Quantum-State Homeostasis condition of Paper 22 on published quantum error-correction records. The framework converts logical-state maintenance into normalized engineering margins, evidence-status labels, tiered verdicts, limiting-branch reports, and a reproducible CSV-first evaluation workflow. It separates restoration capacity, logical-basis sharpness, protected-mode occupation, source-sink coupling, logical gain, acceptance overhead, and repeated-round stability instead of collapsing them into a single logical-error-rate claim. QHOME-RETROFIT is not a new quantum processor, error-correcting code, decoder, or threshold theorem. It does not claim raw shot-level access where such records are not publicly available, and it does not treat detection-assisted post-selection as equivalent to full real-time source-sink closure. The core operating rule is: score only the branch supported by the released evidence, label what is weakly proxied, and leave underdetermined what the public record cannot decide. The manuscript is a systems-code and reproducibility-layer paper, not a hardware demonstration. It defines a diagnostic grammar, evidence classes, tier gates, reproducibility plans, raw-record replay boundaries, and package-level audit artifacts. Its companion package provides fixed CSV inputs, generated outputs, dashboards, tests, and manifest checks so that the branch verdicts can be inspected rather than accepted as prose claims. Before scaling claims about fault-tolerant quantum computing, this paper argues, researchers should test logical-state maintenance: whether a reported improvement is correction-driven, detection-assisted, acceptance-limited, repeated-round stable, source-sink supported, and sufficiently evidenced to justify the engineering claim being made. Keywords: QHOME-RETROFIT, quantum error correction, logical qubits, fault-tolerant quantum computing, logical-state maintenance, branch-resolved diagnostics, source-sink architecture, post-selection, accepted-stream filtering, reproducibility, systems code, evidence-status labels, tiered verdicts, logical error suppression.
This paper addresses a missing architectural layer in fault-tolerant quantum computing. The central question is not whether quantum processors require cooling, better qubits, error-correcting codes, real-time decoders, protected oscillator modes, engineered reservoirs, or feedback, but whether these mechanisms can be organized into a single measurable condition for active logical-state maintenance. The paper proposes Quantum-State Homeostasis as a source–sink framework for stabilizing protected logical quantum information under continuous dissipation. In this framework, a fault-tolerant quantum processor is not modeled as a perfectly isolated object, nor as a collection of independent engineering patches. Instead, it is modeled as an engineered open-system information architecture whose logical state survives only when restoration capacity, basis sharpness, dominant protected-mode occupation, and entropy-export coupling close together. The central contribution is the homeostasis score Qhomeo. This score combines four necessary factors: restoration capacity above coherence-window load, sharply selected logical basis, dominant protected logical-mode occupation, and engineered source–sink coupling. The resulting condition, Qhomeo = Θ((RQτQ/IQ) − 1) · WQ · p0,Q · κQ, defines logical stability as a conjunctive architecture rather than a single hardware parameter. Cryogenic cooling may extend the coherence window τQ; quantum error correction and decoding may increase restoration capacity RQ; cat qubits, bosonic codes, surface codes, and protected oscillator manifolds may support WQ and p0,Q; reservoir engineering, leakage reset, syndrome extraction, ancilla reset, and feedback may close κQ. However, none of these mechanisms is sufficient alone. A colder processor can still fail if its logical basis is diffuse. A fast decoder can still fail if feedback is not effectively coupled. A protected code manifold can still fail if entropy cannot leave the protected subsystem. The paper therefore reframes fault tolerance as active homeostatic maintenance of a protected logical mode. The structural theorem of the paper is conditional: if a quantum-stabilization architecture admits operational definitions of restoration capacity, coherence window, protected information load, basis sharpness, dominant protected-mode occupation, and source–sink coupling, then it admits a Qhomeo representation. Under the reduced-order assumptions stated in the manuscript, the protected logical mode follows an attractor-like stability condition αΦ > Γ. The paper interprets this not as a new fundamental law of quantum mechanics, but as a reduced-order architectural description of logical survival. Quantum error correction is therefore understood as controlled information transfer: error entropy is not annihilated, but routed into syndrome records, reset costs, reservoir excitations, heat, leakage-removal pathways, or correction-frame updates while the protected logical state is preserved. The empirical layer is framed as an architectural consistency program rather than proof of completed fault tolerance. The framework is anchored against published results across cat-qubit, GKP, and neutral-atom platforms, showing that heterogeneous stabilization mechanisms can be interpreted through the same reduced-order source–sink structure. The paper further commits to time-bounded prospective predictions for next-generation dissipative cat experiments, GKP fixed-point relationships, neutral-atom code-distance scaling, and an engineering sweet-spot range for αΦ/Γ. Failure of individual predictions revises the corresponding sub-claim; failure of multiple predictions triggers broader re-evaluation of the framework. The manuscript also defines claim boundaries: Qhomeo does not replace Hamiltonian models, Lindblad equations, threshold proofs, or platform-specific noise models; it organizes them architecturally. It does not claim that a fault-tolerant quantum computer has already been built, that quantum processors are biological or conscious, or that cooling is unnecessary. Its value lies in proposing a falsifiable, platform-neutral, source–sink architecture for testing whether logical quantum information can be actively maintained as a protected, sharply selected, entropy-exporting dominant mode. Keywords: quantum error correction, fault tolerance, logical qubits, quantum-state homeostasis, Qhomeo, source-sink architecture, reservoir engineering, autonomous QEC, bosonic codes, cat qubits, GKP codes, neutral atoms, logical information condensate, protected logical mode, entropy exhaust, reduced-order model, architectural stability score, quantum information stabilization, prospective falsification.
This preregistration describes a confirmatory study of an upstream conditioning architecture in a quantum error-correction workflow. The project’s purpose is to test whether an intervention applied prior to the primary decoder produces a real and reproducible decoder-relevant effect, remains compatible with more than one downstream decoder family, generates a measurable exposed-observable statistical footprint, and improves or preserves performance across a preregistered regime rather than only at a single operating point. The study is intentionally limited to architecture-level evaluation, with the public claim set confined to exposed observables, frozen transformations, preregistered statistical tests, explicit negative controls, and bounded interpretation rules. The confirmatory design is organized around five preregistered tests: category existence, decoder compatibility, structural footprint, observable statistical signature, and regime robustness. Across these tests, the central comparison is between a baseline control pipeline and a conditioned pipeline in which the upstream intervention is applied while all non-conditioning settings are held fixed. The study uses frozen observables and frozen execution rules, including matched seeds, shot counts, code distances, physical error rates, geometry, and baseline decoder settings, so that any supported effect can be interpreted as evidence about the architecture under test rather than as a byproduct of post hoc tuning. To preserve a clean-room boundary, the registration restricts primary analysis to exposed, decoder-facing quantities only. These include logical failure, an exposed defect-count summary, and an exposed decoder-difficulty proxy, along with a locked scalar error-load construction derived from control-only standardization. The study does not rely on decoder-internal state variables, hidden confidence traces, or implementation-specific internal diagnostics in its primary confirmatory analyses. This structure is intended to let readers evaluate whether the architecture leaves a reproducible footprint in decoder-facing behavior without disclosing reconstruction-level mechanism details. Expected outcomes are defined in confirmatory rather than speculative terms. If the preregistered hypotheses are supported, the study is expected to provide evidence that an upstream conditioning intervention exists as a real architectural category in QEC, acts before the primary decoder, is compatible with downstream decoding, changes decoder-relevant exposed structure, and produces a reproducible observable statistical footprint in logical-failure behavior. If support is absent, mixed, or null, those outcomes will still be recorded under the frozen rules without rescue through post hoc metric changes, reweighting, or reinterpretation. In either case, the expected result of the registration is a bounded, auditable public record of whether this architecture class shows reproducible category-level behavior under a preregistered confirmatory design. The preregistration is not intended to establish a unique mechanism identity, identify a privileged implementation, disclose implementation-specific reconstruction details, or support claims about exact targeting logic, suppression laws, subset-sizing logic, telemetry-governed control, or broader cross-domain theory narratives. Public-facing interpretation is therefore intentionally limited to category validation and exposed-observable behavior. This is meant to support rigorous public evaluation while preserving strict clean-room limits around protected implementation detail.
This record contains a manuscript and supporting reproducibility materials for “Ledger-Valid Recovery Diagnostics for Quantum Computing: A Prespecified Sequential Audit for Claim-Limited Recovery Validation.” The paper proposes a methodological validation framework for quantum-computing recovery claims. Its central claim is that endpoint recovery success is necessary but not sufficient for a strong recovery claim when calibration failure, false-carrier acceptance, postselection artifacts, leakage, sentinel blindness, or hidden discard can carry failure modes out of view. The manuscript introduces a prespecified S0–S4 ledger audit that converts familiar diagnostic ingredients—label calibration, candidate recovery, false-carrier challenge tests, postselection/leakage accounting, and sentinel observability—into an ordered, claim-limiting taxonomy. A supportive recovery claim is permitted only when all required gates pass; otherwise, the first failed stage determines a lower claim ceiling and an interpretable failure class. The evaluation is based on synthetic endpoint-level validation suites rather than circuit-level simulation or hardware data. These suites test the behavior of the decision architecture under clean support, degraded observability, false-carrier artifacts, postselection/leakage artifacts, sentinel-blind cases, correlated artifacts, and adversarial overlap. The results show a strong specificity/sensitivity tradeoff: the full ledger protocol sharply reduces synthetic non-support supportive-call rates relative to endpoint-only reporting, but with substantial loss of mechanism-positive support sensitivity. The paper explicitly treats this as a conservative claim-validity architecture, not as a new quantum error-correcting code, new physical observable, hardware speedup, or proof of improved device performance. The supporting materials document the final synthetic validation protocol, endpoint definitions, decision-bound implementation, direction-aware threshold sensitivity analysis, latent-threshold eligibility analysis, mechanism-negative/latent-eligible boundary cases, and figure/table traceability. The archive is intended to support review of the manuscript’s aggregate numerical claims and methodological provenance. Hardware implementation, independent simulator validation, and full raw-event-ledger reproduction are identified as future extensions. Suggested keywords: quantum computing; quantum error correction; validation methodology; recovery diagnostics; leakage; postselection; benchmarking; synthetic validation; decision architecture; reproducibility.
This paper develops an engineering-facing diagnostic bridge between the recoverability-based theory of structural irreversibility and practical evaluation in quantum error correction and monitored quantum platforms. The central problem addressed in this work is that structural recoverability, threshold-like margins, false-collapse, and Recoverability Index–type diagnostics provide useful theoretical distinctions, but they do not by themselves specify how experimentalists or engineers should organize platform-level data, compare regimes, or report recoverability-relevant behavior. The paper therefore introduces a proxy map from structural quantities to engineering diagnostics. Generalized recoverability is associated with recovery performance, decoder-assisted restoration, logical-state fidelity, and related reconstruction-sensitive quantities. Threshold-like margins are associated with entropy-like, noise-sensitive, or transition-localizing proxies. False-collapse is associated with mismatch windows in which collapse-like or transition-like indicators become strong while recovery-sensitive records still indicate residual recoverability. The paper also proposes a minimal diagnostic architecture for QEC and monitored platforms. This architecture consists of four layers: an appearance-sensitive proxy, a recoverability-sensitive proxy, a threshold-like locator, and a window-based reporting layer. Together, these layers support regime classification, early-warning detection, false-collapse-like mismatch identification, finite-window reporting, and cross-regime comparison. A QEC-oriented realization is presented to show how syndrome histories, logical-failure markers, logical recovery performance, entropy-like proxies, false-collapse window frequencies, and RI-like summaries can be organized into a coherent diagnostic workflow. The goal is not to replace detailed decoder analysis or hardware-specific benchmarking, but to provide a bridge-level language for deciding what should be logged, estimated, compared, and reported when studying the approach to effective irreversibility in error-managed quantum systems. This work should be read as an engineering and experimental companion to the broader recoverability program. Its contribution is to make structural irreversibility operationally legible by mapping theoretical quantities to measurable, computable, and reportable diagnostics in contemporary quantum platforms.
Quantum error correction (QEC) is indispensable for scalable fault-tolerant quantum computing. However, discovering QEC codes that remain effective is challenging, as logical performance depends on the interplay between code structure, hardware, syndrome extraction, and decoding, which often impose competing requirements. Here we introduce OmniQEC, an efficient AI scientist for discovering QEC codes suited to deployment on modern quantum processors. OmniQEC formulates QEC design as an iterative discovery process in which an orchestrator, implemented by advanced large language models (LLMs), coordinates code generation, code-level screening, syndrome-extraction synthesis, and decoder-based circuit evaluation. At its core, OmniQEC combines a self-evolving reasoning mechanism with a slow--fast synergistic workflow: a fast loop explores candidates using inexpensive code-level proxies, whereas a slow loop performs physically grounded circuit-level evaluation and feeds the resulting evidence back into the search. We evaluate OmniQEC across four qLDPC construction families, three LLM backends, and 14 total-physical-qubit budgets per backend. The discovered codes show steadily improving logical-error suppression with increasing physical-qubit budgets and outperform the BB codes with [[72,12,6]] and [[144,12,12]] under complete-implementation budgets of 98 and 240 physical qubits, respectively. The discovered codes are hardware-friendly and may be of independent interest for practical QEC implementation. These findings pave the way towards LLM-assisted QEC discovery grounded in physically informed code--circuit--decoder co-design.
Official website: distinctiontheory.orgPublic portal for the start guide, papers, claim status, failure registry, prior-art boundary, and citation resources. Canonical GitHub repository:https://github.com/yiningwu-research/Distinction-Theory FDS-Q2 develops the quantum-computation paper in the Finite Distinction Systems (FDS) / Distinction Theory sequence. It studies fault-tolerant quantum computation as a problem of finite distinction maintenance: logical quantum distinctions must be actively preserved against noise, leakage, decoherence, latency, reset burden, cooling limits, and finite correction infrastructure. This paper is not a no-go theorem for quantum computation. It does not claim that quantum computation is impossible, does not refute the quantum threshold theorem, and does not identify every syndrome measurement with Landauer erasure. Instead, it asks what physical maintenance ledger must be paid in order to instantiate fault-tolerant assumptions at useful scale. The central claim is: Logical error suppression requires finite distinction-maintenance infrastructure. A logical qubit is treated as a protected quantum quotient or code-algebra distinction, QL = q(ρphys), not as a simultaneously readable classical bit. Quantum error correction therefore converts distinction loss into maintenance work: redundancy, syndrome acquisition, decoding, feedback, reset, cooling, routing, reservoir engineering, and control. The main audit object is a vector ledger rather than a scalar cost: Rcorr(τ)(εL; N, C) = ( Bsyn, Bdec, Breset, Llatency, Pmaint ), together with a maintenance-capacity vector Cmaint(τ) = ( Cread, Cdec, Creset, Cfeed, Ccool, Cctrl, Clatency ). The feasibility condition is componentwise: Rcorr(τ) ⪯ Cmaint(τ), meaning that syndrome, decoding, reset, latency, power, cooling, and effective-error components must each fit their corresponding time window, physical location, and engineering capacity. Landauer’s principle enters only as a lower bound on logically irreversible reset, overwrite, or garbage disposal under its standard assumptions: Perase ≥ kBT ln 2 · berase/cycle / τcyc. The paper explicitly distinguishes syndrome acquisition from erasure. It does not assume that every extracted syndrome bit is erased at the same temperature stage where it is measured. Syndrome information may be exported, buffered, decoded elsewhere, processed reversibly for a time, or dissipated through an engineered reservoir. The Q2 requirement is that the entropy-export path, reset burden, latency, cooling load, and failure probability be specified rather than hidden. The paper introduces two audit principles: No-free logical distinction maintenance: if passive protection does not fully suppress noise, then maintaining a logical distinction below error tolerance requires redundancy, syndrome information, feedback, reset or export, engineered dissipation, latency increase, resource growth, task relaxation, or failure. Ledger relocation: maintenance cost can be moved across cold stages, room-temperature electronics, optical channels, autonomous reservoirs, topological gaps, or passive-protection mechanisms, but it cannot be made unaccounted. For surface-code-like architectures, Q2 uses the normal forms Nphys ∼ αnLd2, and pL(d,p) ∼ A(p/pth)(d+1)/2, to illustrate the central tradeoff: logical error decreases as code distance grows, but physical carriers, syndrome load, decoding burden, routing, reset, and maintenance infrastructure also grow. For cryogenic solid-state processors, Q2 defines a cold-stage reset ledger, Presetcold ≳ [ kBTcold ln 2 / τcyc ] χresetβnLd2, and a scaling-wall diagnostic nLmax ∼ [ Pcoolavailτcyc ] / [ ηχresetβ kBTcold ln 2 d2 ]. This diagnostic is not a platform-independent maximum logical-qubit count. It is a way to locate which cooling, reset, control, or latency ledger is being exhausted. The paper also analyzes ledger-relocation latency tax. Moving decoding or syndrome processing to warmer electronics may reduce cold-stage heat, but can increase feedback-loop time, τloop = τmeas + τexport + τdecode + τfeed, which increases idle error and can require larger code distance: τloop ↑ ⇒ peff ↑ ⇒ dreq ↑ ⇒ Nphys, Bsyn, Pmaint ↑. The architecture discussion covers superconducting processors, spin qubits, trapped ions, neutral atoms, photonics, topological protection, bosonic and cat-code approaches, qLDPC codes, LDPC-cat codes, and autonomous or dissipative QEC. These are treated as ledger-shaping or ledger-relocation strategies rather than as ledger-elimination strategies. Q2 further proposes a minimum reporting template for quantum-computing architecture audits: ( nL, d, Nphys, peff, pL*, τcyc, Bsyn, Breset, Pcold, Proom, Ptotal ), together with decoder location, reset location, cooling stage, latency bottleneck, and entropy-export path. This release includes deterministic normal-form demonstrations: surface-code logical-error/load scaling, cold-stage reset-floor sensitivity bands, latency-density feedback, architecture maintenance regimes, and an FDS-Q2 relation map. These figures are conceptual normal forms, not empirical fits, not refrigerator models, and not quantum dynamical simulations. The release includes the paper PDF, LaTeX source, reproducibility code, generated figures, CSV tables, and model-summary outputs.