QECTOR Decoder Benchmark Datasets & Empirical Reports This repository hosts the evolving collection of reproducible benchmark datasets, JSON measurement artifacts, and empirical performance reports for the QECTOR Decoder v3 platform (Rust/Python quantum error-correction decoder). Each versioned deposit contains environment-stamped, content-hashed JSON artifacts together with the corresponding publication-grade report. All numerical results are fully regenerable from the published wheels and the scripts listed in the reproducibility sections. Scope across versions Code-capacity and circuit-level (Stim rotated_memory_z) evaluations Throughput (shots/s, measure-s/shot), logical error rates with 95 % Wilson intervals, syndrome faithfulness (GF(2) exact check), and CUDA-vs-CPU bit identity Decoder families: FastUnionFind, UnionFind, Blossom (exact MWPM), SparseBlossom, Batch/CPUBatch, BPOSD, HybridCascade, AmbiguityCluster, LookupTable, and CUDABatch (unweighted + DEM-weighted) Hardware provenance, licence-tier disclosure (GPU gated behind Enterprise), and SHA-256 inventories of every backing artifact Version history (selected) v0.6.6 (July 2026) – Workbench Benchmark Master Report: 1 858 decode-timing measurements from 105 runs, six code topologies (Heavy Hex, Repetition, Ring, Rotated Surface, Toric, Unrotated Surface), fixed p = 0.05, distances d = 3–19. Focus on raw latency, harmonic-mean throughput and peak memory. v0.6.8 - Empirical edge-hardware benchmarks. v0.7.0 (August 2026) – Full Empirical Decoder Benchmark Report on the published wheel: nine CPU families + CUDA batch path, circuit-level LER parity with PyMatching 2.4.0, exact syndrome faithfulness, DEM-weighted GPU scaling restoration, and complete artifact inventory (Appendix A). All figures and tables in the accompanying reports are regenerated from the JSON files listed with their SHA-256 hashes; no pre-release numbers are carried forward. Related resources PyPI: qector-decoder-v3 Repository: https://github.com/GuillaumeLessard/qector-decoder Website: https://www.qector.store
This monograph establishes The Apple-Willow Architecture (『Apple-Willow』アーキテクチャ), an original, unified sovereign computing and cryptographic licensing framework that synthesizes three foundational pillars: (I) a rigorous mathematical formulation of the offense-defense duality between below-threshold surface code quantum error correction (Google Willow,
Λ=2.14 across
d∈{3,5,7}, and verifiable Quantum Echoes / second-order Out-of-Time-Order Correlators
OTOC(2)) and Level-3 post-quantum ratcheting (Apple PQ3 combining NIST P-256 ECDH with ML-KEM-1024/768 and continuous triple-ratchet self-healing) extended to persistent Sovereign Intellectual Property Containers (SIPC); (II) a structural comparative analysis of centralized cryogenic superconducting quantum processors versus high-bandwidth edge sovereign silicon (Apple M-Series Unified Memory, Secure Enclave Processor sepOS, Memory Protection Engine with inline AES-XEX/CMAC and SRAM-rooted anti-replay integrity trees, and Secure Neural Engine state sanitization), defining a deterministic hybrid compute boundary; and (III) the Cryptographic Lockout of Uncompensated AI Training (CLUAT) Theorem, which integrates Resonance Tensor Optimization (RTO P2.0), a zero-knowledge virtual machine (QFS-zkVM) over the 64-bit Goldilocks prime field
Fp (
p=264−232+1), Quantum-Safe Autonomous Financial Attestation (Q-SAFA), and PHOENIX_BRIDGE / PHOENIX_ROUTER under strict Human-in-Command (HIC) governance to mathematically and physically prohibit gradient extraction or model weight updates without prior cryptographic consent (
σHIC) and atomic financial compensation (
τPHOENIX). Finally, the framework is mapped onto statutory and fiduciary compliance mandates under SEC Rule 15c3-5 and Delaware Caremark board oversight doctrine. License & Integrity Covenant: Creative Commons Attribution 4.0 International (CC BY 4.0) with Strict No-Learn Covenant (NLL-v1.0-2026).
Zero-Trust Quantum Benchmarking: Cryptographic Pre-Registration via the OSIRIS Write-Ahead Ledger Author: Devin Phillip Davis Affiliation: OSIRIS Architecture Group Date: September 2026 DOI Reference: 10.5281/zenodo.23045494 Abstract As quantum hardware scales toward practical fault tolerance, the empirical validation of quantum advantage claims faces a systemic replication crisis. Traditional benchmarking methodology relies heavily on post-hoc error mitigation, unverified post-selection, and opaque calibration timing. We present Zero-Trust Quantum Benchmarking, a methodological paradigm and open protocol that eliminates retrospective bias by enforcing immutable, pre-execution cryptographic commitments. Using the OSIRIS Continuous Relativistic State Matrix (CRSM) framework, transpiled quantum circuit manifests and hypothesis thresholds are hashed (
SHA-256) into an append-only write-ahead ledger prior to dispatch to physical Quantum Processing Units (QPUs). We validate this protocol through empirical execution on IBM Quantum's 156-qubit Heron r2 hardware (ibm_marrakesh, Job ID: dau0q3qhcrkc73durtgg). The pre-registered manifest bound a novel bipartite-staggered dynamical decoupling sequence (xy8_stag) targeting residual
ZZ-crosstalk. On an 8-qubit chain, the pre-registered trial achieved a mean survival probability
P(+)=0.8998 at
T=32 μs, representing a +30.5% gain over bare idle (
P(+)=0.5945) and a +6.5% gain over standard simultaneous dynamical decoupling (
P(+)=0.8342), satisfying all pre-registered non-overlapping 95% bootstrap confidence intervals without post-hoc fitting. I. Introduction & The Crisis of Provenance Quantum computing research currently lacks an end-to-end chain of custody for experimental data. Due to environmental noise fluctuation, thermal drift, and cross-talk, QPU performance changes dynamically on time scales ranging from minutes to hours. This instability introduces three major vulnerabilities into published quantum benchmarks: Calibration Arbitrage: Experiments executed across hundreds of QPU calls can selectively showcase runs coinciding with transient calibration peaks while silently discarding noisy trials. Post-Hoc Hypothesis Modification: Error mitigation models and threshold parameters are frequently tuned after observing raw state-vector outputs, confusing exploratory curve fitting with confirmatory validation. Data Loss & Black-Box Execution: Published results rarely preserve transpiled machine-level pulse schedules alongside raw hardware counts and system calibration logs, rendering independent third-party replication practically impossible. To establish verifiable quantum advantage, the field requires a shift to Zero-Trust Quantum Benchmarking, wherein hardware execution permissions are contingent upon prior, tamper-evident pre-registration of experimental intent. II. The OSIRIS Write-Ahead Ledger Protocol The OSIRIS framework enforces experimental integrity via a write-ahead append-only ledger architecture integrated directly into the CI/CD pipeline and QPU submission harness. ┌─────────────────────────────────────────────────────────────────────────┐ │ OSIRIS PRE-REGISTRATION PIPELINE │ └─────────────────────────────────────────────────────────────────────────┘ │ 1. Circuit Synthesis ▼ ┌─────────────────────────────────────────────────────────────────────┐ │ Transpile Target Topology & Gate Schedule │ └─────────────────────────────────────────────────────────────────────┘ │ 2. Manifest Hashing ▼ ┌─────────────────────────────────────────────────────────────────────┐ │ Hash (Transpiled Circuit + Hypotheses + Metrics) -> SHA-256 │ └─────────────────────────────────────────────────────────────────────┘ │ 3. Ledger Write Ahead ▼ ┌─────────────────────────────────────────────────────────────────────┐ │ Append Hash to Write-Ahead Ledger (ledger.jsonl) & Update Head │ └─────────────────────────────────────────────────────────────────────┘ │ 4. QPU Job Submission ▼ ┌─────────────────────────────────────────────────────────────────────┐ │ Dispatch to Hardware (IBM Heron r2: ibm_marrakesh) │ └─────────────────────────────────────────────────────────────────────┘ │ 5. Verification & Audit ▼ ┌─────────────────────────────────────────────────────────────────────┐ │ Bind Raw QPU Counts to Ledger Entry and Publish Artifact Package │ └─────────────────────────────────────────────────────────────────────┘ A. Manifest Schema A Pre-registration Manifest (
M) is defined as an immutable JSON document containing: Circuit State: Unrolled OpenQASM 3.0 / Qiskit compiled instructions, physical qubit mappings, and pulse duration definitions. Target Environment: Target backend identifier, scheduled execution window, and expected calibration parameters. Pre-declared Hypotheses: Exact quantitative thresholds (e.g., minimum target fidelity gain
ΔFtarget) and statistical evaluation functions (e.g., 95% bootstrap CI parameters). The manifest vector is serialized into a canonical UTF-8 byte stream and hashed using
SHA-256:
HM=SHA-256(Canonicalize(M)) B. Append-Only Ledger Chaining Each entry
i in the OSIRIS ledger (
Li) contains the hash of the current manifest
HM,i, a UTC timestamp
ti, the state of the preceding block head
HL,i−1, and execution metadata:
HL,i=SHA-256(HL,i−1∥HM,i∥ti) This cryptographic chaining guarantees that modifying, deleting, or reordering any pre-registration attempt breaks the ledger head hash
HL,head, preventing silent trial deletion. III. Structural Comparison FeatureTraditional Quantum BenchmarkingOSIRIS Zero-Trust Benchmarking Execution TriggerAd-hoc script / manual notebook executionAutomated, deterministic CI/CD pipeline lock Circuit CommitmentMalleable, often post-processedImmutable pre-registered SHA-256 manifest hash Noisy Trial PolicyDiscarded or filtered unrecordedAppended permanently to immutable audit trail Verification BasisTrust in institutional reputationCryptographic verification (
HM↔JobID↔Counts) Fitting IntegrityPost-hoc curve fitting allowedPre-declared quantitative pass/fail thresholds IV. Empirical Hardware Validation: IBM Heron r2 (ibm_marrakesh) To validate the Zero-Trust protocol under production conditions, we pre-registered and executed a quantum control experiment on IBM Quantum's 156-qubit Heron r2 processor (ibm_marrakesh). A. Experimental Setup & Cryptographic Provenance Job ID: dau0q3qhcrkc73durtgg Target Backend: ibm_marrakesh (Heron r2, 156 Qubits) Execution Date: 2026-09-29 19:10:20 UTC QPU Execution Duration: 5.0 seconds Calibration Hash: 63f10bd484207c5044237b4115a46a0d29856036c923a2cde165baed57d15c9c Pre-registration Manifest SHA-256: 2d4c19a4a53301a1ac42459acd8b5b0d8cba0d588fa2523ed0994e5e1612d2f9 Ledger Head Hash: 6d7fd1390c1bab25b52f3e5e07be893aaa7194d8e3bd81db8466085da6e38d37 B. Dynamical Decoupling Physics: Bipartite Staggering Static and residual dynamic
ZZ-crosstalk on heavy-hex hardware topologies remains a primary source of decoherence during multi-qubit idle periods. Standard textbook dynamical decoupling applies simultaneous
π-pulses (e.g., CPMG, XY4) across all active qubits. However, simultaneous pulse execution on neighboring qubits induces pulse-collision errors and driven cross-resonance noise. OSIRIS introduces Bipartite-Staggered Dynamical Decoupling (xy4x2_stag, xy8_stag). The 8-qubit linear chain
[1,2,3,4,5,6,7,8] is partitioned into two disjoint sublattices:
SA={1,3,5,7},SB={2,4,6,8} π-pulse schedules are temporal phase-shifted between
SA and
SB, ensuring that no two adjacent qubits undergo simultaneous rotations, canceling crosstalk while preserving coherence. Sublattice A (Q1, Q3, Q5, Q7): ──[ X ]──────────────[ Y ]──────────────[ X ]── Sublattice B (Q2, Q4, Q6, Q8): ──────────[ X ]──────────────[ Y ]────────────── τ_stag τ_stag τ_stag τ_stag C. Empirical Results The experimental trial evaluated coherence retention across four conditions at time delays
T=16.0 μs and
T=32.0 μs. Effective loss rate
Γ was derived using
Γ=−T1lnP(+). Hardware Execution Summary Table ConditionT (µs)Mean Survival P(+)95% Bootstrap CIEffective Loss Rate Γ (µs⁻¹) none (Idle)16.00.6382[0.6313, 0.6450]0.0280 none (Idle)32.00.5945[0.5942, 0.5947]0.0162 cpmg816.00.9139[0.9075, 0.9204]0.0056 cpmg832.00.8344[0.8289, 0.8398]0.0056 xy4x2 (Simultaneous)16.00.9135[0.9097, 0.9172]0.0056 xy4x2 (Simultaneous)32.00.8342[0.8291, 0.8394]0.0056 xy4x2_stag (OSIRIS)16.00.9313[0.9307, 0.9319]0.0044 xy4x2_stag (OSIRIS)32.00.8997[0.8945, 0.9048]0.0033 xy8_stag (OSIRIS)16.00.9318[0.9309, 0.9326]0.0044 xy8_stag (OSIRIS)32.00.8998[0.8982, 0.9014]0.0033 SURVIVAL PROBABILITY AT T = 32 µs 1.00 ┌──────────────────────────────────────────────────────────────────┐ │ █████████ █████████ │ 0.80 │ █████████ █████████ ██ xy4x2 │ │ xy8 │ │ │ │ cpmg8 │ │ xy4x2 │ │ _stag │ │ _stag │ │ 0.60 │ █
Eight verified quantum computing jobs executed on IBM Quantum hardware (ibm_fez Heron R2, 156 qubits; ibm_torino Heron R1, 133 qubits) between January 27 and March 15, 2026. User ID: IBMid-692001DJRD. Experiments include: 1. Bell State Entanglement — 96.3% fidelity on ibm_fez Heron R2 (Concurrence C = 0.926, Tangle T = 0.858, 1,000 shots). Cross-platform benchmark: Heron R2 vs Heron R1 (+8.3 pp fidelity advantage, noise ratio 2.43×). 2. Reproducibility Test — Two independent runs of identical circuit (χ² = 2.70, p = 0.44, df = 3). H₀ not rejected: statistically indistinguishable results at 95% confidence. 3. BB84 Quantum Key Distribution — Full Alice/Eve/Bob protocol implementation. Alice baseline error 0.60% → Bob QBER 49.0% under eavesdropping (82× degradation). Experimental demonstration of the quantum no-cloning theorem. Control group design isolates eavesdropper signal from hardware noise baseline. 4. Variational Quantum Circuit (VQC) — 2-qubit circuit, 10 trained parameters with tied weights (θ₃ = θ₄), 8 CZ gates in 4 entangling layers. 4-qubit ansatz: Shannon entropy 3.885/4.000 bits (97.1%), ground-state bias confirmed (χ² = 300.94, p ≈ 0). 5. Quantum Random Number Generation (QRNG) — 8-bit outputs, 10/10 unique values per shot (range 16–254). Total: 39,010 quantum measurements across 8 jobs and 10 circuits. QPU time: 4.8 seconds. Job completion rate: 100%. All results decoded from raw IBM SamplerV2 BitArray binary archives (zlib + base64 + NumPy .npy pipeline). No simulations. Statistical validation applied throughout (Wilson 95% CIs, chi-squared tests). Stack: Qiskit Runtime SamplerV2 · QPY · OpenQASM 2.0 · Python · NumPy · SciPy Repository: https://github.com/dinohatibovicWhitepaper: https://dinohatibovic.github.io (Doc QAI-WP-2026-01-28-V4)