Version 2: pre-registration addendum for Phase D Outcome of the registered gate (G0) The G0 gate failed for every dataset, window family and null. No twin built from independent error mechanisms with circuit-local supports reproduces the bulk of the window-count distributions in the public data from Google Willow, Google Sycamore or Rigetti. For larger codes the twin cannot even be simulated. As the protocol requires, hypotheses H1–H3 are therefore not tested. This version adds pre-registration addendum 1. It fixes the analyses run instead, before either touches the test halves: • Model-free certificate (T3), on the test halves. It covers every registered configuration that has a circuit (the Google archives and Rigetti D6e). Windows are whole-patch windows of 1 and of 5 rounds, separated by one unused round, and the disjointness of their fault-location sets is checked from each circuit. Each stratum (archive, code family, code distance, window family) gets a premise curve ε_lo(k) on the grid k = c·j, j = 1–16, with Bonferroni correction at family-wise α = 0.05.• Threshold values for the certificate. ε* = 7.4 × 10⁻⁴ (Fowler, PRL 109, 180502, 2012) is the primary value; 2.73 × 10⁻⁵ (Aliferis, Gottesman and Preskill, QIC 6, 97, 2006) is a sensitivity check. Certificates against ε* are computed for surface-code strata only. Repetition-code, colour-code and stability strata get premise curves only.• Bursts. The primary analysis uses all windows; a secondary one excludes the windows flagged by the frozen burst classifier. B1/B2 event rates are reported descriptively.• Cat-qubit case study (exploratory). The model-based premise meter is applied to the AWS cat-qubit (D4) distance-3 configurations whose twin was simulable in G0. It reports R(k) intervals and k_cert, with the H1 reading (consistent if R_hi ≤ 3 for all k ≤ k_cert). It is labelled exploratory because D4's own G0 verdict is a fail. Status of the data when version 2 was created G0, which uses only the bulk bins, has run on the test halves. Its stored histograms include tail bins, but no tail statistic has been computed or examined. Both new analyses were dry-run on fit halves as pipeline checks. One choice was made after that dry run, and it is recorded in the addendum: ε* certificates were limited to surface-code strata, and strata were split by code family. The dry run had shown repetition-code and stability strata crossing ε* at k = c, i.e. at their base error rate, where Fowler's surface-code theorem does not apply. The model-based certification horizon is not computed, because it needs a twin tail. Files added in version 2 • phaseD_addendum.json: the machine-readable addendum. SHA-256: a458bcb40aa474d94a882a563a38a1a152d7bfb4404df9299f99fb020ab78834• ADDENDUM.md: the readable version of the addendum.• qpremise_code_phaseD_ade59b0.zip: the code that will run. The addendum's code_sha256 (794122ae1557c009664127e1c2e6b109781d5a71efcc566bc637b991c0403ab6) can be recomputed from it as the SHA-256 over the files matching qpremise/**/*.py, phaseD/scripts/*.py and phaseC/scripts/run_g0.py, taken in path order: each file's relative path, then its bytes with LF line endings.• SHA256SUMS_addendum.txt: checksums of the three files above. The version 1 files are unchanged. The original registration text follows. ──────────────────────────── Version 1 registration (2026-10-01) What this registers The analysis protocol of the premise meter. It tests whether public quantum-error-correction syndrome data agree with an independent-noise "twin" fitted to the same data. It also measures how far each dataset can certify the local-stochastic premise of the threshold theorem. Every analysis choice is fixed in frozen_protocol.json:• configuration eligibility, and the pre-registered subset in g0_selection.json;• the interleaved fit/test split;• the window families;• twin construction: candidate mechanisms from each circuit, an exact parity-moment fit, and a signed quasi-probability simulation with local weights;• the G0 gate decision rule;• the burst classifiers B1 and B2 with their validation targets;• the excess-tail-ratio interval and the certification-horizon conditions;• the model-free certificate's window rule. qpremise_code_at_freeze_79dbf14.zip holds the analysis code at the freeze. The protocol's code_sha256 can be recomputed from it: the SHA-256 over every qpremise/**/*.py file in path order, each file's relative path followed by its bytes with LF line endings. Hypotheses analysed after this registration (on test halves only) H1. After removing windows flagged by the frozen burst classifier, the excess tail ratio R(k) = P_obs(K ≥ k) / P_twin(K ≥ k) has an upper 95% confidence bound ≤ 3 for all k ≤ k_cert. Failure: a lower bound > 3 that replicates on the held-out half. H2. Including burst windows, R(k) > 10 for k ≥ k_b in at least one dataset, and a burst-mixture model fitted to the flagged windows predicts the published repetition-code error floor within a factor of 10. H3. The empirical horizon (power ≥ 0.8 at α = 0.05 against a factor-5 excess) agrees with the exact binomial computation within ±1. At least one dataset certifies k ≥ 10 in whole-patch windows. These are evaluated only on (dataset, window family) pairs that pass the G0 gate under both the stationary (N1) and drift-aware (N5) twins. The model-free certificate (T3) does not depend on the twin. Its threshold ε* is fixed before any certificate is computed. Timing and what had been seen Frozen 2026-10-01 17:31 IST (git commit 79dbf14). Before the freeze, only fit halves had been analysed. The G0 gate (bulk of the window-count distributions only; decision rule frozen) began on the test halves minutes after the freeze. When this record was created, no tail statistic (R(k), H1–H3, burst rates, certificates) had been computed from the test halves, and their tail bins had not been examined. The planned cloud-hardware contrast experiment (H4, H5) is not part of this registration and will be registered separately before any hardware run. Full details are in PREREGISTRATION.md. Protocol SHA-256: 5f7458cfdbe0e203fd9e2bf5d579703509c8374bae53096c37f8f1530540707a
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 │ █
Note: description expanded on 2026-10-14 for readability. It adds no new predictions or criteria. The frozen pre-registration is the attached PDF, unchanged since publication. Status: the experiment was run on 2026-10-14, after this record was published. Results, including every pre-registered test, will be reported in a separate record linked here. In plain language Theory says a quantum system never completely forgets where it started, even when its dynamics are chaotic. This leftover memory is called a quantum birthmark (Graf et al., Phys. Rev. X, 2026). Theory also says the birthmark should be larger when the system's rules run the same forwards and backwards in time (time-reversal symmetry) than when that symmetry is broken. This record pre-registers a test of that prediction on IBM's ibm_kingston quantum processor. We built two nearly identical sets of 4-qubit circuits. One set has time-reversal symmetry and the other does not. Both use exactly the same gates, so they experience the same hardware noise. We measure how often each circuit returns to its starting state, compared with the 1-in-16 chance level, and predict that the symmetric set shows about 1.67× more memory than the broken set. All predictions, pass/fail criteria, circuits and analysis code were deposited here before any quantum hardware was used. What is tested, and what is not Tested: whether the return probability stays above the ergodic baseline 1/16 at depths 8–23, and whether that excess is larger for the time-reversal-symmetric class by the ratio exact numerics predict for these fixed instances. Not tested: the withdrawn temporal-memory claims of 10.5281/zenodo.20470129. The birthmark is closed-system coherent memory, which measurement and reset erase, so no outcome here bears on those claims. Not tested: the universal random-matrix value 1.889. At this size (N = 16) the circuit family itself gives about 1.66, so a finite-size difference is expected. Not a quantum-advantage claim: a 16-dimensional system is exactly simulable. This is a hardware-validation experiment. Design Hardware: ibm_kingston, physical qubits 108–109–118–129 as an open chain, selected by a no-QPU calibration audit (included as v6_backend_audit.zip). Circuits: a kicked-Ising Floquet period Kx(a/2) → D(h1) → Kx(b) → D(h2) → Kx(a/2), with D(h) = exp(−iΣhiZi)·exp(−iπ/4 ΣZiZj), at exactly 6 CZ per period. COE (symmetric): h1 = h2. TRSB (broken): h1 = h + d, h2 = h − d. The classes differ only in virtual-Z angles. Instances: 16 seeded COE/TRSB pairs (seed 20261013), run at every depth from 8 to 23 (48–138 CZ). Observable: P(t) = |⟨0000|Ft|0000⟩|². The primary statistic is the readout-mitigated excess ratio R = ECOE / ETRSB, where E is the mean of P(t) − 1/16. A noise fidelity common to both classes cancels in R. Controls: 32 deep circuits (depths 60–63) as a decoherence-floor check. 8 state-preparation monitors. 16 readout-calibration circuits. Run: one SamplerV2 job of 568 circuits at 256 shots each, with dynamical decoupling and twirling off and the execution order shuffled. Predictions Quantity COE TRSB R Excess over 1/16, depths 8–23 (noiseless, primary) 0.0896 0.0537 1.667 Same instances, infinite-time limit 0.0952 0.0634 1.502 Circuit family, 10,000 random draws — — 1.661 Random-matrix reference, N = 16 — — 1.889 Under four simulated noise models (nominal, pessimistic, and each with coherent errors), the mitigated R stays between 1.64 and 1.77. The shot-noise standard deviation of R at 256 shots is 0.070–0.125. Pre-registered decision criteria Test Pass condition H1 (primary): symmetry dependence 99% CI lower bound of R > 1.0 H2 (primary): quantitative agreement 99% CI of R intersects 1.54–1.87 and is at most 1.0 wide S1: birthmark above decohered floor Window excess minus depth 60–63 excess, 99% CI lower bound > 0, for both classes S2: matched fidelity between classes 0.85 ≤ FCOE/FTRSB ≤ 1.15 S3: instance-level agreement Pearson r ≥ 0.80 against exact predictions S4 (flag only): state prep and drift Monitors ≥ 0.95, drift ≤ 0.045 Overall verdict: CONFIRMED if H1, H2 and S2 all pass; PARTIAL if H1 passes but H2 or S2 fails; NOT CONFIRMED if H1 fails. Every test is reported whatever the outcome. Uncertainty comes from a 10,000-sample parametric multinomial bootstrap over every circuit's counts, with instances held fixed. Amendment 1 (v1.1.0, made before any data) Amendment 1 changed two things relative to v1.0.0 (10.5281/zenodo.23355804): Shots: reduced from 1024 to 256 per circuit for QPU budget, cutting estimated execution from about 152 s to about 38 s. H2: changed from "point estimate in 1.54–1.87" to the CI rule above, because at 256 shots the point rule would falsely fail 20–25% of the time under the pessimistic models. A CI-width cap of 1.0 keeps H2 informative. Circuits, instances and predictions are unchanged. The trade-off is that H2 is now a weaker test. Provenance Every reported number is derived by script from raw counts: Source and transpiled circuits are saved as QPY. Before submission, every transpiled circuit is mapped back to 4 qubits and its unitary checked against the exact model to < 10−8. The analysis reads its decision bands only from predictions.json and its data only from the raw results file. Submission is gated on the DOI of this record. Files: The PDF is the authoritative pre-registration. predictions.json holds every predicted number and decision band. birthmark_prereg_v1.1.0.zip contains the circuit builder, verification, submission and frozen analysis scripts, plus simulated-data self-tests. v6_backend_audit.zip is the pre-submission calibration audit. Known limitations Small system size (N = 16), so the random-matrix value is not expected. The prediction is specific to depths 8–23 and to these 16 fixed instances. The noise models exclude leakage, TLS fluctuations and crosstalk from outside the chain. T1 relaxation biases P(0000) upward, which pulls R toward 1 (conservative). One backend, one path, one job: no replication. Data: CC BY 4.0. Code: MIT. Principal investigator: Amit Brahmbhatt, Quantum-Clarity LLC.
Proposal to the BlueQubit Quantum Flywheel open call (2026). Track 2 (breaking quantum advantage claims) with a Track-1 hardware component and a Track-3-adjacent seed. Aim 1 — execute the author's own hash-verified K₈ τ-sweep pre-registration (10.5281/zenodo.17918774, never run as written) exactly as specified on three IBM Heron backends under one pre-declared backend amendment; publish the outcome either way. Aim 2 — adversarial classical re-analysis of the author's 156-qubit / 10⁶-shot and 1,430-circuit "entropy suppression" datasets (10.5281/zenodo.19656600, 10.5281/zenodo.19505907) with coverage-adjusted estimators and tensor-network reproduction. Aim 3 — pre-registered hardware test of whether an auditable rule-evolving controller (organism_sim / bridge, 10.5281/zenodo.22862567) helps evolutionary dynamical-decoupling search under real calibration drift; four arms, binding criterion stated in PREREGISTRATION.md before any job. Includes PREREGISTRATION.md (binding criteria committed before submission of any hardware job), prepared form answers, and the supporting audits of the author's 60 prior records (HONEST_ASSESSMENT, FLYWHEEL_ASSESSMENT, PUBLICATIONS index). The archive is git archive of tag v1.0.0.
Pre-registration of a single confirmatory out-of-sample test. The hypothesis, frozen model parameters (fitted on 2024–2025 XAUUSD H1 data), classical comparator, test statistic and decision rule are fixed before any 2026 test data are processed. The record contains the registration document (PDF), the frozen parameters (JSON) and the test script (Python). SHA-256 hashes of the JSON and script are listed in Section 9 of the PDF. Version 2 supersedes version 1. It adds a seasonally adjusted condition (V2-SA) to the decision rule, introduced after calibration simulations and before any 2026 data were processed; see Section 8 of the PDF.
This registration freezes the preregistration document and the exact reference implementation (code, configs, and SHA256 manifest) for a single scarce “heavy” run of the CNC fork experiment in the T=2 binary-clock setting. The goal is to maximize the chance of a conclusive decision either way while extracting high-value diagnostics from the same dataset. Execution: Planned to be performed by an external hardware operator with IBM Quantum access. At the time of registration, Morgan Cameron has offered to execute the run, subject to availability. If executed by another operator, the executor identity and run artefacts DOI will be recorded in the post run dataset deposit. The preregistered protocol, code, and decision rule are independent of executor identity. Protocol, analysis, and report: Dale James Raymond. The authoritative analysis plan is CNC_T2_Fork_Heavy_Prereg_v2.pdf. The exact runnable artefacts are: cnc_t2_qiskit_harness_v3.py cnc_t2_runner_v3.py cnc_t2_config_heavy_v3.json (intended run) cnc_t2_config_lean_v3.json (sanity/layout scout only) RUNBOOK_T2_FORK_HEAVY_V3.md Integrity: SHA256SUMS.txt contains hashes for all files in this registration.