Denominator Recovery and Post-Selection Audit in a GHZ Three-Body Model: A Two-Stage Search-Based Mechanism Check

hui wang

Published Apr 25, 2026• 0 citations

Abstract

This paper introduces a denominator-recovery audit framework for high-correlation claims in a GHZ three-body model, aimed at separating mechanism gain from post-selection bookkeeping gain. Within a unified pipeline, we compare `none` and `energy_weighted` denominator modes and run a two-stage search (90 deg coarse + 2 deg fine), while jointly auditing `F` and `coincidence_rate` trade-offs. Under the current configuration (`samples=80000`, `numba_cpu`, fixed gating), the best fine-stage candidate reaches only `F=0.085396`, remaining far from the target `F=4` with `|err|=3.914604`. Target-attainment decomposition consistently indicates correlation-shape mismatch as the dominant bottleneck rather than coincidence sparsity. Robustness indicators (bootstrap and seed sweep) do not show convergence toward 4 either. We therefore report a method-level conclusion: within the tested model family and protocol, no evidence supports an `F->4` transition. Strong GHZ-style claims should be evaluated through joint auditing of denominator logic, sample-inclusion rules, and retained failure cases. The contribution is a reproducible, ledger-style audit workflow for GHZ correlation studies. Code repository: https://github.com/tomnattle/chain-explosion-modelThis version adds explicit disclosure of the post-selection cost-benefit regime: while F can approach 4 under aggressive filtering, the retained sample ratio drops to about 25% (about 75% discarded). The update includes the corresponding cost-benefit curve and supporting artifacts.

DOI: 10.5281/zenodo.19763472

Related papers

Analysis Rule Sensitivity in Bell and GHZ Experiments: A Reproducible Audit Framework

hui wang

This paper synthesizes two published audit lines into a single reproducible framework for Bell and GHZ interpretation under analysis-rule sensitivity. Using public records and artifact-linked evidence, we show that Bell/CHSH on the same NIST event stream shifts from S_strict=2.336276 to S_standard=2.839387 (Delta=+0.503111) under protocol change, while GHZ search under the current audited pipeline remains far from F=4 (best fine-stage F=0.085396). We formalize a ledger-style audit protocol that treats pairing windows, denominator policy, post-selection, and uncertainty as first-class reported variables. We further introduce a singles-aware diagnostics layer (C_norm = coincidences / sqrt(singles_A * singles_B)) as a testable bridge for normalization-path analysis, while explicitly avoiding ontology-level promotion from current evidence. The contribution is a publication-ready, boundary-aware audit standard with claim-to-artifact traceability across both lines. Related records: Bell DOI https://doi.org/10.5281/zenodo.19763028 ; GHZ DOI https://doi.org/10.5281/zenodo.19763473 ; Code repository: https://github.com/tomnattle/chain-explosion-model

Apr 25, 20260 citations

Denominator-Audit Robustness Analysis for Bell/CHSH Statistics: A Reconciliation Study of Strict vs Standard Protocols

hui wang

We present a denominator-audit framework for Bell/CHSH statistics to disentangle mechanism effects from protocol-bookkeeping effects under a shared data context. The protocol compares strict and standard definitions in parallel and separates evaluation into an engineering gate (computability and basic data sufficiency) and a thesis gate (claim-level preregistered criteria). On the same NIST completeblind event stream, binary CHSH yields S_strict=2.336276 (window 0.0) and S_standard=2.839387 (window 15.0), i.e., Delta=+0.503111 from pairing-rule change alone. Bootstrap (n=2000) gives CI95_strict=[2.295151, 2.378669] and CI95_standard=[2.820420, 2.857413]; because 2sqrt(2)=2.828427 lies inside the standard CI, we do not claim Tsirelson violation. A simulated fallback run also shows that S_standard does not necessarily exceed S_strict, reinforcing protocol sensitivity. We report a method-level, boundary-aware conclusion: Bell/CHSH claims should be interpreted through protocol definitions, uncertainty intervals, and retained negative results, rather than peak statistics alone. Figures may be added in a subsequent version; current evidence is provided via tables and machine-readable result files.

Apr 25, 20260 citations

Ledger-Valid Recovery Diagnostics for Quantum Computing: A Prespecified Sequential Audit for Claim-Limited Recovery Validation

David Reardon

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.

Aug 15, 20260 citations

Post-Selection Sensitivity in a GHZ-Type Mermin Statistic: An In-Silico Audit (medium-v10) GHZ 型 Mermin 统计量的后选择敏感性:medium-v10 仿真审计(非硬件复刻)

Hui Wang

[EN] This deposit documents a rigorous in-silico post-selection audit of a GHZ-type Mermin statistic in the repository's medium-v10 wave model (three local phase-locked sources), motivated by textbook/laboratory GHZ narratives—it is not claimed to replay one specific hardware run. Within that simulator class, we show that chasing high F couples to amplitude gating and low retention, and matched-retention random controls fail to reproduce the gated lift—supporting a selection-driven reading of the reported metric inside the model. Using the V10.4 real cost curve and matched-retention random controls, we show that elevated F values in this simulator class are tightly coupled to selection rules and retention trade-offs. We frame this as a method-level sensitivity result inside the model class, not as a hardware-level claim. [中] 本归档记录对 medium-v10 波动模型中 GHZ 型 Mermin 统计量的严格仿真后选择审计(三个局域相位锁定源),动机来自教科书/实验室叙事,不声称复刻某一具体硬件实验。在该模拟器类内,我们展示:追逐高 F 与振幅门控及低保留率绑定,而同保留率随机对照无法复现门控抬升——从而在模型内支持对报告指标的筛选驱动解读。通过 V10.4 真实代价曲线和同保留率随机对照,我们展示了:在该模拟器类内,较高 F 与筛选规则及保留率权衡紧密耦合。本文将其定位为模型内的方法学敏感性结果,而非硬件层结论。 Reproducibility (repository): from repo root run python scripts/explore/ghz_medium_v10/v10_4_real_cost_curve.py (see script header for output paths). Companion figure in this deposit: figures/V10_4_REAL_COST_CURVE.png. 可复现(配套仓库): 在仓库根目录运行 python scripts/explore/ghz_medium_v10/v10_4_real_cost_curve.py(输出路径见脚本头部)。本归档插图:figures/V10_4_REAL_COST_CURVE.png。

Apr 26, 20260 citations

Auditable Null Results in Quantum Hardware Scaling: A Pre-Specified Falsification Study of QAOA Recovery Models

Devin Peters

Empirical scaling laws for the Quantum Approximate Optimization Algorithm (QAOA) on near-term hardware are often motivated by noise-compounding arguments or circuit-structure heuristics. Such models are rarely evaluated under pre-specified failure criteria that prevent post-hoc rescue. This study reports an audit-disciplined attempt to construct and test a predictive scaling law for QAOA-based minimal cut set recovery in fault tree models. The workflow used hash-locked artifacts, pre-specified kill switches, one-time holdout evaluation, and explicit no-rerun and no-rescue rules at every phase boundary. The initial F²-grounded compounding specification failed its pre-specified identifiability gate (KS3). Under an anti-leakage filter applied to 108 candidate rescue terms, zero candidates recovered a passing α₁ slope while also adding explanatory power above the structural baseline. A pre-specified structure-dominated fallback model was then defined and fit. The fallback reproduced its locked training prediction pathway to machine precision, with maximum absolute prediction difference of 3.55 × 10⁻¹⁵. It then failed the locked 24-row transport holdout. Holdout RMSE was 5.2214 against a locked threshold of 0.3770, and all 24 residuals were positive, giving a two-sided sign-test p-value of 1.19 × 10⁻⁷. The mean log residual of 5.198 corresponds to approximately 180-fold underprediction on the linear scale. Post-failure diagnostics indicated lower-n domain shift with standardized mean difference of −2.27 and four holdout rows with G_2q below the training range. By design, these diagnostics were explanatory only and did not authorize rescue, refit, reweighting, row removal, or threshold revision. The results do not support a deployable scaling law on the present corpus. Instead, they demonstrate that pre-specified audit controls can convert an attempted positive scaling-law claim into a reproducible falsification result with clear claim boundaries. The audit framework, the locked failure chain, and the allowed-and-forbidden claim boundary together constitute the paper's contribution. The work is offered as a methodological reference for future QAOA-on-hardware scaling studies.

May 13, 20260 citations

Denominator Audit of Bell/CHSH Statistics: Protocol Sensitivity to Pairing-Rule Definitions 贝尔不等式的分母审计:配对规则定义的协议敏感性分析

Hui Wang

Archive Notice (Deprecated): This record is kept for archival purposes and is no longer the current version. Please use the latest Bell Audit v5 record: https://zenodo.org/records/19904639 (DOI: https://doi.org/10.5281/zenodo.19904639). 留档提示(已过期): 本记录仅用于历史留档,已非当前版本。请优先访问最新版 Bell Audit v5:https://zenodo.org/records/19904639(DOI:https://doi.org/10.5281/zenodo.19904639)。 [EN] This paper presents a "Denominator Audit" of Bell/CHSH violations using NIST experimental data. Historically, violations of S > 2.0 are cited as proof of non-locality. Our audit reveals that these results are not intrinsic to the physical system but are "manufactured" through the selective manipulation of coincidence windows (Accounting Fraud). On the same NIST complete-blind stream, we compare a strict pairing tolerance (0.0) versus the Round-1 standard tolerance (15.0) in NIST grid-index units on the exported CSV t axis (not calibrated seconds in this deposit). The frozen binary-CHSH snapshot gives S_strict = 2.336276 vs S_standard = 2.839387 (Δ = +0.503111). A bootstrap CI for the standard branch includes 2\sqrt{2} (artifacts/reports/chsh_bootstrap_ci_standard15.json, ci_contains_tsirelson: true); we therefore discuss protocol sensitivity, not Tsirelson violation. Separately, the “30 cm truth” is a laboratory heuristic (about 1 ns ↔ ~30 cm in vacuum); it motivates coincidence bookkeeping sensitivity and must not be read as “parameter 15.0 equals 15 ns” here. Reproducibility (repository): data file data/nist_completeblind_side_streams.csv; run from repo root python scripts/explore/chsh_denominator_audit.py (writes artifacts/bell_window_scan_v1/). [中] 在同一组 NIST complete-blind 事件流上,我们在导出 CSV 的 t 网格上对比严苛配对容差(0.0)与第一轮标准容差(15.0),单位为 NIST 网格指数(本归档不将其标定为秒)。冻结的二元 CHSH 快照为 S_strict = 2.336276 与 S_standard = 2.839387(Δ = +0.503111)。标准分支的 bootstrap 置信区间覆盖 2\sqrt{2}(artifacts/reports/chsh_bootstrap_ci_standard15.json,ci_contains_tsirelson: true);因此本文强调协议敏感性,而非 Tsirelson 违背。另:“30 厘米的真相”是实验室启发(真空中约 1 纳秒 ↔ 约 30 厘米),用于提示符合会计的敏感性,不应被读作“参数 15.0 等于 15 纳秒”。可复现(配套仓库): 数据 data/nist_completeblind_side_streams.csv;在仓库根目录运行 python scripts/explore/chsh_denominator_audit.py(输出写入 artifacts/bell_window_scan_v1/)。

Apr 26, 20260 citations