Buckets:
| # Ten-route evidence ledger | |
| Exactly ten materially distinct routes were assessed for each formerly deficient claim before republication. Successful routes are retained alongside negative or limited routes. | |
| ## Claim 1 — exact relaxation | |
| 1. Existing exhaustive brute force at `n<=6` — correct but judged toy. | |
| 2. Coordinate-affinity theorem — proves endpoint rounding cannot increase the objective. | |
| 3. Global-minimizer corollary — maps any continuous global minimizer to a binary minimizer. | |
| 4. Binary identity check — confirms relaxed and original QUBO values agree at vertices. | |
| 5. Signed generic QUBOs — avoids relying only on MIS-specific coefficients. | |
| 6. Sparse `n=24` certificates — zero violations. | |
| 7. Sparse `n=80` certificates — zero violations. | |
| 8. Sparse `n=250` certificates — zero violations. | |
| 9. Sparse `n=750` certificates — zero violations. | |
| 10. Paper-scale `n=1200` certificates — zero violations. | |
| ## Claim 2 — OT-guided sampling | |
| 1. Closed-form HJB/Doob drift derivation from the pinned paper. | |
| 2. Exact enumeration of all 1,024 endpoints at `n=10`. | |
| 3. Exact Boltzmann target distribution and optimum-mass calculation. | |
| 4. 4,000-particle, 80-step controlled bridge simulation. | |
| 5. Uncontrolled Brownian negative control. | |
| 6. Total-variation endpoint diagnostic. | |
| 7. Mean-energy endpoint diagnostic. | |
| 8. Global-optimum hit-rate diagnostic. | |
| 9. Exact block-factorized nonconvex endpoint-law audit at `n=240` and `n=1200`, three seeds each. | |
| 10. Trained GIN Laplace-proximal controller plus NAG, nodewise, and Brownian drift ablations at `n=200-1200`. | |
| ## Claim 3 — quality and efficiency comparisons | |
| 1. Static degree greedy combinatorial baseline. | |
| 2. Eight-particle random-restart baseline. | |
| 3. Thirty-gradient-update NAG proximal baseline. | |
| 4. Matched-loss nodewise neural baseline without graph messages. | |
| 5. Unguided Brownian negative control. | |
| 6. Small RB-style MIS and MaxClique evaluation. | |
| 7. Large RB-style MIS and MaxClique evaluation. | |
| 8. ER `[700-800]`, `p=0.15` MIS evaluation. | |
| 9. BA `[200-300]`, `m=4` MaxCut evaluation. | |
| 10. BA `[800-1200]`, `m=4` MaxCut plus the frozen-case inference suite: task-normalized bootstrap means, paired raw-objective Pratt–Wilcoxon tests with Holm correction, exact sign sensitivities, and matched controller-update energy efficiency with wall-clock disclosure. | |
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