# Attack Plan: From Suspect to Receipt **Status:** ACTIVE — every result suspect until receipt matches conjecture **Date:** 2026-07-04 **Principle:** No claim is accepted without a receipt. Conjecture → prediction → measurement → receipt → accept or reject. --- ## The 13 Things We Actually Have | # | What | Type | Receipt | |---|------|------|---------| | 1 | sidon_preserved_mod (2-moduli CRT Sidon) | Lean proof | CRTSidon.lean, 0 sorries, lake-built (verified on prior runs) | | 2 | helical_coverage_74 (74 steps → 28 classes) | Lean proof | HopfFibration.lean, native_decide | | 3 | ofChiralLabel_isUnit (ChiralLabel → unit quat) | Lean proof | HopfFibration.lean | | 4 | ring_fastest (ring > SUBLEQ > AVX-512) | Lean proof | HCMR.lean, simple omega | | 5 | Conservation law (program + residual ≥ K(data)) | Measured | 8 experiments, real bytes, weird_machine_conservation_law.md | | 6 | Chiral invariance (flat CRT negation, odd L) | Proven + measured | 50K trials, ring automorphism proof | | 7 | Hoffman gap=1 for unit-distance graphs | Measured | numpy eigenvalues, 6 graphs, hn_spectral_database.json | | 8 | q-profile sweep (q>1 = 100% Sidon) | Measured | crt_qprofile_sweep.json, exact arithmetic | | 9 | Photonic Sidon 18/18 PASS | Measured | Perceval SLOS, photonic_sidon_evidence.jsonl | | 10 | pipeline_core.py runs (binary swaps) | Implemented | chiral_batch_pipeline.json, 256→64 | | 11 | dna_braid.wgsl (GPU braid sort) | Implemented | Existing, tested | | 12 | dna_radix_gpu.py (GPU QUBO sort) | Implemented | Existing, tested | | 13 | BraidStateN.lean ChiralLabel/Rossby | Lean, compiles | Prior lake build passed | --- ## Conjectures to Validate (in priority order) ### C1: CRTSidonN.lean compiles **Conjecture:** The n-moduli generalization is valid Lean that compiles. **Prediction:** `lake build SilverSight.CRTSidonN` exits 0. **Receipt needed:** Build log showing 0 errors. **Status:** Lake build running (currently at ~73% of full Mathlib). **Action:** Wait for build, check exit code. ### C2: HCMR suite compiles **Conjecture:** The 5 new modules (HCMR, CacheSieve, Blitter6502OISC, YangMillsPerformance, WorkloadTestbench) compile with 2 sorries. **Prediction:** `lake build` exits 0 with exactly 2 sorries (CacheSieve.evict_prefers_reset, YangMillsPerformance.compression_overhead_bounded). **Receipt needed:** Build log + sorry count. **Status:** Same lake build run. **Action:** Check build output for error count and sorry locations. ### C3: Positional chiral pipeline produces non-uniform Sidon results **Conjecture:** The positional chirality (permuting phases across strand positions) produces DIFFERENT Sidon results for different chiral configs. **Prediction:** Not all 2^k configs have the same collision count (unlike flat negation, which was 100% uniform). **Receipt needed:** pipeline_core.py output with `--filter crt` showing variance in collisions across configs. **Status:** UNTESTED. The previous run used flat negation (chiral-invariant). **Action:** Run pipeline_core.py with positional chirality on CPU compute. Compare collision counts across configs. If all identical → positional chirality is also invariant (conjecture FALSE). If variance exists → conjecture TRUE. ### C4: Quaternion product Sidon filter discriminates chiral configs **Conjecture:** The QuaternionSidonFilter (Hamilton product of 1,i,j,k basis) produces different results for different chiral configs. **Prediction:** Some configs pass (0 collisions), others fail (>0 collisions). **Receipt needed:** pipeline_core.py output with `--filter quat` showing variance. **Status:** UNTESTED. Previous DQ run gave 0/64 (all fail) — but that was with flat negation, not positional. **Action:** Run with positional chirality + quaternion filter. If variance → TRUE. If uniform → FALSE. ### C5: COUCH Kelvin check actually filters **Conjecture:** Configs with Rossby drift = 0 (Kelvin regime) exist in the 65K cross-enriched space and are rejected by COUCH. **Prediction:** Some of the 65K configs have drift=0 (all-achiral or balanced left/right). These should be rejected. **Receipt needed:** COUCH pass count < total, with some configs tagged "kelvin". **Status:** UNTESTED. **Action:** Run pipeline with k=8, count Kelvin-rejected configs. ### C6: Cross-enrichment (4^8 = 65K) runs on GPU **Conjecture:** chiral_cross_enrich.wgsl compiles and runs, processing 65K configs. **Prediction:** GPU dispatch completes, output buffer has 65K results. **Receipt needed:** WGSL compilation + dispatch log + output JSON. **Status:** UNTESTED. Shader is written but never compiled. **Action:** Test on GPU pod (A40 or user's WebGPU node). Check compilation, then run. ### C7: HCMR self-loop probabilities are measured (not just defined) **Conjecture:** The values 0.823, 0.885, 0.0 come from real EPYC KVM benchmarks. **Prediction:** A benchmark log or measurement file exists with these values. **Receipt needed:** Benchmark output showing these numbers. **Status:** SUSPECT. The Lean module DEFINES them as constants. No measurement file found. **Action:** Search Research Stack for benchmark logs. If none found → relabel as "assumed" not "measured". ### C8: q-profile sweep result (q>1 = 100% Sidon) is robust **Conjecture:** The q>1 preference holds across different label sets and moduli. **Prediction:** Reproducing with different Sidon label sets gives the same q>1 preference. **Receipt needed:** Re-run with 3+ different label sets, check q>1 rate. **Status:** Measured once (3 label sets). Need more. **Action:** Run q-profile sweep with 10+ random Sidon label sets. ### C9: Hoffman gap=1 is universal for unit-distance graphs **Conjecture:** All unit-distance graphs have Hoffman gap=1 (not just Moser/Golomb). **Prediction:** de Grey 1581 graph also has gap=1. **Receipt needed:** Hoffman bound on de Grey 1581. **Status:** UNTESTED (the --full flag never ran successfully). **Action:** Run hn_spectral_database.py --full on GPU pod (needs numpy for 1581×1581 eigenvalues). ### C10: Rossby drift correlates with QUBO tractability **Conjecture:** QUBO instances with Rossby drift=0 (Kelvin) are harder for QAOA. **Prediction:** Kelvin-regime QUBO instances have flatter energy landscapes. **Receipt needed:** QUBO energy landscape measurement + Rossby drift correlation. **Status:** ENTIRELY SPECULATIVE. No experiment designed. **Action:** Design experiment: generate random QUBO instances, compute Rossby drift from chiral encoding, measure energy landscape flatness, check correlation. --- ## Execution Order ``` Phase 0: VERIFY FOUNDATION (blocking) C1: CRTSidonN compiles? → lake build (running) C2: HCMR suite compiles? → same build C7: HCMR self-loops measured? → search Research Stack Phase 1: TEST THE PIPELINE (blocking) C3: Positional chirality varies? → run pipeline_core.py --filter crt C4: Quaternion filter varies? → run pipeline_core.py --filter quat C5: Kelvin check filters? → count Kelvin-rejected in C3/C4 output Phase 2: GPU (after Phase 1 confirms variance) C6: Cross-enrich shader runs? → compile + dispatch on GPU C9: de Grey Hoffman bound? → run --full on GPU Phase 3: ROBUSTNESS (after Phase 2) C8: q-profile robust? → 10+ label sets C10: Rossby ↔ QUBO? → design + run correlation experiment Phase 4: QUANTUM (after Phase 3 confirms C10) QUBO/QAOA integration experiments ``` --- ## Rule Every conjecture has: 1. A PREDICTION (what we expect) 2. A RECEIPT needed (what would prove it) 3. A REJECTION criterion (what would disprove it) No conjecture is accepted until the receipt matches the prediction. If the receipt contradicts the prediction → conjecture is DEAD, update the theory. If C3 fails (positional chirality is also invariant): → The entire chiral filtering story is dead → COUCH (geometric) is the only discriminating filter → Sidon filter is decorative, not functional If C4 fails (quaternion filter is uniform): → The quaternion/S³ story is dead → Stick with CRT sums (proven, 2-moduli) If C10 fails (Rossby ≠ QUBO tractability): → The QUBO/QAOA bridge is dead → The pipeline is a combinatorial filter, not a quantum pre-filter Each failure narrows the theory to what's actually true.