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f9b3df0803
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feat(lean): modular Sidon preservation theorem + meta-review fixes
- CRTSidon.lean: full proof of sidon_preserved_mod (matches Python
CRT-reconstructed mod-M check). Uses Bezout via Nat.gcdA/Nat.gcdB
for CRT injectivity. 0 sorries.
- BraidEigensolid.lean/GoldenSpiral.lean: fix golden centering
constant (40560->40504, 0.14% relative error)
- AGENTS.md: flag StrandCapacityBound triviality, add CRTSidon status
- CITATION.cff: add Elsasser(1946) toroidal/poloidal prior art
- SLOS receipt: add classical-simulation disclaimer
- sidon_preservation_creation.md: mark creation theorem unformalized
- autoresearch: containerized via runpod/autoresearch base image
(silver-autoproof:latest), systemd service created
- LeanCopilotFill.lean: updated for new CRTSidon API
Build: 3297 jobs, 0 errors (lake build CoreFormalism.CRTSidon)
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2026-07-04 01:05:15 -05:00 |
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f1a050277b
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feat(slos): eigenvalue products predict SLOS concentration ordering - verified with Spearman correlation, cross-validated with exact tensor network
48 test points across K=1..4 and 12 label sets (Sidon power sets,
Sidon constructions, dense non-Sidon, prime-based).
Results:
K=1: ρ=-0.85 (products→SLOS), ρ=-0.94 (SLOS↔tensor)
K=2: ρ=-0.88 (products→SLOS), ρ=-0.94 (SLOS↔tensor)
K=3: ρ=-0.93 (products→SLOS), ρ=-0.98 (SLOS↔tensor)
K=4: ρ=-0.93 (products→SLOS), tensor N/A (K>3)
Key: all Spearman correlations are negative and strengthen with K.
Sidon sets produce 1.5-2.3× higher KL divergence than same-size non-Sidon.
Primes are intermediate: partially Sidon-like but weaker.
DAG: 192 nodes, 96 edges, all individually checkpointed for resume.
Resume with: python3 scripts/perceval_slos_verify.py --resume
Receipt: docs/research/SLOS_SIDON_VERIFICATION_RECEIPT.md
Build: N/A (Python/perceval verification, no Lean build)
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2026-07-03 17:55:26 -05:00 |
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