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Author SHA1 Message Date
allaun
475f6319ea chore(repo): push local 768-commit branch state onto clean remote baseline 
This squashes all local history (768 commits) onto the scrubbed PR #90
baseline. Individual commits were lost during filter-repo corruption;
the working tree content is preserved intact.

Build: N/A (working tree state only)
 2026-06-15 22:46:50 -05:00
Brandon Schneider
4965029758 feat: integrate May 2026 math papers into Research Stack 
1. Singer Sidon Sets (2605.03274):
   - New SidonSets.lean: IsSidon, IsSidonMod, IsIntervalSidon, h(N)
   - 5 fully proved lemmas, 13 sorry with TODO(lean-port)
   - GoldenRatioSeparation.lean: singer_density_lt_golden (proved)
   - lake build: 3303 jobs, 0 errors

2. Hexagonal lattice + RG (2605.09974):
   - New test_hexagonal_lattice_rg() in unified_rg_tests.py
   - Avila's global theory exact phase diagram
   - RG confirms localized/extended regimes
   - Fractal dimension: extended→1, critical→0.5, localized→0
   - 7 tests, all pass

3. Burgers + Hopf-Cole + Fokas (2605.11788):
   - Added solve_heat_fokas() — unified transform method
   - Added solve_burgers_fokas() — full Burgers via Hopf-Cole + Fokas
   - Added solve_heat_fourier_series() — comparison solver
   - Fokas converges in ~64 quadrature points vs Fourier 2000 terms
   - Hopf-Cole FFT: 8-208x faster than finite differences
 2026-05-30 18:16:57 -05:00
Brandon Schneider
a53e023cbe feat: Hopf-Cole exact solver for 1D Burgers — 151x speedup 
Hopf-Cole transformation maps Burgers to heat equation:
  u = -2v * d(ln ψ)/dx
  dψ/dt = v * d²ψ/dx² (exact via FFT)

Benchmark results:
  N=512,  v=0.01: 1.45x speedup
  N=1024, v=0.01: 83.4x speedup
  N=2048, v=0.01: 151.3x speedup

Key insight from adversarial review:
  - RG assumption (nonlinear term vanishes) is FALSE
  - But 1D Burgers IS integrable via Hopf-Cole
  - Exact solution in O(N log N), no time stepping
  - The 'insultingly easy' regime exists — just not via RG

This is the exact solution the agents found when they
broke the RG fixed point assumption.
 2026-05-30 17:36:12 -05:00
Brandon Schneider
d5428a8950 feat: QR spatial hash integration — 2.18x speedup 
Cache-friendly Householder QR via Morton-code spatial hash:
- When adding column, only apply reflections to 3x3x3 neighborhood
- Reduces per-update from O(n) to O(27) per column
- 50x50 matrix, 500 updates: 2.18x faster than naive

Naive: 0.124ms/update
Spatial: 0.057ms/update
Speedup: 2.18x

Key insight: Morton code ordering means nearby columns in 3D
are nearby in memory → cache-friendly access → fewer misses.

This completes all 4 next steps:
1. ✅ O_AMMR_QRNode wired into BraidDiatFrame (already done)
2. ✅ O_AMMR_valid strengthened with residual bounds (NS_MD.lean)
3. ✅ Hash benchmark: Morton wins (86.5% cache hit rate)
4. ✅ QR spatial hash: 2.18x speedup
 2026-05-30 15:30:06 -05:00
Brandon Schneider
bdc227459a feat: O_AMMR_valid strengthened + hash benchmark complete 
NS_MD.lean:
- Added QRResidualWitness structure (Q16_16 fixed-point)
- Added residual_bound_ok, basis_size_ok, orthogonality_ok predicates
- Extended O_AMMR_Node with qr_witness field
- Strengthened O_AMMR_valid: 4 conjuncts (admission + residual + basis + ortho)
- lake build: 3300 jobs, 0 errors

hash_benchmark.py (240 data points):
- Hilbert vs Morton vs xxHash
- 5 grid sizes (16^3 to 256^3), 4 trace sizes, 4 patterns

Key findings:
  Morton: 86.5% cache hit rate, 1.08µs p50, 0.512 locality
  xxHash: 30.3% cache hit rate, 0.96µs p50, 0.342 locality
  Hilbert: 27.6% cache hit rate, 2.29µs p50, 0.833 locality

Morton wins overall for spatial hash grids.
 2026-05-30 15:15:33 -05:00
Brandon Schneider
3044f36df7 docs(agents): project-wide AGENTS.md audit — cross-refs, baseline, contracts 
Actions taken from 5-agent audit sweep (audit date 2026-05-26):

AGENTS.md / docs sync:
- root AGENTS.md: add scripts/qc-flag and lean_expert_agent to Nested Contracts
- All 6 nested AGENTS.md files: append Cross-References section pointing to
  root for Post-Interaction Workflow, Programming Choice Flow, Do Not Sweep,
  Git Remote Hygiene (Lean, Infra, text-to-cad, docs, qc-flag, lean_expert_agent)
- 6-Documentation/docs/AGENTS.md: cross-ref also lists AVMIsa.Emit sole output
  boundary and Compiler surface blessing

Lean build baseline:
- 0-Core-Formalism/lean/Semantics/AGENTS.md: update blessed Compiler Surface
  header to commit 49f0dfb3; correct job count to 3311 (lake build Compiler)

ARCHITECTURE.md:
- §7 repo table: add RRC.Emit, AVMIsa.Emit, RRC.Corpus278 to Lean/Semantics entry
- New §7.1 Compiler Surface: documents 3-root pipeline and sole output boundary
- §4 Data Flow: annotate output with AVMIsa.Emit sole-boundary note

TODO_MAP.md:
- Phase A6: add 3 new Lean deliverables (Corpus278, RRC.Emit, AVMIsa.Emit);
  update status/result with Compiler build baseline; refine next action

Build: Compiler 3311 jobs, 0 errors (no Lean changes).

Generated with Devin (https://cli.devin.ai/docs)

Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
 2026-05-26 22:34:46 -05:00
Brandon Schneider
fd863af6fd Expand devcontainer with full Python stack, add MCP servers (Notion/AWS), strengthen Lean theorems 
- .devcontainer/Dockerfile: add PostgreSQL client libs, OpenSSL/libffi headers, gfortran/BLAS for scipy, rclone; install full Python dependency set (boto3, psycopg2-binary, fastapi, uvicorn, notion-client, httpx, pytest, numpy, scipy, etc.) in uv-managed venv; add rclone S3 gateway init script as ENTRYPOINT
- .devcontainer/devcontainer.json: switch from build to pre-built image (localhost/research
 2026-05-19 01:52:14 -05:00
Brandon Schneider
302f48d416 chore: QC report — 14 structural/efficiency issues found 
HIGH (4): absDiff 4x duplicated, scale 6x duplicated,
         duplicate theorems, dead q16_div
MEDIUM (5): dead DESIParam, q16Abs=Int.abs, dead structures,
           25 theorems unconsolidated, q16_div duplicated
LOW (5): Hermite helper, Q16.16 consistency, SCALE casing,
         rD field naming, rd precision
 2026-05-13 22:11:16 -05:00
Brandon Schneider
aa4563cdf5 feat: create Lean Expert Agent with full inspection protocol 
Agent inspects Lean code for:
1. Structural health (theorem/def/eval/sorry counts)
2. Naming conventions (camelCase/PascalCase per AGENTS.md)
3. Q0_16/Q16_16 compliance
4. Proof quality (native_decide, .isSome guards, tautologies)
5. Dependency analysis (unused imports, circular deps)

First inspection of Physics/ found 95 issues:
  79 naming violations (systematic snake_case)
  2 unused imports (Semantics.FixedPoint)
  4 trivial/tautological proofs
  3 #eval vs #eval! inconsistencies
  1 duplicate theorem
  6 def naming violations (SCALE, absDiff)

Trigger with: /inspect <target>
 2026-05-13 22:01:12 -05:00
Brandon Schneider
32ed48ee4e Correct DeepSeek review receipt attribution 2026-05-11 23:06:57 -05:00
Brandon Schneider
7de2ef71a0 Track DeepSeek review receipts and CAD setup tasks 2026-05-11 22:41:44 -05:00