Finds related arxiv papers for cornfield concepts via keyword overlap.
Uses /shm/arxiv_texts.tsv (559 MB) for fast local matching.
pg_trgm GIN indexes on neon-64gb for Postgres queries.
Results: 240 candidate citations for 48 concepts.
Loaded into concept_citations table (relation_type='candidate').
Moves all classification authority from Python into Lean:
- Adds `0-Core-Formalism/lean/Semantics/PistClassifyTrace.lean` executable.
Reads a raw trace JSON and emits spectral radius, RRC shape, and tactic
family using `Semantics.PIST.Spectral` and `Semantics.PIST.Classify`.
- Registers `pist-classify-trace` in `lakefile.toml`.
- Fixes `Semantics.PIST.Spectral` power iteration to handle directed
transition matrices:
- `symmetrize` now preserves half-integer weights as Q16_16 raw values.
- `matVecMul` uses saturated Q16_16 arithmetic to prevent overflow.
- Rewrites `4-Infrastructure/shim/pist_trace_classify_offline.py` as a pure
I/O wrapper: reads JSON, calls the Lean classifier, optionally calls
`rrc-watchdog`, and emits the combined JSON. Removes Python-side spectral
computation, shape thresholds, tactic heuristic, and KNN.
- Updates `AGENTS.md` and `4-Infrastructure/AGENTS.md` with the new build
baseline and shim contract.
Verification:
- `lake build` → 8604 jobs, 0 errors
- Canary trace outputs match previous Python outputs to within Q16_16 rounding
(e.g., apply_chain λ_q16 = 59044 vs 59045).
- `python3 -m py_compile` on the rewritten shim passes.
Created a local, offline Python shim `pist_trace_classify_offline.py` that computes trace transition matrix spectra, maps the max eigenvalue to the Q16.16 spectral radius, evaluates the color-space shape classification logic from `Semantics.PIST.Classify`, and invokes the local `rrc-watchdog` Lean binary inside the podman container to verify alignment. This avoids querying the dead AWS RDS instance and saves LLM API tokens.
Build: 3314 jobs, 0 errors (lake build Compiler)
- qaoa_adapter.py: fix finsler_metric_to_qubo to store Q_ij + Q_ji per
undirected pair; update is_anisotropic and _find_anisotropic_pair to
accept raw_matrix so asymmetry detection still works after summation;
add measure option to pauli_to_cirq.
- benchmark_finsler_qaoa.py: new benchmark harness for Finsler-Randers
routing via QAOA.
Formulate directed Finsler routing as TSP-MTZ (QAP) using HiGHS MIP and
benchmark against QUBO subset-selection. Five solvers across four sizes.
Key results:
- QAP-MIP scales well: n=48 solves to feasibility in 13s
- QUBO degenerate for all-positive Q_ij (unconstrained always selects 0)
- 2-phase strategy viable: QUBO-card to select K, then TSP-on-subset
Build: N/A (Python shim)
Perceval is the photonic quantum simulation SDK used by
rrc_photonic_stress_test.py (SLOS backend). Already installed
system-wide; added to requirements.txt for venv reproducibility.
- Redirected the default RDS_HOST/PGHOST database connection default
to neon-64gb (100.92.88.64) across all Python shims, shell wrappers,
and Rust probes.
- Cleaned up local defaults in rds_connect.py, sync_wiki_to_rds.py,
dataset_ingest_rds.py, batch_embed_artifacts.py, db.rs, cache-offload.sh,
db-consolidate.sh, backup.sh, and ene-api-wrapper.sh.
Build: 0 jobs, 0 errors (lake build)
- Replaced database-1-instance-1.cghu8yqogqwo.us-east-1.rds.amazonaws.com
with 'localhost' as default.
- Removed AWS IAM generate-db-auth-token CLI subprocessing and boto3
token generation blocks from rds_connect.py, ingest_flexure_joints.py,
pist_route_repair.py, and ene-api-wrapper.sh.
- Purged AWS DEFAULT_REGION and AWS_REGION configurations where applicable.
- Updated Rust rds_probe to use standard PG environment variables.
Build: 0 jobs, 0 errors (lake build)
Implemented rrc_bosonic_db_buffer.py containing AsyncDatabaseBuffer
which queues, batches, and flushes PostgreSQL inserts for bosonic tensor
network receipts and metrics. Documented both rrc_bosonic_tensor_gpu.py
and rrc_bosonic_db_buffer.py in 4-Infrastructure/AGENTS.md.
Build: 0 jobs, 0 errors (lake build)
Encodes each Burgers representation as a node connected by proven
isomorphisms from the codebase. Continuous-time quantum walk e^{-iAt}
on the adjacency matrix converges to eigenvector centrality; the
0D DualQuat Braid is confirmed as the universal hub (#1 in all three
rankings: centrality, quantum walk probability, and degree).
Build: N/A (Python shim, no Lean files touched)
Replace the TODO(lean-port) sorry with a complete proof of the
projectionOrdering theorem: for positive SourceValue pairs s1 < s2
with s2 ≤ maxExpected, projectToCoding preserves strict ordering
of the Q0_64 values.
The proof uses Nat-only arithmetic (no Float) and handles two cases:
- a2 < d: both values fit in Q0_64 range, ordering follows from
monotonicity of integer division
- a2 = d: a2*s/d = s clamped to q0_64MaxRaw; a1*s/d < q0_64MaxRaw
via the key inequality (d-1)*s < (s-1)*d
Build: 8598 jobs, 0 errors (lake build)
AGENTS.md: added SpherionTwinPrime architecture section, updated Burgers energy dissipation to parametric form.
spherion_twin_prime.py (20KB): priority-queue walk with polarity energy tuning.
Build: 8598 jobs, 0 errors.
- e8_singer_improvement: proven via Singer set as direct witness; (119/120)^k ≤ 1 by
pow_le_one₀, bound follows from mul_le_of_le_one_right.
- erdos30_e8_conditional: proven via interval_sidon_exists (Singer's theorem bridge);
C=1/4, Nat.sqrt ↔ Real.sqrt bridge via nlinarith on squared terms.
- sidon_weight_bound: restated — LHS corrected from σ₃(a+b) sums to σ₃(a)·σ₃(b)
products over unordered pairs (original was INVALID_STATEMENT; E₈ convolution
identity delivers products, not values at pair-sums). Remains ANALYTIC_OPEN.
- e8_levelset_density: restated — T fixed to N^4 (fixed T refuted by
e8_levelset_density_fails; σ₃(n) ≤ n·n³ = n^4 ≤ N^4 for n ≤ N). Fixed base
typo Nat.log N → Nat.log 2 N. Remains ANALYTIC_OPEN sorry.
- §14 summary updated with proven theorems and restatement notes.
- Add merkle_tensegrity_load_equation_generator.py to 4-Infrastructure/shim/
(required by cad_force_probe_experiment_matrix.py import).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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)
Squash the four overlapping feature branches into a single change set against
main, eliminating cross-PR merge conflicts and the duplicated CI-fix scripts.
What this brings in (merge order #79 -> #80 -> #81 -> #89):
- #79 refactor(infra): shared utilities (4-Infrastructure/lib/*: q16, hashing,
jsonl, fraction_utils) + the scripts/math-first/* validators that the
math-check CI requires.
- #80 feat(lean): Semantics.E8Sidon (1025 lines) -- Eisenstein coefficient
identity E4^2 = E8 and the Sidon framework. E4_sq_eq_E8_coeff is fully proved
(all Fourier-coefficient extraction machine-checked); the single residual gap
is pinned to E4_sq_eq_E8_qExpansion (Mathlib lacks the valence formula /
dim M8 = 1). 4 sorries + 1 axiom (e8_additive_completeness), all TODO(lean-port).
- #81 refactor(lean): Float-free FixedPoint core (integer-only sqrt/log2/expNeg).
E8Sidon.lean kept at #80's final 1025-line version (the #81 intermediate
438-line copy was overridden by merge order).
- #89 feat(lean): Semantics.RRC.PolyFactorIdentity -- short-sleeve polynomial
detection at the zerocopy limb boundary; now imports Semantics.E8Sidon for
sigma3/sigma7/convolutionLHS (single source of truth) instead of inlining them.
Conflict resolution:
- flake.nix -> canonical rs-surface removal (Garnix shutdown).
- scripts/math-first/* -> byte-identical across branches, clean.
- .cursorrules / AGENTS.md -> unified; baselines + sorry inventory refreshed.
Verification:
- lake build (default aggregator): 3573 jobs, 0 errors.
- lake build Semantics.RRC.PolyFactorIdentity (E8Sidon + FixedPoint + PolyFactor):
3655 jobs, 0 errors. Witnesses verified (sigma7 4 = 16513, convolutionLHS 6 = 2350).
- Python tests: 68/68 pass.
Note: the "Workers Builds: researchstack" check is a preexisting external
Cloudflare build unrelated to this change (no branch touches 4-Infrastructure/cloudflare/).
Build: 3573 jobs (default), 3655 jobs (narrow), 0 errors
Co-Authored-By: Allaun Silverfox <bigdataiscoming+9i37y6j2@protonmail.com>
New tier between CPU_FFMPEG and FRAMEBUFFER:
GPU_CUDA(7) > GPU_VAAPI(6) > GPU_APU(5) > CPU_FFMPEG(4) >
ETHERNET(3) > FRAMEBUFFER(2) > ESP32(1) > RELAY(0)
- _detect_virtio_net(): probes /sys/class/net for virtio driver (0x1af4)
- PistPacket computation via TX/RX descriptor rings
- Host vhost-user backend does matrix transforms
- CRC32 hardware offload = witness verification
- Works in any VM with network (even without framebuffer)
ray_vcn_bridge.py: Ray transport for the VCN-LUPINE bridge.
Replaces GPUNodeConnection TCP/MKV transport with Ray ObjectRef.
FrameDispatcher, BraidBackend, CUDABackend are unchanged — only
the wire between daemon and GPU node changes.
- RayBraidBackend: compute actor matching VCNBraidBackend pattern
- RayCUDABackend: GPU actor with /dev/dri (Mesa, no NVIDIA plugin)
- RayVCNBridge: full bridge as Ray actor (replaces daemon)
- RayGPUNodeConnection: drop-in for GPUNodeConnection
- SyncBraidWrapper/SyncCUDAWrapper: bridge Ray actors to sync interface
STRAND 42B → 63B, CROSSING 42B → 22B, PIST 24B → 57B
Batch 10: 5ms (0.5ms/frame), 10/10 non-empty
- Add detection for integrated AMD graphics (APUs/iGPUs) based on hardware model name
- Configure UMA-friendly full-range yuvj420p format to reduce system memory bandwidth footprint by 50%
- Force lossless constant QP (-qp 0) and full PC range to prevent clamping loss
- Re-run syntax checks and Lean compiler verification tests
Build: 3313 jobs, 0 errors (lake build)
- ray_vcn_transport.py: @ray.remote wrappers for braid VCN encode/decode
- Distributed encode on CPU workers, compute on GPU workers
- RayVCNTransport actor with frame counter + ObjectRef storage
- FAMM-gated encode task, batch encode/decode helpers
- 20 strands in 576ms (28.8ms/strand), 20/20 CRC ok
- raycluster.yaml: KubeRay cluster on qfox-1
- Head + CPU worker + GPU worker (RTX 4070 SUPER via /dev/dri)
- No NVIDIA device plugin — Mesa direct device access
- Tolerations for desktop taint on qfox-1
- num-gpus instead of custom GPU resource
- fix-nftables-k3s.sh: nftables forward rules for flannel/cni0
- nftables default policy=drop blocks pod-to-pod networking
- systemd service nftables-k3s-fix for persistence
- KubeRay operator moved to nixos (control plane can reach API server)
- FFmpeg 8.0 + reedsolo installed in Ray head pod via conda
- Vectorized create_yuv420_frame when numpy is available to eliminate the 500k-iteration scalar Python loop.
- Pre-filled memoryview slice buffers in the fallback path.
- Updated 4-Infrastructure/AGENTS.md to document the optimization.
Build: 3313 jobs, 0 errors (lake build)
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.
