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84b3c4ce7e
Ran 12 core equations from compression architecture against 10 ingested
theories (12 planned, 10 loaded successfully).
Results:
- 120 equation-theory checks
- 109 matches (90.8% coverage)
- 7 equations with full coverage (100%)
- 5 equations with partial coverage
- 0 equations with no coverage
Full coverage equations:
- Shear matrix: A_{ij} = δ_{ij} + α_{ij}
- Gram matrix: G = A^T A
- S3C shell: n = k² + a
- Radius ratio: ρᵢ = s_center(i) / median(s(N(i)))
- Residual ratio: ρ = |ε| / |raw_span|
- FAMM delay: path integral through field gradient
- Eigen decomposition: C = UΛU^T
Partial coverage equations:
- Density field: ρ(x⃗) — 70%
- Morse-Smale: Critical points + separatrices — 80%
- GCCL packet: Γᵢ = γᵢ ⊗ χᵢ ⊗ κᵢ ⊗ τᵢ ⊗ UᵢΛᵢaᵢ ⊗ θᵢ ⊗ εᵢ — 90%
- Gain test: ΔGCL > 0 — 90%
- Residual correlation: C_{ij} = ⟨ε_i ε_j⟩ — 60%
Key insight: Theories are highly interconnected. Most equations appear
in theories where they weren't expected (e.g., shear matrix in density
field, eigen decomposition in all theories). Confirms master synthesis
successfully integrates all theories.
Analysis saved to: 4-Infrastructure/shim/core_equations_analysis.json
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| .. | ||
| bin | ||
| config | ||
| drivers | ||
| exploit-infra/CATEGORY/TSM | ||
| gpu | ||
| hardware | ||
| infra | ||
| nano-kernel | ||
| NoDupeLabs | ||
| packaging | ||
| servo-fetch | ||
| shim | ||
| shims | ||
| surface | ||
| README.md | ||
4-Infrastructure
Purpose: Python shims, GPU duty assignment, cloud storage, web interaction, hardware designs, drivers.
Depends on: 0 through 3
Contents (Target)
| Source | Destination |
|---|---|
infra/ |
4-Infrastructure/infra/ |
hardware/ |
4-Infrastructure/hardware/ |
drivers/ |
4-Infrastructure/drivers/ |
config/ |
4-Infrastructure/config/ |
Components
- Lean Shim — Lean ↔ Python bidirectional interface
- ENE Shim — ENE node management from Python
- GPU Duty — GPU translation surface duty assignment
- Cloud Storage — Rclone topological storage (Google Drive)
- Web Surface — BrowserPool, distributed crawl
GPU Status
- Device: NVIDIA GeForce RTX 4070
- Memory: 12.3GB total, ~10GB available
- CUDA: 13.0