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b349853793
Evolve erans from flat histogram coding to spectral decomposition of residual field (field effect spectrum). Changes to master synthesis: - Added erans_field_effect_spectrum to theoretical_foundations - Updated stage_13: compute residual correlation matrix C, eigen-decompose C = UΛU^T, code spectral coefficients with erans - Updated source to include erans-field-effect-spectrum - Added 3 new compression gain sources: * erans_spectral_compaction (10-20% gain from energy compaction) * spectral_pattern_separation (2-3% gain from spectral overlap) * famm_spectral_pruning (3-5% gain from residual spectral energy) - Updated estimated aggregate gain: 20-35% reduction (was 18-28%) - Added 6 spectral keeper phrases - Updated core_synthesis to mention spectral decomposition - Added 5 new tags: erans-field-effect, spectral-encoding, residual-field-spectrum, field-effect Field effect spectrum: residual correlation matrix C captures how residuals propagate through manifold. Spectral energy compaction (90% energy in 10% coefficients) provides 10-20% gain over flat histogram coding. Spectral overlap measure improves OAC gate precision. FAMM delays use residual spectral energy for context efficiency. |
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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