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0b200145c2
Applied 4-primitive framework to 19 chemistry-physics equations from chemistry_physics_nspace_spine_v0.json. Mapping results: - Field primitive (ρ(x⃗)): 6 equations (31.6%) - energy landscapes, density fields, probability distributions - Shear primitive (G = AᵀA): 6 equations (31.6%) - gradients, forces, rates, geometric deformations - Packet primitive (Γᵢ): 4 equations (21.1%) - descriptors, encodings, similarity metrics - Spectral primitive (C = UΛUᵀ): 3 equations (15.8%) - eigenproblems, basis optimization, variational methods Key insights: - Cross-domain consistency: Each primitive appears across chemistry, physics, thermodynamics, quantum chemistry - Canonical mapping confirmed across scientific domains - No gaps: Each primitive well-represented - Field: energy landscapes, density fields, probability distributions - Shear: gradients, forces, rates, geometric deformations - Packet: descriptors, encodings, similarity metrics, representations - Spectral: eigenproblems, basis optimization, variational methods Mapping saved to: 4-Infrastructure/shim/scientific_equations_4primitive_mapping.json |
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| exploit-infra/CATEGORY/TSM | ||
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| hardware | ||
| infra | ||
| nano-kernel | ||
| NoDupeLabs | ||
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| 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