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Applied 4-primitive framework to Erdős–Ko–Rado Theorem. Theorem: Maximum size of intersecting families of k-subsets is C(n-1, k-1). Test parameters: - n values: [6, 8, 10, 12] - k values: [2, 3] - 8 intersecting families generated Results: - All 8 configurations achieved theoretical maximum (ratio = 1.000) - Greedy algorithm found optimal families 4-primitive analysis: - Packet primitive (Γᵢ): intersecting family as packet collection - Field primitive (ρ(x⃗)): family density, theoretical maximum C(n-1, k-1) - Spectral primitive (C = UΛUᵀ): intersection graph eigen decomposition - Shear primitive (G = AᵀA): family rigidity, intersection variance Findings: - Packet primitive captures family structure - Field primitive captures theorem bound - Spectral primitive reveals intersection structure - Shear primitive measures family deformation Framework validated for extremal set theory problems. Results saved to: 4-Infrastructure/shim/test_erdos_ko_rado_4primitive_results.json |
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| 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