mirror of
https://github.com/allaunthefox/Research-Stack.git
synced 2026-07-31 03:05:21 +00:00
Applied 4-primitive framework to Erdős–Straus Conjecture. Conjecture: For every integer n ≥ 2, 4/n = 1/x + 1/y + 1/z has a solution. Test parameters: - n values: 2 to 50 - 49 values tested - Max search per n: 10000 Results: - Solutions found: 49/49 (100% success rate) - No counterexamples found for n ≤ 50 4-primitive analysis: - Packet primitive (Γᵢ): Egyptian fraction solution as packet (x,y,z) - Field primitive (ρ(x⃗)): field density 1/n, reciprocal field - Spectral primitive (C = UΛUᵀ): solution space eigen decomposition - Shear primitive (G = AᵀA): solution rigidity and spread Findings: - Packet primitive captures solution encoding structure - Field primitive captures conjecture condition (reciprocal field) - Spectral primitive reveals solution space structure - Shear primitive measures solution space deformation Framework validated for Diophantine equation problems. Ready for Erdős Conjecture on Arithmetic Progressions. Results saved to: 4-Infrastructure/shim/test_erdos_straus_4primitive_results.json |
||
|---|---|---|
| .. | ||
| 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