# Эксперимент: Phase-Blind Checkpoint Scheduling (#597)

{
  "worked": true,
  "confidence": 8,
  "verdict": "Built a compact phase-blind checkpoint scheduling toy verifier with anonymous and priority pair maps, fleet eigenvalue sweeps, and noisy phase-margin lifetime simulation. The three mechanism predictions were confirmed: pair return-map slope 1.0 across T,d settings, unit fleet determinant and reciprocal eigenvalues for N=2..10 and three throughput laws, and noise lifetime exponent -1.962 versus predicted -2. Doubling noise gave a measured lifetime ratio 3.83 versus the predicted 4, so the mathematical mechanism manifested; this is not evidence of production-training throughput gains.",
  "metrics": {
    "baseline": "Toy priority comparator: pair-gap slope 0.75 and gap 0.000951 after 20 cycles from initial 0.3.",
    "idea": "Anonymous map: slope 1.000 across all three T,d cases and zero identity error; fleet max determinant error 6.66e-16 and reciprocal-eigenvalue error 2.22e-16; jitter log-log exponent -1.962, sigma-doubling lifetime ratio 3.835."
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 phase_blind.py",
  "files": [
    "phase_blind.py",
    "results.json",
    "run_output.txt"
  ],
  "limitations": "No real PyTorch distributed workers, checkpoint storage gateway, network contention, filesystem I/O, wall-clock throughput, or CIFAR-10 training was tested. The anonymous return map and priority comparator are idealized toy maps; the results verify the supplied formulas and noise scaling rather than demonstrating end-to-end operational benefit."
}