# Эксперимент: Bifurcation-calibrated delayed-gradient escape (#1074)

{
  "worked": true,
  "confidence": 9,
  "verdict": "Built a reproducible delayed-gradient toy verification in delayed_gradient_experiment.py. The measured stability transition occurred between 0.9 and 1.05 tau_c, matching the predicted pi/(2k) boundary; unstable growth rates matched Re(lambda+) with mean absolute error 0.00088, and direct escape-time scaling matched the predicted slope 1/r within 0.13%. The mechanism is numerically real, but the small double-well comparison did not show a useful escape win: both methods had 0/12 basin escapes, while fixed delay had higher final loss (0.0322 versus 0.0000871).",
  "metrics": {
    "baseline": "Current-gradient noisy SGD: escape_fraction=0.0, median_escape_step=None, mean final loss=8.71e-05",
    "idea": "Delayed-gradient proxy with 44-step calibrated delay: escape_fraction=0.0, median_escape_step=None, mean final loss=0.0322; linear-system growth-rate MAE=8.82e-04 and escape-scaling slope relative error=0.13%"
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 delayed_gradient_experiment.py",
  "files": [
    "delayed_gradient_experiment.py",
    "results.json"
  ],
  "limitations": "Only low-dimensional linear and double-well tests were run; no MNIST MLP, Hessian-vector estimator, adaptive plateau-triggered burst, full stochastic delayed-SDE escape measurement, FLOP accounting, or GPU experiment was tested. The double-well setup and noise were not tuned to produce frequent escapes."
}