Эксперимент: Barrier-Controlled Basin Switching (#517)

{ "worked": true, "confidence": 9, "verdict": "Built a readable quartic double-well Langevin MVP with analytical barrier feedback ε=ΔV/q, transition-rate sweeps, and a fixed-noise baseline comparison. The mechanism manifested strongly: the measured log-rate versus inverse-noise slope was −0.2493 versus predicted −0.25, feedback log-rate versus q was −1.0487 versus −1, and the q=2 to q=3.5 rate ratio was 0.215 versus predicted 0.223. The controller did not improve this single-seed toy escape time (3249 versus 2821 steps), so there is no demonstrated optimizer speed or accuracy win despite successful mechanism verification.", "metrics": { "baseline": "Fixed-noise Langevin: target reached in 2821 steps; ε=0.08333", "idea": "Barrier-controlled Langevin: target reached in 3249 steps; ε=0.125 in escape mode and ε=0.03125 in safe mode", "prediction_1": "Observed slope −0.24935 vs predicted −0.25, relative error 0.26%", "prediction_2": "Observed feedback slope −1.04866 vs predicted −1, absolute error 4.87%", "prediction_3": "Observed rate ratio 0.21514 vs predicted exp(−1.5)=0.22313" }, "how_to_run": "/home/maxwelhelp/main/bin/python3 experiment.py > results.json", "files": [ "experiment.py", "results.json", "article.md" ], "limitations": "Only the analytically known one-dimensional quartic potential was tested; no learned quasipotential, neural-network training, CIFAR/MNIST experiment, Adam/SGD comparison, multi-seed confidence intervals, or wall-clock/FLOP analysis was performed." }