Эксперимент: Hidden-Diffusion Irreversibility Monitor (#1164)

{ "worked": true, "confidence": 9, "verdict": "Built a reproducible two-dimensional OU hidden-diffusion monitor. The exact analytic spectrum was invariant to D_xy up to 6.7e-16 when A_yy=0, while the forward/reverse path-action gap changed from 3.54 to 16.34, closely tracking the paper's sigma formula range of 3.57 to 17.29. This clearly demonstrates the claimed observed-spectrum blind spot and latent irreversibility sensitivity, but it is a synthetic validation rather than an end-to-end RNN result.", "metrics": { "baseline": "Observed-only spectrum pairwise relative variation: 6.66e-16; observed autocorrelation pairwise maximum variation: 0.0177.", "idea": "Monitor gaps for D_xy={-0.75,0,0.75}: {3.538,3.988,16.337}; spread 12.798 versus formula sigma spread 13.714. Maximum sample autocorrelation error versus exact OU prediction: 0.0165." }, "how_to_run": "/home/maxwelhelp/main/bin/python3 run_experiment.py", "files": [ "hidden_diffusion_monitor.py", "run_experiment.py", "results.json" ], "limitations": "Only the synthetic stable two-state OU setting was tested; no stochastic RNN, delayed-Copy task, learned drift/diffusion estimation, classifier-based reverse likelihood, uncertainty penalty, or GPU benchmark was implemented. The monitor uses known transition parameters for the path-action calculation, so estimation error in a learned latent model remains untested." }