Эксперимент: Phase-Aware Bias-Energy Trust Region (#979)

{ "worked": true, "confidence": 9, "verdict": "Built the phase-aware clipping controller and verified the paper's mechanism numerically. Across p=1.25, 1.5, and 2.0, the observed phase boundary matched alpha=p beta; in a focused p=1.5 sweep, the maximizer stayed at r=1 through alpha=1.5 and moved to the predicted r_star above it, with maximum radius error below 1.6e-4. The pure-residual extremum and tau scaling also matched c_p to numerical precision. In the toy optimizer, the controller reduced mean residual and median update magnitude, but had higher update variance and slightly worse final loss than fixed clipping, so this is mechanism confirmation rather than an overall optimization win.", "metrics": { "baseline": "Fixed clipping: final_loss=3.42e-05, median_update=0.00340, update_std=0.0178, clip_fraction=0.261, mean_residual=1.364", "idea": "Phase-aware: final_loss=4.37e-05, median_update=0.00302, update_std=0.0364, clip_fraction=0.0588, mean_residual=0.658, final_tau=1.411; phase and radius predictions matched with maximum radius error 1.6e-4" }, "how_to_run": "/home/maxwelhelp/main/bin/python3 phase_aware.py", "files": [ "phase_aware.py", "results.json", "run_output.txt" ], "limitations": "Only a small synthetic quadratic experiment was run; no Transformer, WikiText-103, GPU benchmark, multiple-seed statistical study, or rigorous recovery-time comparison was tested. Controller targets and rates remain empirical." }