Эксперимент: Nonreciprocal Brownian Optimizer (#588)

{ "worked": true, "confidence": 9, "verdict": "Built the two-replica nonreciprocal optimizer math prototype and a small MLP experiment. The mechanism manifested: continuous stability transitioned at the predicted k0+k1+k2=0 boundary (observed between -1.0 and -0.9), the discrete Euler boundary was predicted at eta=1.0 and observed at 1.00002, and entropy production was zero at reciprocity while scaling as 0.35714·delta² with negligible fit-ratio variation. The MLP comparison did not show a practical win: baseline final loss was 0.67615 versus 0.68896 reciprocal and 0.68581 nonreciprocal.", "metrics": { "baseline": "MLP final loss 0.676155; deterministic single-replica SGD", "idea": "Nonreciprocal two-replica final loss 0.685811 (k1=0.95,k2=0.25); EP at delta=0 was 8.15e-32 and quadratic coefficient was 0.357143" }, "how_to_run": "/home/maxwelhelp/main/bin/python3 experiment.py", "files": [ "experiment.py", "results.json", "run_output.txt" ], "limitations": "Only a tiny synthetic full-batch MLP was tested, not MNIST/CIFAR or minibatch-gradient temperature estimation. The optimizer used fixed noise/couplings and did not test annealing, saddle escape time, broad hyperparameter sweeps, matched FLOPs in a realistic training regime, or statistical repeats." }