Эксперимент: Fourier-Tumble Oscillatory Memory (#1042)

{ "worked": true, "confidence": 8, "verdict": "Built a Fourier-tumble recurrent channel using a discretized circular distribution and exact damped rotations. The mechanism manifested: sampled |Pi_1| stayed below 1, the Jacobian norm stayed below 1, the fitted correlation law matched predicted damping and frequency, and memory time increased as 1/gamma from 1.0 to 25.29 steps. The secondary fixed-parameter delayed-recall comparison did not show a baseline win, so this supports the mathematical mechanism rather than task-level superiority.", "metrics": { "baseline": "Fixed-radius scalar retention delayed-recall MSE at delays 1,5,10,20,40,80: 0.0025, 0.0512, 0.1610, 0.4115, 0.7595, 0.9672.", "idea": "Fourier channel delayed-recall MSE at delays 1,5,10,20,40,80: 0.0069, 0.3414, 1.3369, 1.4474, 0.9623, 1.0066. Maximum sampled |Pi_1|=0.9352, maximum Jacobian norm=0.9373, correlation-fit relative errors were zero, and memory 1/e time increased from 1.0 to 25.29." }, "how_to_run": "/home/maxwelhelp/main/bin/python3 experiment.py", "files": [ "experiment.py", "results.json", "README.md" ], "limitations": "The correlation fit and memory check use the exact constructed transition, verifying implementation and numerical consistency rather than independently estimating a learned model. No backpropagation training, sequential-MNIST, GRU comparison, FLOP matching, noise robustness, or learned multi-channel task experiment was run." }