Эксперимент: Cross-Degree Certificate Against Recurrent Oscillation (#608)

{ "worked": true, "confidence": 9, "verdict": "Built a deterministic weighted threshold-dynamics verifier for the cross-degree certificate, including exact partition search and a baseline-versus-safe-threshold comparison. All three mechanism predictions were confirmed: the nontrivial period-two boundary matched 1 <= R <= c* exactly, weight scaling produced the predicted linear boundary, and setting R=1.1c* suppressed the certified orbit in every sweep. This demonstrates the mechanism, but not improved trained-GNN accuracy.", "metrics": { "baseline": "R=1.0; period-two rate from 300 random initial states = 0.0833", "idea": "R=1.1c*=2.2; period-two rate from 300 random initial states = 0.0000; exact c*=2.0", "prediction_checks": "Boundary confirmed; scaling boundary errors were 0 at scales 0.5, 1.0, 1.5, and 2.0; 10% threshold suppression confirmed at all scales" }, "how_to_run": "/home/maxwelhelp/main/bin/python3 certificate_experiment.py", "files": [ "certificate_experiment.py", "results.json" ], "limitations": "Only a small 8-node bipartite weighted threshold system was tested. The experiment used exact partition enumeration rather than the proposed spectral/local-swap approximation, and did not train or evaluate a recurrent GNN, node-labeling task, learned penalty, signed weights, non-bipartite graphs, or accuracy/runtime tradeoffs." }