Hans Architecture: Spiral Phase-Transition Dynamics for Next-Generation AI Systems

v1.2 update: Added direct Transformer comparison — 54% lower MSE on time-series, 360% higher reward on CartPole.Core innovations:Contemporary AI systems (Transformer, Mamba, MoE) share three structural limitations: static computation depth, frozen inference parameters, and unstructured exploration. Hans Architecture addresses each through: (1) H_spiral — a spiral constraint vector field that transforms post-failure accumulation from random walk into directed spiral convergence along a fixed manifold; (2) MDL-Compress — an online knowledge distillation mechanism enabling genuine self-evolution during inference; (3) a sound-field multi-agent coordination framework where cross-agent rule transfer achieves 5.7× the performance gain of within-agent optimization.Experimental validation:All claims are validated through seven layers of cross-verified experiments with fixed random seeds. The primary reproducibility target (Experiment 05) achieves t-statistic = 13.58 and cross-seed standard deviation = 0.15% across 5 independent random seeds, confirming stable and significant results.Code availability:The complete experimental codebase is available at the linked GitHub repository. The primary reproducibility entry point is experiments/exp05_transfer_stability.py.