Coherence Stability Principle: Active Governance in Chaotic Systems

This working paper introduces the Coherence Stability Principle, a classical dynamics-based framework for predicting when a system will remain orderly, enter oscillatory instability, or collapse into chaos. Instead of invoking quantum mechanics or speculative behavior, this work uses chaos theory and a Reynolds-like dimensionless parameter — Re_EOS — to model the balance between variance injection and coherence-binding capacity. A logistic-map simulation demonstrates that rising variance naturally drives a system from laminar order → oscillation → deterministic chaos. A governance intervention mechanism, Effective Coherence Restoration (ECR), is then tested. When an "Oscillation Warning" is detected, ECR throttles variance and successfully prevents chaotic collapse — restoring coherence in real-time. This publication includes: • the Coherence Stability Principle formulation• operational regimes and threshold logic• full Python simulation code• results comparing uncontrolled vs. ECR-governed systems• limitations and roadmap for future research This work forms an independent research artifact within the EOS family — a proof-of-concept demonstration that chaos is predictable and steerable using classical stability mechanics.