The Miulus Law: Toward a Unified Framework for Epistemic Stability Across Systems

This paper presents The Miulus Law: Toward a Unified Framework for Epistemic Stability Across Systems, an expanded formulation of the Miulus Law.The study introduces a single invariant equation: E = (S/N) * R where S is verified signal, N is informational noise, and R is recognition—the capacity of a system to integrate verified information coherently.A system remains stable while E ≥ Ec (approximately 0.35–0.40); below this threshold, collapse of structure, meaning, or function occurs. The unified framework generalizes the law beyond information environments to encompass quantum mechanics, cognition, social systems, thermodynamics, and gravity.It interprets spacetime curvature as an epistemic gradient that aggregates dispersed information into correlated structure, with black holes representing local epistemic minima and Hawking radiation acting as a restoring process. The paper also introduces the Epistemic Suite—Recorder, Verifier, Vault, and Librarian—as a practical implementation of the law.Together they maintain verified signal, reduce noise, and coordinate recognition across distributed networks, creating the first engineered architecture designed to sustain epistemic fitness above the collapse threshold. This work consolidates and extends the earlier studies Epistemic Collapse in the Age of AI-Generated Hyperreality, High-Fidelity Noise and the Collapse of Cognitive–Social Cohesion, and Counter-Leaking in AI-Driven Information Warfare and The Miulus Law: Epistemic Fitness as a Universal Constraint on Self-Referential Systems, uniting them under a single theoretical framework that links information theory, physics, and cognition through one law of epistemic equilibrium.