Abstract

Emergent Necessity Theory (ENT) presents a falsifiable, cross-domain framework for identifying when systems, physical, neural, or artificial, cross a critical coherence threshold, beyond which structured behavior becomes inevitable. Rather than beginning with assumptions about consciousness, agency, or complexity, ENT defines structural conditions where recursive stabilization forces coherence to persist. Structure emerges as a necessity when contradiction entropy falls below the threshold and recursive feedback maintains persistence. This paper unifies theoretical foundations, mathematical formalism, and domain-specific simulations into a single, cohesive exposition of ENT. Simulations of dynamics in neural, artificial intelligence, and quantum systems are presented, analyzing structural emergence, collapse behavior, symbolic drift, and perturbation stability. The coherence function and resilience ratio (t) are introduced as measurable metrics for detecting phase-like transitions in symbolic consistency. Domain-specific values across neural ( ≈0.5), AI (≈0.6), quantum (≈1.5 ), and cosmological (≈1.8 ) systems are justified, demonstrating that these thresholds are not arbitrary but derive from normalized coherence dynamics, physical constraints, and falsifiable predictions. Ethical Structurism is proposed as a falsifiable framework for AI accountability, where symbolic stability, not moral interpretation, defines safety. All claims are open-source, simulation-supported, and designed to be easy to falsify. If empirical tests fail to detect threshold behavior, the framework should be revised or discarded. ENT does not define consciousness; it defines the structural necessity that may precede it. In this view, what might resemble stability behaviors (structurally defined) are not assumed; they are earned through coherence. Operational decisions use the normalized signal; raw τ and domain serve only as calibration anchors.