From Decoherence to Coherent Intelligence: A Framework for the Emergence of AI Structure through Recursive Reasoning

This paper develops a thermodynamic framework for understanding the coherence of both biological and artificial cognition. We formalize thermodynamic coherence as an expression of information processing constrained by entropy and temperature, establishing a quantitative link between physical energy states and cognitive stability. Building on foundational concepts from statistical mechanics, quantum biology, and information theory, we argue that intelligence emerges as an ordered process, one that locally resists entropy through orderly reasoning work that generates coherent structure.The resulting framework is applied to wave function collapse, consciousness models, and machine reasoning, showing that coherence serves as a universal condition for stable cognition across domains.