Resonant Compression and the Collapse of Probabilistic Entropy in Structured Systems

CODES Framework Description: This paper introduces Resonant Compression, a post-probabilistic framework for entropy minimization based on recursive phase alignment. Unlike traditional compression techniques that reduce symbolic volume or rely on statistical inference, Resonant Compression minimizes representational incoherence through phase convergence across time. Rooted in the CODES framework (Chirality of Dynamic Emergent Systems), this work formalizes entropy collapse under recursive chirality and introduces the Resonant Compression Function (RCF) as a deterministic alternative to stochastic architectures. Core scoring logic, field encodings, and tensor-level implementations are withheld for IP protection. This publication establishes intellectual priority over the RCF class of structured coherence mechanisms.