Compression of Entropy_ How Structure Emerges in Far-From-Equilibrium Systems — and Why Deterministic Computing Depends on It

CODES Framework Abstract This paper formalizes how order emerges from entropy through deterministic phase alignment. It defines entropy compression as a lawful process of structural resonance, using the Phase Alignment Score (PAS_s, PAS_h) to quantify coherence in far-from-equilibrium systems. Gauss’s prime density, reaction–diffusion spirals, and bioelectric morphogenesis illustrate natural entropy-compression mechanisms, while deterministic computing (Resonance Intelligence Core) extends the same invariant logic into inference and verification. Entropy is reframed as a coordinate field revealing where lawful structure must form.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-21
DOI
https://doi.org/10.5281/zenodo.17410300
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

Compression of Entropy_ How Structure Emerges in Far-From-Equilibrium Systems — and Why Deterministic Computing Depends on It

Zenodo (CERN European Organization for Nuclear Research)
Neural Networks and Reservoir Computing
article

Compression of Entropy_ How Structure Emerges in Far-From-Equilibrium Systems — and Why Deterministic Computing Depends on It

article en

Abstract

CODES Framework Abstract This paper formalizes how order emerges from entropy through deterministic phase alignment. It defines entropy compression as a lawful process of structural resonance, using the Phase Alignment Score (PAS_s, PAS_h) to quantify coherence in far-from-equilibrium systems. Gauss’s prime density, reaction–diffusion spirals, and bioelectric morphogenesis illustrate natural entropy-compression mechanisms, while deterministic computing (Resonance Intelligence Core) extends the same invariant logic into inference and verification. Entropy is reframed as a coordinate field revealing where lawful structure must form.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 23%
Neural Networks and Reservoir Computing
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Compression of Entropy_ How Structure Emerges in Far-From-Equilibrium Systems — and Why Deterministic Computing Depends on It · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS