Entropy as Coherence Distribution

Entropy is reframed as a measure of coherence distribution across a system’s generative possibility space rather than as disorder, randomness, or missing information. The paper models entropy as a downstream summary statistic of how coherence is allocated, redistributed, and degraded under quantized constraints. On this account, entropy increases when coherence becomes more diffusely distributed across available configurations, and decreases when coherence concentrates into stable attractor structures. The framework is developed across three layers: the formation of discrete attractor geometries that define a system’s possibility space, the persistence operators that stabilize coherent configurations, and the metabolic redistribution dynamics that govern transitions between them. This structure explains thermodynamic behavior, information‑theoretic entropy, and cosmological entropy as domain‑specific expressions of the same underlying coherence geometry. The result is a unified account of entropy that clarifies its cross‑domain invariance and situates thermodynamic and informational regularities within a broader generative architecture.