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May 4, 20260 citationsOpen Access

A Variational Feedback–Entropy Framework for Multi-Scale Structure Formation: From Gravitational Systems to Neural Inference Dynamics

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AMAngelito Enriquez Malicse

Key Points

  • This research aims to formulate a variational framework to understand structure formation and dynamics across various systems.
  • Developed a variational formulation of evolution modeled as gradient flow.
  • Applied a thermodynamic entropy-production constraint to the free-energy functional.
  • Derived stability conditions and phase transitions from the geometry of the free-energy landscape.
  • Demonstrated formal equivalence to Friston's free-energy principle and Jeans gravitational instability.
  • Identified stability conditions and derived testable predictions from the proposed framework.

Abstract

Abstract We present a variational formulation of structure formation and adaptive dynamics in physical, biological, and cognitive systems. System evolution is modeled as gradient flow on a free-energy functional subject to a thermodynamic entropy-production constraint. We demonstrate formal equivalence between this variational principle, nonlinear feedback dynamical systems, and established frameworks including Friston's free-energy principle and Jeans gravitational instability. The framework functions as a unifying meta-theoretical description and does not replace the underlying domain-specific theories. Stability conditions, phase transitions, and testable predictions are derived from the geometry of the free-energy landscape.

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Cite This Study

Angelito Enriquez Malicse (2026) studied this question.

synapsesocial.com/papers/69f837ab3ed186a739981cf0https://doi.org/10.17605/osf.io/49hm3
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