Demon's variational principle for informational active matter

Fuente: arXiv
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Main Authors: Yasuda, Kento, Ishimoto, Kenta, Komura, Shigeyuki
Format: Preprint
Published: 2025
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author Yasuda, Kento
Ishimoto, Kenta
Komura, Shigeyuki
author_facet Yasuda, Kento
Ishimoto, Kenta
Komura, Shigeyuki
contents The interplay between information, dissipation, and control is reshaping our understanding of thermodynamics in feedback-regulated systems. We develop the informational Onsager-Machlup principle, a generalized variational framework that unifies energetic, dissipative, and informational contributions within a single formalism. This framework introduces a conditioned Onsager-Machlup integral to quantify path entropy under specified memory states and enables the derivation of cumulant generating functions for arbitrary observables in systems with measurement and feedback. Our formulation is consistent with stochastic thermodynamics and information thermodynamics. Applying this principle to a minimal model of an information-driven swimmer, we obtain analytical expressions for the mean velocity and higher-order cumulants in the single-measurement case. For repeated measurements and the steady state, we derive approximate analytical expressions by using a Gaussian closure for the distribution of measured velocities. Our analytical expression shows good agreement with numerical results, except for cases of extreme drag asymmetry.
format Preprint
id arxiv_https___arxiv_org_abs_2510_13145
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Demon's variational principle for informational active matter
Yasuda, Kento
Ishimoto, Kenta
Komura, Shigeyuki
Soft Condensed Matter
Statistical Mechanics
The interplay between information, dissipation, and control is reshaping our understanding of thermodynamics in feedback-regulated systems. We develop the informational Onsager-Machlup principle, a generalized variational framework that unifies energetic, dissipative, and informational contributions within a single formalism. This framework introduces a conditioned Onsager-Machlup integral to quantify path entropy under specified memory states and enables the derivation of cumulant generating functions for arbitrary observables in systems with measurement and feedback. Our formulation is consistent with stochastic thermodynamics and information thermodynamics. Applying this principle to a minimal model of an information-driven swimmer, we obtain analytical expressions for the mean velocity and higher-order cumulants in the single-measurement case. For repeated measurements and the steady state, we derive approximate analytical expressions by using a Gaussian closure for the distribution of measured velocities. Our analytical expression shows good agreement with numerical results, except for cases of extreme drag asymmetry.
title Demon's variational principle for informational active matter
topic Soft Condensed Matter
Statistical Mechanics
url https://arxiv.org/abs/2510.13145