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From the 1 of 8 linked papers with an AI index.

collaborators

8 papers

physics.bio-ph2026

A behavior-environment information loop drives sensory navigation

Kevin S. Chen, Matthew P. Leighton, Damon A. Clark +1

The paper presents an information‑theoretic framework using transfer entropy to quantify how sensory inputs and behavioral actions influence each other during navigation, and shows…

cond-mat.stat-mech2026

On the Information Required for Feedback Control

Matthew P. Leighton, Jose M. Betancourt, Thierry Emonet +2

Biological systems across scales, along with many engineering problems, must control noisy systems with limited information. Here we study information-limited feedback control of s…

cond-mat.stat-mech2026

Hunting for Maxwell's Demon in the Wild

Johan du Buisson, Jannik Ehrich, Matthew P. Leighton +4

The paradox of Maxwell's demon motivated the development of information thermodynamics and the creation of nanoscale information engines. We now understand that machines such as th…

cond-mat.stat-mech2026

Will a Large Complex System be a Maxwell Demon?

Matthew P Leighton

Emerging evidence suggests that physical systems operating as Maxwell demons, in which some subsystem of a larger system extracts heat energy from its environment in an apparent lo…

cond-mat.stat-mech2026

Information thermodynamics of cellular ion pumps

Julian D. Jiménez-Paz, Matthew P. Leighton, David A. Sivak

The framework of bipartite stochastic thermodynamics is a powerful tool to analyze a composite system's internal thermodynamics. It has been used to study the components of differe…

cond-mat.stat-mech2025

Tractable Model for Tunable Non-Markovian Dynamics

Matthew P. Leighton, Christopher W. Lynn

Non-Markovian dynamics are ubiquitous across physics, biology, and engineering. Yet our understanding of non-Markovian processes significantly lags that of simpler Markovian proces…