Irreversibility and biased ensembles in active matter: Insights from stochastic thermodynamics

TL;DR

This paper reviews how stochastic thermodynamics tools can quantify irreversibility and energy dissipation in active matter, revealing new phase transitions and collective behaviors beyond equilibrium analogs.

Contribution

It introduces a systematic approach to measure irreversibility in active systems and explores biased ensembles to uncover novel phase transitions.

Findings

Irreversibility measures relate to energy dissipation in active matter.

Biased ensembles can reveal unexpected phase transitions.

Thermodynamic tools help distinguish active transitions from equilibrium ones.

Abstract

Active systems evade the rules of equilibrium thermodynamics by constantly dissipating energy at the level of their microscopic components. This energy flux stems from the conversion of a fuel, present in the environment, into sustained individual motion. It can lead to collective effects without any equilibrium equivalent, such as a phase separation for purely repulsive particles, or a collective motion (flocking) for aligning particles. Some of these effects can be rationalized by using equilibrium tools to recapitulate nonequilibrium transitions. An important challenge is then to delineate systematically to which extent the character of these active transitions is genuinely distinct from equilibrium analogs. We review recent works that use stochastic thermodynamics tools to identify, for active systems, a measure of irreversibility comprising a coarse-grained or informatic entropy production. We describe how this relates to the underlying energy dissipation or thermodynamic entropy production, and how it is influenced by collective behavior. Then, we review the possibility to construct thermodynamic ensembles out-of-equilibrium, where trajectories are biased towards atypical values of nonequilibrium observables. We show that this is a generic route to discovering unexpected phase transitions in active matter systems, which can also inform their design.