Bounding dissipation in stochastic models

TL;DR

This paper extends the exact calculation of average dissipation to stochastic systems, deriving bounds through coarse-graining and analyzing information capture in Brownian particle models.

Contribution

It generalizes dissipation expressions to stochastic dynamics and introduces bounds via coarse-graining, enhancing understanding of dissipation in complex systems.

Findings

Derived lower bounds for dissipation using coarse-graining

Analyzed information capture in over- and underdamped Brownian models

Extended previous deterministic dissipation formulas to stochastic processes

Abstract

We generalize to stochastic dynamics the exact expression for average dissipation along an arbitrary non-equilibrium process, given in Phys. Rev. Lett. 98, 080602 (2007). We then derive lower bounds by various coarse-graining procedures and illustrate how, when and where the information on the dissipation is captured in models of over- and underdamped Brownian particles.