Stochastic thermodynamics and fluctuation theorems for non-linear systems

TL;DR

This paper generalizes stochastic thermodynamics to non-linear, non-Markovian systems by reformulating the second law with generalized entropy and deriving extended fluctuation theorems applicable beyond linear, Boltzmann-distributed systems.

Contribution

It introduces a generalized entropy framework and extends key fluctuation theorems to non-linear, non-Markovian stochastic systems, relaxing previous assumptions.

Findings

Derived a relation between non-linear master equations and generalized entropy.

Extended Crooks fluctuation theorem for non-linear systems.

Extended Jarzynski equality beyond linear, Boltzmann systems.

Abstract

We extend stochastic thermodynamics by relaxing the two assumptions that the Markovian dynamics must be linear and that the equilibrium distribution must be a Boltzmann distribution. We show that if we require the second law to hold when those assumptions are relaxed, then it cannot be formulated in terms of Shannon entropy. However, thermodynamic consistency is salvaged if we reformulate the second law in terms of generalized entropy; our first result is an equation relating the precise form of the non-linear master equation to the precise associated generalized entropy which results in thermodynamic consistency. We then build on this result to extend the usual trajectory-level definitions of thermodynamic quantities that are appropriate even when the two assumptions are relaxed. We end by using these trajectory-level definitions to derive extended versions of the Crooks fluctuation theorem and Jarzynski equality which apply when the two assumptions are relaxed.