Upper bound for entropy production in Markov processes

TL;DR

This paper establishes upper bounds on entropy production in Markov processes using dynamical activity and transition-rate ratios, complementing existing lower bounds and applicable to both steady-state and time-dependent scenarios.

Contribution

It introduces novel upper bounds for entropy production in Markov processes, expanding the theoretical framework of stochastic thermodynamics.

Findings

Derived two upper bounds for entropy production.

Validated bounds through numerical simulations.

Potential applications in thermodynamic analysis.

Abstract

The second law of thermodynamics states that entropy production cannot be negative. Recent developments concerning uncertainty relations in stochastic thermodynamics, such as thermodynamic uncertainty relations and speed limits, have yielded refined second laws that provide lower bounds of entropy production by incorporating information from current statistics or distributions. In contrast, in this study, we bound the entropy production from above by terms comprising the dynamical activity and maximum transition-rate ratio. We derive two upper bounds: one applies to steady-state conditions, whereas the other applies to arbitrary time-dependent conditions. We verify these bounds through numerical simulation and identify several potential applications.