Non-invasive estimation of dissipation from non-equilibrium fluctuations in chemical reactions

TL;DR

This paper introduces a non-invasive method to estimate entropy production in chemical reactions from stationary fluctuation data, applicable even with partial information, based on fluctuation theorems.

Contribution

It presents a novel, direct approach to quantify dissipation in chemical reactions using fluctuation theorems without requiring detailed system knowledge.

Findings

Method accurately estimates entropy production from time series data.

Coarse-graining affects the dissipation estimate.

Applicable to simple stochastic models of chemical reactions.

Abstract

We show how to extract from a sufficiently long time series of stationary fluctuations of chemical reactions an estimate of the entropy production. This method, which is based on recent work on fluctuation theorems, is direct, non-invasive, does not require any knowledge about the underlying dynamics, and is applicable even when only partial information is available. We apply it to simple stochastic models of chemical reactions involving a finite number of states, and for this case, we study how the estimate of dissipation is affected by the degree of coarse-graining present in the input data.