General theory for localizing the where and when of entropy production meets single-molecule experiments

TL;DR

This paper introduces a fluctuating entropy production framework for coarse-grained, driven nanoscale systems, enabling detailed analysis of individual trajectories and providing bounds on entropy production distributions, exemplified by protein unfolding experiments.

Contribution

It develops a new fluctuating entropy production concept applicable to partially observed, driven systems, extending stochastic thermodynamics to coarse-grained descriptions.

Findings

Distribution of entropy production retains microscopic information.

Bound established on the entropy production of unfolding events.

Framework validated with protein unfolding experiments.

Abstract

The laws of thermodynamics apply to biophysical systems on the nanoscale as described by the framework of stochastic thermodynamics. This theory provides universal, exact relations for quantities like work, which have been verified in experiments where a fully resolved description allows direct access to such quantities. Complementary studies consider partially hidden, coarse-grained descriptions, in which the mean entropy production typically is not directly accessible but can be bounded in terms of observable quantities. Going beyond the mean, we introduce a fluctuating entropy production that applies to individual trajectories in a coarse-grained description under time-dependent driving. Thus, this concept is applicable to the broad and experimentally significant class of driven systems in which not all relevant states can be resolved. We provide a paradigmatic example by studying an experimentally verified protein unfolding process. As a consequence, the entire distribution of the coarse-grained entropy production rather than merely its mean retains spatial and temporal information about the microscopic process. In particular, we obtain a bound on the distribution of the physical entropy production of individual unfolding events.