Information bound for entropy production from the detailed fluctuation theorem

TL;DR

This paper derives a fundamental information-theoretic bound on entropy production using the detailed fluctuation theorem, applicable to various physical systems and verified through experiments.

Contribution

It introduces a tight upper bound on entropy production based on information theory and the detailed fluctuation theorem, extending to continuous systems and quantum engines.

Findings

The bound is expressed via a maximal distribution in the exponential family.

Heat transfer in a bosonic mode approaches the maximal distribution in a certain limit.

The bound is validated experimentally with levitated nanoparticles.

Abstract

Fluctuation theorems impose fundamental bounds in the statistics of the entropy production, with the second law of thermodynamics being the most famous. Using information theory, we quantify the information of entropy production and find an upper tight bound as a function of its mean from the strong detailed fluctuation theorem. The bound is given in terms of a maximal distribution, a member of the exponential family with nonlinear argument. We show that the entropy produced by heat transfer using a bosonic mode at weak coupling reproduces the maximal distribution in a limiting case. The upper bound is extended to the continuous domain and verified for the heat transfer using a levitated nanoparticle. Finally, we show that a composition of qubit swap engines satisfies a particular case of the maximal distribution regardless of its size.