Taming a Maxwell's demon for experimental stochastic resetting

TL;DR

This paper experimentally demonstrates thermodynamically controlled stochastic resetting using optical trapping, effectively implementing a Maxwell's demon that erases information and converts heat into work, revealing non-ergodic behavior.

Contribution

It introduces an experimental method to control stochastic resetting through information thermodynamics, minimizing energetic costs and analyzing non-ergodic trajectories.

Findings

SR converts heat into work from a single bath without feedback

The energetic cost of SR can approach the reversible minimum bound

Trajectories generated by the demon break ergodicity

Abstract

A diffusive process that is reset to its origin at random times, so-called stochastic resetting (SR), is an ubiquitous expedient in many natural systems . Yet, beyond its ability to improve the efficiency of target searching, SR is a true non-equilibrium thermodynamic process that brings forward new and challenging questions . Here, we show how the recent developments of experimental information thermodynamics renew the way to address SR and can lead, beyond a new understanding, to better control on the non-equilibrium nature of SR. This thermodynamically controlled SR is experimentally implemented within a time-dependent optical trapping potential. We show in particular that SR converts heat into work from a single bath continuously and without feedback. This implements a Maxwell's demon that constantly erases information. In our experiments, the erasure takes the form of a protocol that allows to evaluate the true energetic cost of SR. We show that using an appropriate measure of the available information, this cost can be reduced to a reversible minimum while being bounded by the Landauer limit. We finally reveal that the individual trajectories generated by the demon all break ergodicity and thus demonstrate the non-ergodic nature of the demon's modus operandi. Our results offer new approaches to processes, such as SR, where the informational framework provides key experimental tools for their non-equilibrium thermodynamic control.