Information engine fueled by first-passage times

TL;DR

This paper experimentally and theoretically explores a thermodynamic information engine using a cantilever with feedback triggered by first-passage times, deriving fluctuation theorems and work bounds based on protocol distributions.

Contribution

It introduces a novel framework for fluctuation theorems and work bounds using first-passage-time based feedback control, extending beyond specific experimental setups.

Findings

Derived and verified two fluctuation theorems involving information and work.

Established a tight bound on work extraction from thermal fluctuations.

Developed a general protocol-based framework for fluctuation theorems.

Abstract

Using a mechanical cantilever submitted to electrostatic feedback control, we investigate the thermodynamic properties of an information engine that extracts work from thermal fluctuations. The cantilever position is rapidly sampled and the feedback is triggered by the first passage of the system across a fixed threshold. The information $\Delta I$ associated with the feedback is based on the first-passage-time distribution. In this setting, we derive and experimentally verify two distinct fluctuation theorems that involve $\Delta I$ and give a tight bound on the work produced by the engine. Our results extend beyond the specific application to our experiment: we develop a general framework for obtaining fluctuation theorems and work bounds, formulated in terms of probability distributions of protocols rather than underlying measurement outcomes.