Designing optimal discrete-feedback thermodynamic engines

TL;DR

This paper introduces a method for designing optimal feedback protocols in thermodynamic engines, leveraging feedback reversibility to maximize work extraction from information, demonstrated through multi-particle Szilard engine examples.

Contribution

The paper presents a novel approach to designing feedback protocols for thermodynamic engines using feedback reversibility, enabling maximum work extraction from gained information.

Findings

The method achieves optimal work extraction in feedback-controlled thermodynamic processes.

Application to multi-particle Szilard engines demonstrates practical utility.

Feedback reversibility guides the design of efficient thermodynamic protocols.

Abstract

Feedback can be utilized to convert information into useful work, making it an effective tool for increasing the performance of thermodynamic engines. Using feedback reversibility as a guiding principle, we devise a method for designing optimal feedback protocols for thermodynamic engines that extract all the information gained during feedback as work. Our method is based on the observation that in a feedback-reversible process the measurement and the time-reversal of the ensuing protocol both prepare the system in the same probabilistic state. We illustrate the utility of our method with two examples of the multi-particle Szilard engine.