Maximal fluctuation exploitation in Gaussian information engines

TL;DR

This paper investigates the maximum efficiency of information engines in converting information into stored energy, revealing how feedback control can optimize energy storage within thermodynamic limits.

Contribution

It introduces a simple, experimentally relevant model to analyze the limits of information-to-energy conversion with energy storage constraints.

Findings

Restricting energy output limits conversion efficiency.

Feedback control with work input enhances energy storage rate.

Theoretical limits are sharpened for real information-to-energy systems.

Abstract

Understanding the connections between information and thermodynamics has been among the most visible applications of stochastic thermodynamics. While recent theoretical advances have established that the second law of thermodynamics sets limits on information-to-energy conversion, it is currently unclear to what extent real systems can achieve the predicted theoretical limits. Using a simple model of an information engine that has recently been experimentally implemented, we explore the limits of information-to-energy conversion when an information engine's benefit is limited to output energy that can be stored. We find that restricting the engine's output in this way can limit its ability to convert information to energy. Nevertheless, a feedback control that inputs work can allow the engine to store energy at the highest achievable rate. These results sharpen our theoretical understanding of the limits of real systems that convert information to energy.