Global optimisation of the control strategy of a Brownian information Engine: Efficient information-energy exchange in a generalised potential energy surface

TL;DR

This paper investigates the optimal control strategy for a Brownian information engine operating in arbitrary potential energy surfaces, maximizing energy extraction from information feedback and revealing conditions for heater and refrigerator behavior.

Contribution

It introduces a general framework for optimizing control strategies of Brownian information engines in arbitrary potentials, demonstrating conditions for efficient energy conversion and re-entrant heating and cooling behaviors.

Findings

Optimal control strategy aligns the potential minimum with feedback distance.

The engine can act as a heater or refrigerator depending on energy conditions.

Multiple re-entrant heater-refrigerator cycles are possible in different potential shapes.

Abstract

An information engine harnesses energy from a single heat bath, utilising the gathered information. This study explores the best control strategy of a Brownian information engine (BIE), confined in a potential energy surface (PES) of arbitrary shape, and experiencing a measurement outcome-based feedback cycle. The feedback site corresponds to an instantaneous shift in the potential centre to an additional feedback distance over the measurement outcome. The strategy for the most efficient information-to-energy conversion is achieved when the position of the global potential minimum corresponds to the additional feedback distance. The BIE acts as a heater if and only if the average potential energy is higher than the energy at the additional feedback distance. Operating under confinement PES of different shapes, the BIE can harness energy beyond the average potential energy, and multiple heater-refrigerator re-entrance events are feasible. The consequences of the best control strategy are explained using sufficient examples.