Global Optimization of the Control Strategy of a Brownian Information Engine: Efficient Information–Energy Exchange in a Generalized Potential Energy Surface

An information engine harnesses energy from a single heat bath, utilizing 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 center by 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 reentrance events are feasible. The consequences of the best control strategy are explained using sufficient examples.