Driving rapidly while remaining in control: classical shortcuts from Hamiltonian to stochastic dynamics

TL;DR

This paper reviews control strategies in stochastic thermodynamics for mesoscopic systems, focusing on finite-time transformations, optimal paths, and applications like heat engines and biological systems, inspired by quantum control methods.

Contribution

It provides a comprehensive overview of control techniques in stochastic thermodynamics, including inverse engineering and reservoir control, highlighting their applications and connections to quantum control.

Findings

Analysis of control methods like inverse engineering and counterdiabatic driving

Discussion on optimal paths and speed limits in state transformations

Applications to heat engines and biological population control

Abstract

Stochastic thermodynamics lays down a broad framework to revisit the venerable concepts of heat, work and entropy production for individual stochastic trajectories of mesoscopic systems. Remarkably, this approach, relying on stochastic equations of motion, introduces time into the description of thermodynamic processes -- which opens the way to fine control them. As a result, the field of finite-time thermodynamics of mesoscopic systems has blossomed. In this article, after introducing a few concepts of control for isolated mechanical systems evolving according to deterministic equations of motion, we review the different strategies that have been developed to realize finite-time state-to-state transformations in both over and underdamped regimes, by the proper design of time-dependent control parameters/driving. The systems under study are stochastic, epitomized by a Brownian object immersed in a fluid; they are thus strongly coupled to their environment playing the role of a reservoir. Interestingly, a few of those methods (inverse engineering, counterdiabatic driving, fast-forward) are directly inspired by their counterpart in quantum control. The review also analyzes the control through reservoir engineering. Besides the reachability of a given target state from a known initial state, the question of the optimal path is discussed. Optimality is here defined with respect to a cost function, a subject intimately related to the field of information thermodynamics and the question of speed limit. Another natural extension discussed deals with the connection between arbitrary states or non-equilibrium steady states. This field of control in stochastic thermodynamics enjoys a wealth of applications, ranging from optimal mesoscopic heat engines to population control in biological systems.