Search

We present a stylized model of controlled equilibration of a small system in a fluctuating environment. We derive the optimal control equations steering in finite-time the system between two equilibrium states. The corresponding thermodynamic transition is optimal in the sense that it occurs at minimum entropy if the set of admissible controls is restricted by certain bounds on the time derivatives of the protocols. We apply our equations to the engineered equilibration of an optical trap considered in a recent proof of principle experiment. We also analyze an elementary model of nucleation previously considered by Landauer to discuss the thermodynamic cost of one bit of information erasure. We expect our model to be a useful benchmark for experiment design as it exhibits the same integrability properties of well-known models of optimal mass transport by a compressible velocity field.

We investigate the thermodynamic efficiency of sub-micro-scale Stirling heat engines operating under the conditions described by overdamped stochastic thermodynamics. We show how to construct optimal protocols such that at maximum power the efficiency attains for constant isotropic mobility the universal law , where is the efficiency of an ideal Carnot cycle. We show that these protocols are specified by the solution of an optimal mass transport problem. Such solution can be determined explicitly using well-known Monge-Ampère-Kantorovich reconstruction algorithms. Furthermore, we show that the same law describes the efficiency of heat engines operating at maximum work over short time periods. Finally, we illustrate the straightforward extension of these results to cases when the mobility is anisotropic and temperature dependent. [ABSTRACT FROM AUTHOR]