Floquet engineering of quantum thermal machines: A gradient-based spectral method to optimize their performance

TL;DR

This paper introduces a gradient-based spectral method for optimizing quantum thermal machines modeled as periodically-driven open quantum systems, enabling the identification of optimal control protocols for enhanced performance.

Contribution

It presents a novel spectral optimization technique for quantum thermal engines using gradient-based methods within a Floquet framework.

Findings

Demonstrates the effectiveness of the method in finding optimal control regimes.

Provides a systematic approach to optimize external controls in QTMs.

Applicable to experimental setups with physical constraints.

Abstract

A procedure to find optimal regimes for quantum thermal engines (QTMs) is described and demonstrated. The QTMs are modelled as the periodically-driven non-equilibrium steady states of open quantum systems, whose dynamics is approximated in this work with Markovian master equations. The action of the external agent, and the couplings to the heat reservoirs can be modulated with control functions, and it is the time-dependent shape of these control functions the object of optimisation. Those functions can be freely parameterised, which permits to constrain the solutions according to experimental or physical requirements.