A tutorial on optimal control and reinforcement learning methods for quantum technologies

Quantum Optimal Control is an established field of research which is necessary for the development of Quantum Technologies. In recent years, Machine Learning techniques have been proved useful to tackle a variety of quantum problems. In particular, Reinforcement Learning has been employed to address typical problems of control of quantum systems. In this tutorial we introduce the methods of Quantum Optimal Control and Reinforcement Learning by applying them to the problem of three-level population transfer. The jupyter notebooks to reproduce some of our results are open-sourced and available on github(1). (C) 2022 Elsevier B.V. All rights reserved.

Automated summary

Quantum Optimal Control and Reinforcement Learning are effective methods for solving control problems in quantum systems, which can be implemented using machine learning techniques. This tutorial introduces these methods and provides examples using the problem of three-level population transfer.