Abstract
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
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Original language | English |
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Article number | 128054 |
Number of pages | 13 |
Journal | Physics Letters A |
Volume | 434 |
Early online date | 08 Mar 2022 |
DOIs | |
Publication status | Published - 16 May 2022 |
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Dive into the research topics of 'A tutorial on optimal control and reinforcement learning methods for quantum technologies'. Together they form a unique fingerprint.Student theses
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Machine learning applications in quantum state engineering
Brown, J. P. (Author), Paternostro, M. (Supervisor) & Ferraro, A. (Supervisor), Dec 2023Student thesis: Doctoral Thesis › Doctor of Philosophy
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Reinforcement learning based methods for optimal control and design of quantum systems
Sgroi, S. (Author), Paternostro, M. (Supervisor) & Ferraro, A. (Supervisor), Jul 2024Student thesis: Doctoral Thesis › Doctor of Philosophy
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