Learning and Robust Control in Quantum Technology
Authors: Daoyi Dong, Ian R. Petersen
Press: Springer
Publishing time: 2023
ISBN 978-3-031-20244-5
About this book
This monograph provides a state-of-the-art treatment of learning and robust control in quantum technology. It presents a systematic investigation of control design and algorithm realisation for several classes of quantum systems using control-theoretic tools and machine-learning methods. The approaches rely heavily on examples and the authors cover: sliding mode control of quantum systems; control and classification of inhomogeneous quantum ensembles using sampling-based learning control; robust and optimal control design using machine-learning methods; robust stability of quantum systems; and H∞ and fault-tolerant control of quantum systems. Both theoretical algorithm design and potential practical applications are considered. Methods for enhancing robustness of performance are developed in the context of quantum state preparation, quantum gate construction, and ultrafast control of molecules.
Researchers and graduates studying systems and control theory, quantum control, and quantum engineering, especially from backgrounds in electrical engineering, applied mathematics and quantum information will find Learning and Robust Control in Quantum Technology to be a valuable reference for the investigation of learning and robust control of quantum systems. The material contained in this book will also interest chemists and physicists working on chemical physics, quantum optics, and quantum information technology.
About the authors
Daoyi Dong (IEEE Fellow) is currently a Professor at the Australian National University. Before moving to the Australian National University, he had worked at the University of New South Wales, Australia for 15 years. He was with the Academy of Mathematics and Systems Science, Chinese Academy of Sciences and Zhejiang University. He had/has visiting positions at Princeton University, USA, RIKEN, Japan, the University of Hong Kong, Hong Kong, University of Duisburg-Essen, Germany, the University of Sydney, and the University of Melbourne, Australia. His research interests include machine learning, quantum control, system identification and renewable energy. He was awarded an ACA Temasek Young Educator Award by the Asian Control Association and is a recipient of a Future Fellowship, an International Collaboration Award from the Australian Research Council, and a Humboldt Research Fellowship from the Alexander von Humboldt Foundation in Germany.
Ian R. Petersen (IEEE Fellow) received a Ph.D. in Electrical Engineering in 1984 from the University of Rochester, USA. From 1983 to 1985 he was a Postdoctoral Fellow at the Australian National University. In 1985 he joined the University of New South Wales, Canberra, Australia. He moved to The Australian National University in 2017 where he is currently a Professor in the School of Engineering. He was Acting Deputy Vice-Chancellor Research for the University of New South Wales in 2004 and 2005. He held an Australian Research Council Professorial Fellowship from 2005 to 2007, an Australian Research Council Federation Fellowship from 2007 to 2012, and an Australian Research Council Laureate Fellowship from 2012 to 2017. He is a fellow of IFAC, the IEEE and the Australian Academy of Science. His main research interests are in robust control theory, quantum control theory and stochastic control theory. Ian Petersen was elected IFAC Council Member for the 2014–2017 Triennium. He is an Editor of Automatica.
