Learning and Robust Control in Quantum Tec...

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Beschreibung

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.

Über den Autor

Daoyi Dong is currently a Scientia Associate Professor at the University of New South Wales, Canberra, Australia, and an Australian Research Council Future Fellow. His research interests include quantum control and machine learning. He has published more than 100 journal papers and more than 40 conference papers. Associate Professor Dong was awarded an ACA Temasek Young Educator Award by The Asian Control Association, a Humboldt Fellowship by Alexander von Humboldt Foundation, and is a recipient of a Future Fellowship, an International Collaboration Award and an Australian Post-Doctoral Fellowship from the Australian Research Council. He served as an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems (2015-2021) and currently a Technical Editor of IEEE/ASME Transactions on Mechatronics, an Associate Editor of IEEE Transactions on Cybernetics, and a Guest Editor of Annual Reviews in Control.

Ian R. Petersen is currently a professor at the Australian National University. 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 2016. He has served as an Associate Editor for the IEEE Transactions on Automatic Control, Systems and Control Letters, Automatica, and SIAM Journal on Control and Optimization. Currently he is an Editor for Automatica in the area of optimization in systems and control. He is a fellow of the 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 and 2018-2021 Trienniums. He was also elected to be a member of the IEEE Control Systems Society Board of Governors for the periods 2011-2013 and 2015-2017. He was Vice-president for Technical Activity for the Asian Control Association and was General Chair of the 2012 Australia Control Conference. He was General Chair of the 2015 IEEE Multi-Conference on Systems and Control.

Zusammenfassung

Provides systematic approach to control design and algorithms for quantum systems

Includes many recent results and ideas for practical applications

First monograph to present systematic introduction to robust and learning control of quantum systems

Inhaltsverzeichnis

Chapter 1. Introduction.- Chapter 2. Introduction to quantum mechanics and quantum control.- Chapter 3. Control and classification of inhomogeneous quantum ensembles.- Chapter 4. Sampling-based learning control of quantum systems with uncertainties.- Chapter 5. Machine learning for quantum control.- Chapter 6. Sliding mode control.- Chapter 7. Robust stability and performance analysis of quantum systems.- Chapter 8. H¥ control and fault-tolerant control of quantum systems.- Chapter 9.Concluding remarks.- Index.

Details

Erscheinungsjahr:	2023
Fachbereich:	Allgemeines
Genre:	Mathematik
Rubrik:	Naturwissenschaften & Technik
Medium:	Buch
Seiten:	272
Reihe:	Communications and Control Engineering
Inhalt:	xvii 252 S. 2 s/w Illustr. 45 farbige Illustr. 252 p. 47 illus. 45 illus. in color.
ISBN-13:	9783031202445
ISBN-10:	3031202449
Sprache:	Englisch
Ausstattung / Beilage:	HC runder Rücken kaschiert
Einband:	Gebunden
Autor:	Petersen, Ian R. Dong, Daoyi
Auflage:	2023
Hersteller:	Springer International Publishing Springer International Publishing AG Communications and Control Engineering
Maße:	241 x 160 x 21 mm
Von/Mit:	Ian R. Petersen (u. a.)
Erscheinungsdatum:	25.03.2023
Gewicht:	0,576 kg

Artikel-ID: 125014840