@article{1461801,
      recid = {1461801},
      author = {Dong, Daoyi, and Petersen, Ian Richard,},
      title = {Learning and robust control in quantum technology /},
      pages = {1 online resource (xvii, 252 pages) :},
      abstract = {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.},
      url = {http://library.usi.edu/record/1461801},
      doi = {https://doi.org/10.1007/978-3-031-20245-2},
}