Learning-Based Quantum Robust Control: Algorithm, Applications, and Experiments

doi:10.1109/TCYB.2019.2921424

CSpace

	Learning-Based Quantum Robust Control: Algorithm, Applications, and Experiments
	Dong, Daoyi 1,2; Xing, Xi 2; Ma, Hailan 3; Chen, Chunlin 3; Liu, Zhixin 4; Rabitz, Herschel 2
	2020-08-01
发表期刊	IEEE TRANSACTIONS ON CYBERNETICS
ISSN	2168-2267
卷号	50 期号:8 页码:3581-3593
摘要	Robust control design for quantum systems has been recognized as a key task in quantum information technology, molecular chemistry, and atomic physics. In this paper, an improved differential evolution algorithm, referred to as multiple-samples and mixed-strategy DE (msMS_DE), is proposed to search robust fields for various quantum control problems. In msMS_DE, multiple samples are used for fitness evaluation and a mixed strategy is employed for the mutation operation. In particular, the msMS_DE algorithm is applied to the control problems of: 1) open inhomogeneous quantum ensembles and 2) the consensus goal of a quantum network with uncertainties. Numerical results are presented to demonstrate the excellent performance of the improved machine learning algorithm for these two classes of quantum robust control problems. Furthermore, msMS_DE is experimentally implemented on femtosecond (fs) laser control applications to optimize two-photon absorption and control fragmentation of the molecule CH2BrI. The experimental results demonstrate the excellent performance of msMS_DE in searching for effective fs laser pulses for various tasks.
关键词	Nonhomogeneous media Robust control Quantum computing Task analysis Chemistry Machine learning algorithms Uncertainty Differential evolution femtosecond laser quantum control quantum learning quantum robust control
DOI	10.1109/TCYB.2019.2921424
收录类别	SCI
语种	英语
资助项目	Australian Research Council[DP190101566] ; National Natural Science Foundation of China[61828303] ; National Natural Science Foundation of China[61833010] ; NSF[CHE-1464569] ; Army Research Office[W911NF-16-1-0014]
WOS研究方向	Automation & Control Systems ; Computer Science
WOS类目	Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS记录号	WOS:000548811800014
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/51820
专题	中国科学院数学与系统科学研究院
通讯作者	Dong, Daoyi
作者单位	1.Univ New South Wales, Sch Engn & Informat Technol, Canberra, ACT 2600, Australia 2.Princeton Univ, Dept Chem, Princeton, NJ 08544 USA 3.Nanjing Univ, Sch Management & Engn, Dept Control & Syst Engn, Nanjing 210093, Peoples R China 4.Chinese Acad Sci, Acad Math & Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Dong, Daoyi,Xing, Xi,Ma, Hailan,et al. Learning-Based Quantum Robust Control: Algorithm, Applications, and Experiments[J]. IEEE TRANSACTIONS ON CYBERNETICS,2020,50(8):3581-3593.
APA	Dong, Daoyi,Xing, Xi,Ma, Hailan,Chen, Chunlin,Liu, Zhixin,&Rabitz, Herschel.(2020).Learning-Based Quantum Robust Control: Algorithm, Applications, and Experiments.IEEE TRANSACTIONS ON CYBERNETICS,50(8),3581-3593.
MLA	Dong, Daoyi,et al."Learning-Based Quantum Robust Control: Algorithm, Applications, and Experiments".IEEE TRANSACTIONS ON CYBERNETICS 50.8(2020):3581-3593.