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Quantum Ensemble Classification: A Sampling-Based Learning Control Approach

文献类型：期刊论文

作者Chen, Chunlin1,2; Dong, Daoyi3; Qi, Bo4; Petersen, Ian R.3; Rabitz, Herschel2
刊名IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
出版日期2017-06-01
卷号28期号:6页码:1345-1359
关键词Inhomogeneous ensembles quantum discrimination quantum ensemble classification (QEC) sampling-based learning control (SLC)
ISSN号2162-237X
DOI10.1109/TNNLS.2016.2540719
英文摘要Quantum ensemble classification (QEC) has significant applications in discrimination of atoms (or molecules), separation of isotopes, and quantum information extraction. However, quantum mechanics forbids deterministic discrimination among nonorthogonal states. The classification of inhomogeneous quantum ensembles is very challenging, since there exist variations in the parameters characterizing the members within different classes. In this paper, we recast QEC as a supervised quantum learning problem. A systematic classification methodology is presented by using a sampling-based learning control (SLC) approach for quantum discrimination. The classification task is accomplished via simultaneously steering members belonging to different classes to their corresponding target states (e.g., mutually orthogonal states). First, a new discrimination method is proposed for two similar quantum systems. Then, an SLC method is presented for QEC. Numerical results demonstrate the effectiveness of the proposed approach for the binary classification of two-level quantum ensembles and the multiclass classification of multilevel quantum ensembles.
资助项目National Natural Science Foundation of China[61004049] ; National Natural Science Foundation of China[61273327] ; National Natural Science Foundation of China[61374092] ; Australian Research Council[DP130101658] ; Australian Research Council[FL110100020] ; U.S. National Science Foundation[CHE-0718610]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000401982100008
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/25472]  
专题系统科学研究所
通讯作者Dong, Daoyi
作者单位1.Nanjing Univ, Sch Management & Engn, Dept Control & Syst Engn, Nanjing 210093, Jiangsu, Peoples R China
2.Princeton Univ, Dept Chem, Princeton, NJ 08544 USA
3.Univ New South Wales, Sch Engn & Informat Technol, Canberra, ACT 2600, Australia
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		 Chen, Chunlin,Dong, Daoyi,Qi, Bo,et al. Quantum Ensemble Classification: A Sampling-Based Learning Control Approach[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2017,28(6):1345-1359.
APA Chen, Chunlin,Dong, Daoyi,Qi, Bo,Petersen, Ian R.,&Rabitz, Herschel.(2017).Quantum Ensemble Classification: A Sampling-Based Learning Control Approach.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,28(6),1345-1359.
MLA Chen, Chunlin,et al."Quantum Ensemble Classification: A Sampling-Based Learning Control Approach".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 28.6(2017):1345-1359.

入库方式： OAI收割

来源：数学与系统科学研究院

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