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Experimental Simultaneous Learning of Multiple Nonclassical Correlations

文献类型：期刊论文

作者Yang, Mu1,9; Ren, Chang-liang2; Ma, Yue-chi3,4,5; Xiao, Ya6; Ye, Xiang-Jun1,9; Song, Lu-Lu4,5,7; Xu, Jin-Shi1,9; Yung, Man Hong4,5,7,8; Li, Chuan-Feng1,9; Guo, Guang-Can1,9
刊名PHYSICAL REVIEW LETTERS
出版日期2019-11-06
卷号123期号:19页码:6
ISSN号0031-9007
DOI10.1103/PhysRevLett.123.190401
通讯作者Xu, Jin-Shi(jsxu@ustc.edu.cn) ; Yung, Man Hong(yung@sustc.edu.cn) ; Li, Chuan-Feng(cfli@ustc.edu.cn)
英文摘要Nonclassical correlations can be regarded as resources for quantum information processing. However, the classification problem of nonclassical correlations for quantum states remains a challenge, even for finite-size systems. Although there exists a set of criteria for determining individual nonclassical correlations, a unified framework that is capable of simultaneously classifying multiple correlations is still missing. In this Letter, we experimentally explored the possibility of applying machine-learning methods for simultaneously identifying nonclassical correlations. Specifically, by using partial information, we applied an artificial neural network, support vector machine, and decision tree for learning entanglement, quantum steering, and nonlocality. Overall, we found that, for a family of quantum states, all three approaches can achieve high accuracy for the classification problem. Moreover, the run time of the machine-learning methods to output the state label is experimentally found to be significantly less than that of state tomography.
资助项目National Key Research and Development Program of China[2016YFA0302700] ; National Natural Science Foundation of China[61725504] ; National Natural Science Foundation of China[11774335] ; National Natural Science Foundation of China[11821404] ; National Natural Science Foundation of China[11605205] ; National Natural Science Foundation of China[11875160] ; National Natural Science Foundation of China[U1801661] ; Key Research Program of Frontier Sciences, Chinese Academy of Sciences (CAS)[QYZDY-SSW-SLH003] ; Science Foundation of the CAS[ZDRW-XH-2019-1] ; Anhui Initiative in Quantum Information Technologies[AHY060300] ; Anhui Initiative in Quantum Information Technologies[AHY020100] ; Fundamental Research Funds for the Central Universities[WK2030380017] ; Fundamental Research Funds for the Central Universities[WK2470000026] ; National key research and development program[2017YFA0305200] ; Youth Innovation Promotion Association (CAS)[2015317] ; Natural Science Foundation of Chongqing[cstc2015jcyjA00021] ; Natural Science Foundation of Chongqing[cstc2018jcyjA2509] ; Entrepreneurship and Innovation Support Program for Chongqing Overseas Returnees[cx2017134] ; Entrepreneurship and Innovation Support Program for Chongqing Overseas Returnees[cx2018040] ; Natural Science Foundation of Guangdong Province[2017B030308003] ; Key R&D Program of Guangdong province[2018B030326001] ; Guangdong Innovative and Entrepreneurial Research Team Program[2016ZT06D348] ; Science, Technology and Innovation Commission of Shenzhen Municipality[JCYJ20170412152620376] ; Science, Technology and Innovation Commission of Shenzhen Municipality[JCYJ20170817105046702] ; Science, Technology and Innovation Commission of Shenzhen Municipality[KYTDPT20181011104202253] ; Economy, Trade and Information Commission of Shenzhen Municipality[201901161512]
WOS研究方向Physics
语种英语
WOS记录号WOS:000495073200001
出版者AMER PHYSICAL SOC
源URL[http://119.78.100.138/handle/2HOD01W0/10313]  
专题中国科学院重庆绿色智能技术研究院
通讯作者Xu, Jin-Shi; Yung, Man Hong; Li, Chuan-Feng
作者单位1.Univ Sci & Technol China, CAS Ctr Excellence Quantum Informat & Quantum Phy, Hefei 230026, Anhui, Peoples R China
2.Chinese Acad Sci, Ctr Nanofabricat & Syst Integrat, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
3.Tsinghua Univ, Ctr Quantum Informat, Inst Interdisciplinary Informat Sci, Beijing 100084, Peoples R China
4.Southern Univ Sci & Technol, Shenzhen Inst Quantum Sci & Engn, Shenzhen 518055, Peoples R China
5.Southern Univ Sci & Technol, Dept Phys, Shenzhen 518055, Peoples R China
6.Ocean Univ China, Dept Phys, Qingdao 266100, Shandong, Peoples R China
7.Southern Univ Sci & Technol, Shenzhen Key Lab Quantum Sci & Engn, Shenzhen 518055, Peoples R China
8.Huawei Technol, Cent Res Inst, Shenzhen 518129, Peoples R China
9.Univ Sci & Technol China, CAS Key Lab Quantum Wormat, Hefei 230026, Anhui, Peoples R China
推荐引用方式
GB/T 7714		 Yang, Mu,Ren, Chang-liang,Ma, Yue-chi,et al. Experimental Simultaneous Learning of Multiple Nonclassical Correlations[J]. PHYSICAL REVIEW LETTERS,2019,123(19):6.
APA Yang, Mu.,Ren, Chang-liang.,Ma, Yue-chi.,Xiao, Ya.,Ye, Xiang-Jun.,...&Guo, Guang-Can.(2019).Experimental Simultaneous Learning of Multiple Nonclassical Correlations.PHYSICAL REVIEW LETTERS,123(19),6.
MLA Yang, Mu,et al."Experimental Simultaneous Learning of Multiple Nonclassical Correlations".PHYSICAL REVIEW LETTERS 123.19(2019):6.

入库方式： OAI收割

来源：重庆绿色智能技术研究院

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