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Quantum nonlocality of massive qubits in a moving frame

在一个动人的框架的巨大的 qubits 的量 nonlocality

作     者:Hong-Yi Su Yu-Chun Wu Jing-Ling Chen Chunfeng Wu L. C. Kwek 

作者机构:Theoretical Physics Division Chern Institute of Mathematics Nankai University Tianjin 300071 People's Republic of China Key Laboratory of Quantum Information University of Science and Technology of China 230026 Hefei People's Republic of China Centre for Quantum Technologies National University of Singapore 3 Science Drive 2 Singapore 117543 Pillar of Engineering Product Development Singapore University of Technology and Design 20 Dover Drive Singapore 138682 National Institute of Education and Institute of Advanced Studies Nanyang Technological University 1 Nanyang Walk Singapore 637616 Institute of Advanced Studies Nanyang Technological University 60 Nanyang View Singapore 639673 

出 版 物:《Physical Review A》 (物理学评论A辑:原子、分子和光学物理学)

年 卷 期:2013年第88卷第2期

页      面:022124-022124页

核心收录:

学科分类:070207[理学-光学] 07[理学] 08[工学] 0803[工学-光学工程] 0702[理学-物理学] 

基  金:National Basic Research Program (973 Program) of China [2012CB921900] NSF of China [10975075, 11175089] National Basic Research Program of China [2011CBA00200, 2011CB921200] National Natural Science Foundation of China [11275182, 60921091] National Research Foundation Ministry of Education of Singapore 

主  题:QUBITS QUANTUM entanglement QUANTUM states WIGNER rotation matrix PARAMETER estimation LORENTZ transformations 

摘      要:We perform numerical tests on the quantum nonlocality of two-level quantum systems (qubits) observed by a uniformly moving observer. Under a suitable momentum setting, the quantum nonlocality of two-qubit nonmaximally entangled states could be weakened drastically by the Lorentz transformation, allowing for the existence of local-hidden-variable models, whereas three-qubit genuinely entangled states are robust. In particular, the generalized Greenberger-Horne-Zeilinger state remains nonlocal under arbitrary Wigner rotation and the generalized W state could admit local-hidden-variable models within a rather narrow range of parameters.

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