Computationally Efficient Nonlinear Bell Inequalities for Quantum Networks

Ming-Xing Luo
Phys. Rev. Lett. 120, 140402 – Published 3 April 2018
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Abstract

The correlations in quantum networks have attracted strong interest with new types of violations of the locality. The standard Bell inequalities cannot characterize the multipartite correlations that are generated by multiple sources. The main problem is that no computationally efficient method is available for constructing useful Bell inequalities for general quantum networks. In this work, we show a significant improvement by presenting new, explicit Bell-type inequalities for general networks including cyclic networks. These nonlinear inequalities are related to the matching problem of an equivalent unweighted bipartite graph that allows constructing a polynomial-time algorithm. For the quantum resources consisting of bipartite entangled pure states and generalized Greenberger-Horne-Zeilinger (GHZ) states, we prove the generic nonmultilocality of quantum networks with multiple independent observers using new Bell inequalities. The violations are maximal with respect to the presented Tsirelson’s bound for Einstein-Podolsky-Rosen states and GHZ states. Moreover, these violations hold for Werner states or some general noisy states. Our results suggest that the presented Bell inequalities can be used to characterize experimental quantum networks.

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  • Received 28 July 2017
  • Revised 9 February 2018

DOI:https://doi.org/10.1103/PhysRevLett.120.140402

© 2018 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & Technology

Authors & Affiliations

Ming-Xing Luo*

  • Information Security and National Computing Grid Laboratory, School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, China; CSNMT, International Cooperation Research Center of China, Southwest Jiaotong University, Chengdu 610031, China; and Department of Physics, University of Michigan, Ann Arbor, Michigan 48109, USA

  • *mxluo@home.swjtu.edu.cn

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Issue

Vol. 120, Iss. 14 — 6 April 2018

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