Many-box locality

Yuqian Zhou, Yu Cai, Jean-Daniel Bancal, Fei Gao, and Valerio Scarani
Phys. Rev. A 96, 052108 – Published 8 November 2017
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Abstract

There is an ongoing search for a physical or operational definition for quantum mechanics. Several informational principles have been proposed which are satisfied by a theory less restrictive than quantum mechanics. Here, we introduce the principle of “many-box locality,” which is a refined version of the previously proposed “macroscopic locality.” These principles are based on coarse graining the statistics of several copies of a given box. The set of behaviors satisfying many-box locality for N boxes is denoted LNMB. We study these sets in the bipartite scenario with two binary measurements, in relation with the sets Q and Q1+AB of quantum and “almost quantum” correlations, respectively. We find that the LNMB sets are, in general, not convex. For unbiased marginals, by working in the Fourier space we can prove analytically that LNMBQ for any finite N, while LMB=Q. Then, with suitably developed numerical tools, we find an example of a point that belongs to L16MB but not to Q1+AB. Among the problems that remain open is whether QLMB.

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  • Received 18 August 2017

DOI:https://doi.org/10.1103/PhysRevA.96.052108

©2017 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & Technology

Authors & Affiliations

Yuqian Zhou1,2,3, Yu Cai2,*, Jean-Daniel Bancal4, Fei Gao1, and Valerio Scarani2,5

  • 1State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • 2Centre for Quantum Technologies, National University of Singapore, Singapore
  • 3State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China
  • 4Quantum Optics Theory Group, University of Basel, Switzerland
  • 5Department of Physics, National University of Singapore, Singapore

  • *Corresponding author: caiyu01@gmail.com

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Issue

Vol. 96, Iss. 5 — November 2017

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