Efficient quantum repeater with respect to both entanglement-concentration rate and complexity of local operations and classical communication

Zhaofeng Su, Ji Guan, and Lvzhou Li
Phys. Rev. A 97, 012325 – Published 22 January 2018

Abstract

Quantum entanglement is an indispensable resource for many significant quantum information processing tasks. However, in practice, it is difficult to distribute quantum entanglement over a long distance, due to the absorption and noise in quantum channels. A solution to this challenge is a quantum repeater, which can extend the distance of entanglement distribution. In this scheme, the time consumption of classical communication and local operations takes an important place with respect to time efficiency. Motivated by this observation, we consider a basic quantum repeater scheme that focuses on not only the optimal rate of entanglement concentration but also the complexity of local operations and classical communication. First, we consider the case where two different two-qubit pure states are initially distributed in the scenario. We construct a protocol with the optimal entanglement-concentration rate and less consumption of local operations and classical communication. We also find a criterion for the projective measurements to achieve the optimal probability of creating a maximally entangled state between the two ends. Second, we consider the case in which two general pure states are prepared and general measurements are allowed. We get an upper bound on the probability for a successful measurement operation to produce a maximally entangled state without any further local operations.

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  • Received 18 September 2017

DOI:https://doi.org/10.1103/PhysRevA.97.012325

©2018 American Physical Society

Physics Subject Headings (PhySH)

General PhysicsQuantum Information, Science & Technology

Authors & Affiliations

Zhaofeng Su*

  • Centre for Quantum Software and Information, University of Technology Sydney, Ultimo, NSW 2007, Australia and Institute of Computer Science Theory, School of Data and Computer Science, Sun Yat-Sen University, Guangzhou 510006, China

Ji Guan

  • Centre for Quantum Software and Information, University of Technology Sydney, Ultimo, NSW 2007, Australia

Lvzhou Li

  • Institute of Computer Science Theory, School of Data and Computer Science, Sun Yat-Sen University, Guangzhou 510006, China

  • *zhaofeng.su@student.uts.edu.au
  • lilvzh@mail.sysu.edu.cn

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Issue

Vol. 97, Iss. 1 — January 2018

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