Cost of Quantum Entanglement Simplified

Xin Wang and Mark M. Wilde
Phys. Rev. Lett. 125, 040502 – Published 24 July 2020
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Abstract

Quantum entanglement is a key physical resource in quantum information processing that allows for performing basic quantum tasks such as teleportation and quantum key distribution, which are impossible in the classical world. Ever since the rise of quantum information theory, it has been an open problem to quantify entanglement in an information-theoretically meaningful way. In particular, every previously defined entanglement measure bearing a precise information-theoretic meaning is not known to be efficiently computable, or if it is efficiently computable, then it is not known to have a precise information-theoretic meaning. In this Letter, we meet this challenge by introducing an entanglement measure that has a precise information-theoretic meaning as the exact cost required to prepare an entangled state when two distant parties are allowed to perform quantum operations that completely preserve the positivity of the partial transpose. Additionally, this entanglement measure is efficiently computable by means of a semidefinite program, and it bears a number of useful properties such as additivity and faithfulness. Our results bring key insights into the fundamental entanglement structure of arbitrary quantum states, and they can be used directly to assess and quantify the entanglement produced in quantum-physical experiments.

  • Received 15 December 2019
  • Accepted 7 July 2020

DOI:https://doi.org/10.1103/PhysRevLett.125.040502

© 2020 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & Technology

Authors & Affiliations

Xin Wang1,2,* and Mark M. Wilde3,†

  • 1Institute for Quantum Computing, Baidu Research, Beijing 100193, China
  • 2Joint Center for Quantum Information and Computer Science, University of Maryland, College Park, Maryland 20742, USA
  • 3Hearne Institute for Theoretical Physics, Department of Physics and Astronomy and Center for Computation and Technology, Louisiana State University, Baton Rouge, Louisiana 70803, USA

  • *wangxin73@baidu.com
  • mwilde@lsu.edu

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Issue

Vol. 125, Iss. 4 — 24 July 2020

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