l1-norm coherence of assistance

Ming-Jing Zhao, Teng Ma, Quan Quan, Heng Fan, and Rajesh Pereira
Phys. Rev. A 100, 012315 – Published 15 July 2019

Abstract

We introduce and study the l1-norm coherence of assistance both theoretically and operationally. We first provide an upper bound for the l1-norm coherence of assistance and show a necessary and sufficient condition for the saturation of the upper bound. For two- and three-dimensional quantum states, the analytical expression of the l1-norm coherence of assistance is given. Operationally, the mixed quantum coherence can always be increased with the help of another party's local measurement and one way classical communication since the l1-norm coherence of assistance, as well as the relative-entropy coherence of assistance, are shown to be strictly larger than the original coherence. The relation between the l1-norm coherence of assistance and entanglement is revealed. Finally, a comparison between the l1-norm coherence of assistance and the relative-entropy coherence of assistance is made.

  • Received 4 March 2019

DOI:https://doi.org/10.1103/PhysRevA.100.012315

©2019 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & Technology

Authors & Affiliations

Ming-Jing Zhao1, Teng Ma2,3,4, Quan Quan5, Heng Fan6, and Rajesh Pereira7

  • 1School of Science, Beijing Information Science and Technology University, Beijing 100192, China
  • 2Shenzhen Institute for Quantum Science and Engineering and Department of Physics, South University of Science and Technology of China, Shenzhen 518055, China
  • 3Shenzhen Key Laboratory of Quantum Science and Engineering, Shenzhen 518055, China
  • 4Key Laboratory of Quantum Information, University of Science and Technology of China, CAS, Hefei 230026, China
  • 5State Key Laboratory of Low-Dimensional Quantum Physics and Department of Physics, Tsinghua University, Beijing 100084, China
  • 6Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China
  • 7Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada N1G2W1

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Issue

Vol. 100, Iss. 1 — July 2019

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