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Benchmarking one-shot distillation in general quantum resource theories

Bartosz Regula, Kaifeng Bu, Ryuji Takagi, and Zi-Wen Liu
Phys. Rev. A 101, 062315 – Published 8 June 2020

Abstract

We study the one-shot distillation of general quantum resources, providing a unified quantitative description of the maximal fidelity achievable in this task, and revealing similarities shared by broad classes of resources. We establish fundamental quantitative and qualitative limitations on resource distillation applicable to all convex resource theories. We show that every convex quantum resource theory admits a meaningful notion of a pure maximally resourceful state, which maximizes several monotones of operational relevance and finds use in distillation. We endow the generalized robustness measure with an operational meaning as an exact quantifier of performance in distilling such maximal states in many classes of resources, including bi- and multipartite entanglement, multilevel coherence, as well as the whole family of affine resource theories, which encompasses important examples such as asymmetry, coherence, and thermodynamics.

  • Figure
  • Received 1 November 2019
  • Revised 28 April 2020
  • Accepted 8 May 2020

DOI:https://doi.org/10.1103/PhysRevA.101.062315

©2020 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & TechnologyGeneral Physics

Authors & Affiliations

Bartosz Regula1,*, Kaifeng Bu2,†, Ryuji Takagi3,‡, and Zi-Wen Liu4,§

  • 1School of Physical and Mathematical Sciences, Nanyang Technological University, 637371 Singapore
  • 2Department of Physics, Harvard University, Cambridge, Massachusetts 02138, USA
  • 3Center for Theoretical Physics and Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
  • 4Perimeter Institute for Theoretical Physics, Waterloo, Ontario, Canada N2L 2Y5

  • *bartosz.regula@gmail.com
  • kfbu@fas.harvard.edu
  • rtakagi@mit.edu
  • §zliu1@perimeterinstitute.ca

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Issue

Vol. 101, Iss. 6 — June 2020

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