Quantum Monge-Kantorovich Problem and Transport Distance between Density Matrices

Shmuel Friedland, Michał Eckstein, Sam Cole, and Karol Życzkowski
Phys. Rev. Lett. 129, 110402 – Published 7 September 2022
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Abstract

A quantum version of the Monge-Kantorovich optimal transport problem is analyzed. The transport cost is minimized over the set of all bipartite coupling states ρAB such that both of its reduced density matrices ρA and ρB of dimension N are fixed. We show that, selecting the quantum cost matrix to be proportional to the projector on the antisymmetric subspace, the minimal transport cost leads to a semidistance between ρA and ρB, which is bounded from below by the rescaled Bures distance and from above by the root infidelity. In the single-qubit case, we provide a semianalytic expression for the optimal transport cost between any two states and prove that its square root satisfies the triangle inequality and yields an analog of the Wasserstein distance of the order of 2 on the set of density matrices. We introduce an associated measure of proximity of quantum states, called swap fidelity, and discuss its properties and applications in quantum machine learning.

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  • Received 23 February 2021
  • Revised 1 August 2022
  • Accepted 2 August 2022

DOI:https://doi.org/10.1103/PhysRevLett.129.110402

© 2022 American Physical Society

Physics Subject Headings (PhySH)

Statistical Physics & ThermodynamicsQuantum Information, Science & TechnologyGeneral Physics

Authors & Affiliations

Shmuel Friedland1, Michał Eckstein2,*, Sam Cole3, and Karol Życzkowski2,4

  • 1Department of Mathematics, Statistics and Computer Science, University of Illinois, Chicago, Illinois 60607-7045, USA
  • 2Institute of Theoretical Physics, Jagiellonian University and Mark Kac Center, ul. Łojasiewicza 11, 30–348 Kraków, Poland
  • 3Department of Mathematics, University of Missouri, Columbia, Missouri 65211, USA
  • 4Center for Theoretical Physics, Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warszawa, Poland

  • *Corresponding author. michal.eckstein@uj.edu.pl

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Issue

Vol. 129, Iss. 11 — 9 September 2022

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