Computing quantum channel capacities
File(s)
Accepted version
Author(s)
Ramakrishnan, Navneeth
Iten, Raban
Scholz, Volkher B
Berta, Mario
Type
Journal Article
Abstract
The capacity of noisy quantum channels characterizes the highest rate at which information can be reliably transmitted and it is therefore of practical as well as fundamental importance. Capacities of classical channels are computed using alternating optimization schemes, called Blahut-Arimoto algorithms. In this work, we generalize classical Blahut-Arimoto algorithms to the quantum setting. In particular, we give efficient iterative schemes to compute the capacity of channels with classical input and quantum output, the quantum capacity of less noisy channels, the thermodynamic capacity of quantum channels, as well as the entanglement-assisted capacity of quantum channels. We give rigorous a priori and a posteriori bounds on the estimation error by employing quantum entropy inequalities and demonstrate fast convergence of our algorithms in numerical experiments.
Date Issued
2021-02-01
Date Acceptance
2020-10-16
Citation
IEEE Transactions on Information Theory, 2021, 67 (2), pp.946-960
ISSN
0018-9448
Publisher
Institute of Electrical and Electronics Engineers
Start Page
946
End Page
960
Journal / Book Title
IEEE Transactions on Information Theory
Volume
67
Issue
2
Copyright Statement
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000612137400017&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Technology
Computer Science, Information Systems
Engineering, Electrical & Electronic
Computer Science
Engineering
Channel capacity
Noise measurement
Convergence
Optimization
Approximation algorithms
Algorithms
channel capacity
entropy
information theory
quantum mechanics
ENTROPY
Publication Status
Published
Coverage Spatial
ELECTR NETWORK
Date Publish Online
2020-10-28