Strong converse bound on the two-way assisted quantum capacity
File(s)1570422502.pdf (239.66 KB)
Published version
Author(s)
Berta, M
Wilde, MM
Type
Conference Paper
Abstract
We show that the max-Rains information of a quantum channel is an efficiently computable, single-letter strong converse upper bound for transmitting quantum information over quantum channels when assisted by positive-partial-transpose (PPT) preserving channels between every use of the channel. This includes in particular the quantum capacity with local operations and classical communication (LOCC) assistance. For our proof we make use of the amortized entanglement of quantum channels, which is defined as the largest net amount of entanglement that can be generated if the sender and receiver are allowed to share an arbitrary state before using the channel. Our main technical result is that amortization does not enhance the entanglement of quantum channels when entanglement is quantified by the max-Rains relative entropy. We prove this statement by employing semi-definite programming (SDP) duality and SDP formulations for the max-Rains relative entropy and the channel's max-Rains information, found recently in [Wang et al., arXiv:1709.00200].
Date Issued
2018-08-16
Date Acceptance
2018-06-17
Citation
IEEE International Symposium on Information Theory - Proceedings, 2018, pp.2167-2171
ISBN
9781538647806
ISSN
2157-8095
Publisher
IEEE
Start Page
2167
End Page
2171
Journal / Book Title
IEEE International Symposium on Information Theory - Proceedings
Copyright Statement
© 2018 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.
Source
International Symposium on Information Theory (ISIT)
Publication Status
Published
Start Date
2018-06-17
Finish Date
2018-06-22
Coverage Spatial
Vail, CO, USA
Date Publish Online
2018-08-16