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Abstract

We derive a new bound on the effectiveness of the Petz map as a universal recovery channel in approximate quantum error correction using the second sandwiched R\'{e}nyi relative entropy \(\tilde{D}_{2}\). For large Hilbert spaces, our bound implies that the Petz map performs quantum error correction with order-\(\epsilon\) accuracy whenever the data processing inequality for \(\tilde{D}_{2}\) is saturated up to terms of order \(\epsilon^2\) times the inverse Hilbert space dimension. Conceptually, our result is obtained by extending arXiv:2011.03473, in which we studied exact saturation of the data processing inequality using differential geometry, to the case of approximate saturation. Important roles are played by (i) the fact that the exponential of the second sandwiched R\'{e}nyi relative entropy is quadratic in its first argument, and (ii) the observation that the second sandwiched R\'{e}nyi relative entropy satisfies the data processing inequality even when its first argument is a non-positive Hermitian operator.

Details

1009240
Identifier / keyword
Title
Approximate Petz recovery from the geometry of density operators
Publication title
arXiv.org; Ithaca
Publication year
2022
Publication date
Mar 18, 2022
Section
Mathematics; Mathematical Physics; Quantum Physics
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2022-03-22
Milestone dates
2021-08-24 (Submission v1); 2021-08-30 (Submission v2); 2021-09-15 (Submission v3); 2022-03-18 (Submission v4)
Publication history
 
 
   First posting date
22 Mar 2022
ProQuest document ID
2564692928
Document URL
https://www.proquest.com/working-papers/approximate-petz-recovery-geometry-density/docview/2564692928/se-2?accountid=208611
Full text outside of ProQuest
Copyright
© 2022. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2022-03-23
Database
ProQuest One Academic