Quick Navigation

Topics

Entanglement Theory Quantum Correlations

Doubly minimized Petz and sandwiched Renyi mutual information: Properties

arXiv
Authors: Laura Burri

Year

2024

Paper ID

66973

Status

Preprint

Abstract Read

~2 min

Abstract Words

131

Citations

N/A

Abstract

The doubly minimized Petz Renyi mutual information of order α is defined as the minimization of the Petz divergence of order α of a fixed bipartite quantum state relative to any product state. The doubly minimized sandwiched Renyi mutual information is defined analogously using the sandwiched divergence in place of the Petz divergence. In this work, we establish several properties of these two types of Renyi mutual information. In particular, for the Petz case, we prove additivity for αin [1/2,2]. For the sandwiched case, we establish a novel duality relation for αin \[2/3,infty\] via Sion's minimax theorem, and we subsequently use this duality relation to prove additivity for the same range of α. Previously, additivity for the sandwiched case was known only for αin \[1,infty\], but it had been conjectured to hold for αin \[1/2,infty\].

Why This Paper Matters

  • This paper contributes to the Entanglement Theory & Quantum Correlations research area in the Quantum Articles archive.
  • It adds a 2024 reference point for readers tracking recent quantum research.
  • The doubly minimized Petz Renyi mutual information of order α is defined as the minimization of the Petz divergence of order α of a fixed bipartite quantum state relative to...

Paper Tools

Become a member to use research tools

Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.

Show Paper arXiv Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

Local Citation Graph (Related-Paper Links)

Current Paper #66973

External citation index: OpenAlex citation signal

Community Reactions

Quick sentiment from readers on this paper.

Score: 0
Likes: 0 Dislikes: 0

Sign in to react to this paper.

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.