Bell pair extraction using graph foliage techniques

Future quantum networks can facilitate communication of quantum information between various nodes. We are particularly interested in whether multiple pairs can communicate simultaneously across a network. Quantum networks can be represented with graph states, and producing communication links amounts to performing certain quantum operations on graph states. This problem can be formulated in a graph-theoretic sense with the (Bell) vertex-minor problem. We discuss the recently introduced foliage partition and provide a generalization. This generalization leads us to a useful result for approaching the vertex-minor problem. We apply this result to identify the exact solution for the Bell vertex-minor problem on line, tree, and ring graphs.

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Publication Details

Journal
Journal of Mathematical Physics
Published
2025-02-01
DOI
https://doi.org/10.1063/5.0206530
Citations
1
Primary Topic
Topological and Geometric Data Analysis
Type
article
Field-Weighted Citation Impact
1.50

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article

Bell pair extraction using graph foliage techniques

Derek Zhang
1 citations
Journal of Mathematical Physics
Topological and Geometric Data Analysis
1.50
article

Bell pair extraction using graph foliage techniques

Derek Zhang
article en
1 citations

Abstract

Future quantum networks can facilitate communication of quantum information between various nodes. We are particularly interested in whether multiple pairs can communicate simultaneously across a network. Quantum networks can be represented with graph states, and producing communication links amounts to performing certain quantum operations on graph states. This problem can be formulated in a graph-theoretic sense with the (Bell) vertex-minor problem. We discuss the recently introduced foliage partition and provide a generalization. This generalization leads us to a useful result for approaching the vertex-minor problem. We apply this result to identify the exact solution for the Bell vertex-minor problem on line, tree, and ring graphs.

Journal of Mathematical PhysicsVol. 66(2)
University of Maryland, College Park (US)
National Science Foundation
Openalex Percentile: Top 19%
Topological and Geometric Data Analysis
1.50
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