Optimization of Bottlenecks in Quantum Graphs Guided by Fiedler Vector-Based Spectral Derivatives

Fuente: arXiv
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Hauptverfasser: Campbell, John TM, Dooley, John
Format: Preprint
Veröffentlicht: 2025
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author Campbell, John TM
Dooley, John
author_facet Campbell, John TM
Dooley, John
contents This paper discusses the relationships between the Fiedler vector, the Cheeger constant, and threshold behaviors in networks of quantum resource nodes represented as Quantum Directed Acyclic Graphs (QDAGs). We explore how these mathematical constructs can be applied to understand the dynamics of quantum information flow in QDAGs, especially in the context of routing problems with bottlenecks in graph signal processing, and how new eigenvalue-based rewiring techniques can optimize entanglement distribution between nodes in a QDAG.
format Preprint
id arxiv_https___arxiv_org_abs_2506_07875
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Optimization of Bottlenecks in Quantum Graphs Guided by Fiedler Vector-Based Spectral Derivatives
Campbell, John TM
Dooley, John
Quantum Algebra
Quantum Physics
This paper discusses the relationships between the Fiedler vector, the Cheeger constant, and threshold behaviors in networks of quantum resource nodes represented as Quantum Directed Acyclic Graphs (QDAGs). We explore how these mathematical constructs can be applied to understand the dynamics of quantum information flow in QDAGs, especially in the context of routing problems with bottlenecks in graph signal processing, and how new eigenvalue-based rewiring techniques can optimize entanglement distribution between nodes in a QDAG.
title Optimization of Bottlenecks in Quantum Graphs Guided by Fiedler Vector-Based Spectral Derivatives
topic Quantum Algebra
Quantum Physics
url https://arxiv.org/abs/2506.07875