Signed Quantum Graphs

Traditional Graphs, such as weighted graphs, or fuzzy graphs have static edge weights or membership values.These graphs have been widely used to model various complex systems, but they typically do not incorporate dynamicinteractions found in evolving systems like brain networks. Temporal graphs are data-based algorithmic time-dependentstructures. There is no such structure to represent the dynamic interactions of networks. Quantum graphs are structuredgraphs based on the dynamic behaviors of vertices and links. This study introduces Signed Quantum Graphs (SQGs) withtime-dependent signs that represent dynamical systems. The properties of SQGs have been investigated. Additionally,concepts and properties of triadic closure, balance, domination, and strength of a SQG have been studied. The area ofapplications in brain networks has been mentioned. We propose a dynamic signed graph framework, where edge signsevolve periodically using functions. Structural properties and convergence results are provided.

Publication Details

Journal
DiRROS repository (University of Maribor)
Published
2025-09-01
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
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article

Signed Quantum Graphs

DiRROS repository (University of Maribor)
Complex Network Analysis Techniques
article

Signed Quantum Graphs

article en

Abstract

Traditional Graphs, such as weighted graphs, or fuzzy graphs have static edge weights or membership values.These graphs have been widely used to model various complex systems, but they typically do not incorporate dynamicinteractions found in evolving systems like brain networks. Temporal graphs are data-based algorithmic time-dependentstructures. There is no such structure to represent the dynamic interactions of networks. Quantum graphs are structuredgraphs based on the dynamic behaviors of vertices and links. This study introduces Signed Quantum Graphs (SQGs) withtime-dependent signs that represent dynamical systems. The properties of SQGs have been investigated. Additionally,concepts and properties of triadic closure, balance, domination, and strength of a SQG have been studied. The area ofapplications in brain networks has been mentioned. We propose a dynamic signed graph framework, where edge signsevolve periodically using functions. Structural properties and convergence results are provided.

DiRROS repository (University of Maribor)
Openalex Percentile: Top 36%
Complex Network Analysis Techniques
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Signed Quantum Graphs · DiRROS repository (University of Maribor) (2025) | TGRS Research Map | TGRS