Further analysis on structure and spectral properties of symmetric graphs

TL;DR

This paper investigates the spectral properties of symmetric graphs, revealing conditions under which they are unfriendly, and explores implications for graph matching and controllability in multi-agent systems.

Contribution

It provides new insights into the spectral characteristics of symmetric graphs and their relation to graph structure and controllability.

Findings

Symmetric graphs often contain subgraphs with identical topology.

Distinct eigenvalues in adjacency matrices imply unfriendly spectral properties.

Examples include both synthetic and real-world graphs.

Abstract

Graph is an abstract representation commonly used to model networked systems and structure. In problems across various fields, including computer vision and pattern recognition, and neuroscience, graphs are often brought into comparison (a process is called \textit{graph matching}) or checked for symmetry. Friendliness property of the associated adjacency matrices, specified by their spectral properties, is important in deriving a convex relaxation of the (intractable) discrete graph matching problem. In this work, we study unfriendliness properties of symmetric graphs by studying its relation to the underlying graph structure. It is revealed that a symmetric graph has two or more subgraphs of the same topology, and are adjacent to the same set of vertices. We then show that if adjacency matrices of symmetric graphs have distinct eigenvalues then there exist eigenvectors orthogonal to the vector of all ones, making them unfriendly. Relation of graph symmetry to uncontrollability of multi-agent systems under agreement dynamics with one controlled node is revisited. Examples of both synthetic and real-world graphs are also given for illustrations.