Localization Phenomena in Large-Scale Networked Systems: Robustness and Fragility of Dynamics

TL;DR

This paper investigates eigenvector localization in large networked systems, revealing how such phenomena lead to fragility in dynamics and highlighting the importance of spectral analysis for understanding robustness.

Contribution

It introduces a spectral perturbation framework to explain how localized eigenvectors cause fragility in network dynamics, connecting graph structure complexity to stability issues.

Findings

Localized eigenvectors can cause low robustness margins.

Eigenvector localization is linked to specific structural features of networks.

Fragility in network dynamics can be analyzed through pseudo-spectrum methods.

Abstract

We study phenomena where some eigenvectors of a graph Laplacian are largely confined in small subsets of the graph. These localization phenomena are similar to those generally termed Anderson Localization in the Physics literature, and are related to the complexity of the structure of large graphs in still unexplored ways. Using spectral perturbation theory and pseudo-spectrum analysis, we explain how the presence of localized eigenvectors gives rise to fragilities (low robustness margins) to unmodeled node or link dynamics. Our analysis is demonstrated by examples of networks with relatively low complexity, but with features that appear to induce eigenvector localization. The implications of this newly-discovered fragility phenomenon are briefly discussed.