Spectral Measure of Robustness in Complex Networks
Jun Wu, Yue-Jin Tan, Hong-Zhong Deng, Yong Li, Bin Liu, Xin Lv

TL;DR
This paper introduces natural connectivity, a spectral measure for assessing the robustness of complex networks, which quantifies path redundancy and correlates with network resilience.
Contribution
It defines natural connectivity based on graph spectrum, providing a simple, physically meaningful robustness metric that outperforms existing measures in discriminating network resilience.
Findings
Natural connectivity increases with added edges.
It correlates well with network robustness.
It effectively discriminates network resilience.
Abstract
We introduce the concept of natural connectivity as a robustness measure of complex networks. The natural connectivity has a clear physical meaning and a simple mathematical formulation. It characterizes the redundancy of alternative paths by quantifying the weighted number of closed walks of all lengths. We show that the natural connectivity can be derived mathematically from the graph spectrum as an average eigenvalue and that it increases strictly monotonically with the addition of edges. We test the natural connectivity and compare it with other robustness measures within a scenario of edge elimination. We demonstrate that the natural connectivity has an acute discrimination which agrees with our intuition.
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Taxonomy
TopicsComplex Network Analysis Techniques · Functional Brain Connectivity Studies · Opinion Dynamics and Social Influence
