Local assortativity affects the synchronizability of scale-free network
Mengbang Zou, Weisi Guo

TL;DR
This paper presents an analytical approach to estimate network eigenvalues affecting synchronizability, revealing how local assortativity and topology influence the ability of scale-free networks to synchronize.
Contribution
It introduces a novel perturbation theory-based method to accurately estimate extreme eigenvalues and links local assortativity to synchronizability in scale-free networks.
Findings
Smallest non-zero eigenvalue relates inversely to local assortativity.
Synchronizability can be tuned by rewiring low-degree nodes.
Method validated on scale-free networks with common dynamical models.
Abstract
Synchronization is critical for system level behaviour in physical, chemical, biological and social systems. Empirical evidence has shown that the network topology strongly impacts the synchronizablity of the system, and the analysis of their relationship remains an open challenge. We know that the eigenvalue distribution determines a network's synchronizability, but analytical expressions that connect network topology and all relevant eigenvalues (e.g., the extreme values) remain elusive. Here, we accurately determine its synchronizability by proposing an analytical method to estimate the extreme eigenvalues using perturbation theory. Our analytical method exposes the role global and local topology combine to influence synchronizability. We show that the smallest non-zero eigenvalue which determines synchronizability is estimated by the smallest degree augmented by the inverse degree…
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Taxonomy
TopicsGene Regulatory Network Analysis · Nonlinear Dynamics and Pattern Formation · Functional Brain Connectivity Studies
