Analytic relationship of relative synchronizability to network structure and motifs.

ABSTRACT: Synchronization phenomena on networks have attracted much attention in studies of neural, social, economic, and biological systems, yet we still lack a systematic understanding of how relative synchronizability relates to underlying network structure. Indeed, this question is of central importance to the key theme of how dynamics on networks relate to their structure more generally. We present an analytic technique to directly measure the relative synchronizability of noise-driven time-series processes on networks, in terms of the directed network structure. We consider both discrete-time autoregressive processes and continuous-time Ornstein-Uhlenbeck dynamics on networks, which can represent linearizations of nonlinear systems. Our technique builds on computation of the network covariance

SUBMITTER: Lizier JT 

PROVIDER: S-EPMC10500263 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature