Extreme events in a complex network: interplay between degree distribution and repulsive interaction
Abstract
The role of topological heterogeneity in the origin of extreme events in a network is investigated here. The dynamics of the oscillators associated with the nodes are assumed to be identical and influenced by mean-field repulsive interactions. An interplay of topological heterogeneity and the repulsive interaction between the dynamical units of the network triggers extreme events in the nodes when each node succumbs to such events for discretely different ranges of repulsive coupling. A high degree node is vulnerable to weaker repulsive interactions, while a low degree node is susceptible to stronger interactions. As a result, the formation of extreme events changes position with increasing strength of repulsive interaction from high to low degree nodes. Extreme events at any node are identified with the appearance of occasional large-amplitude events (amplitude of the temporal dynamics) that are larger than a threshold height and rare in occurrence, which we confirm by estimating the probability distribution of all events. Extreme events appear at any oscillator near the boundary of transition from rotation to libration at a critical value of the repulsive coupling strength. To explore the phenomenon, a paradigmatic second-order phase model is used to represent the dynamics of the oscillator associated with each node. We make an annealed network approximation to reduce our original model and thereby confirm the dual role of the repulsive interaction and the degree of a node in the origin of extreme events in any oscillator.
Cite
@article{arxiv.2212.01345,
title = {Extreme events in a complex network: interplay between degree distribution and repulsive interaction},
author = {Arnob Ray and Timo Bröhl and Arindam Mishra and Subrata Ghosh and Dibakar Ghosh and Tomasz Kapitaniak and Syamal K. Dana and Chittaranjan Hens},
journal= {arXiv preprint arXiv:2212.01345},
year = {2022}
}
Comments
10 pages, 5 figures, Accepted for publication in Chaos: An Interdisciplinary Journal of Nonlinear Science