English

Clusterization and phase diagram of the bimodal Kuramoto model with bounded confidence

Adaptation and Self-Organizing Systems 2020-09-29 v2 Social and Information Networks Dynamical Systems

Abstract

Inspired by the Deffuant and Hegselmann-Krause models of opinion dynamics, we extend the Kuramoto model to account for confidence bounds, i.e., vanishing interactions between pairs of oscillators when their phases differ by more than a certain value. We focus on Kuramoto oscillators with peaked, bimodal distribution of natural frequencies. We show that, in this case, the fixed-points for the extended model are made of certain numbers of independent clusters of oscillators, depending on the length of the confidence bound -- the interaction range -- and the distance between the two peaks of the bimodal distribution of natural frequencies. This allows us to construct the phase diagram of attractive fixed-points for the bimodal Kuramoto model with bounded confidence and to analytically explain clusterization in dynamical systems with bounded confidence.

Keywords

Cite

@article{arxiv.2007.01214,
  title  = {Clusterization and phase diagram of the bimodal Kuramoto model with bounded confidence},
  author = {André Reggio and Robin Delabays and Philippe Jacquod},
  journal= {arXiv preprint arXiv:2007.01214},
  year   = {2020}
}

Comments

10 pages, 4 figures