Bifurcations in the Kuramoto model on graphs

TL;DR

This paper investigates how different network topologies influence the onset and nature of synchronization in the Kuramoto model, revealing that structural properties like graph volume significantly affect synchronization thresholds and bifurcations.

Contribution

It identifies specific graph families where synchronization transitions occur at the same critical coupling, and uncovers new bifurcations in small-world networks, advancing understanding of topology's role in coupled oscillators.

Findings

Synchronization onset depends on simple graph properties like volume.

Power law graphs can achieve arbitrarily low synchronization thresholds.

Small-world graphs exhibit a new bifurcation to stable twisted states.

Abstract

In his classical work, Kuramoto analytically described the onset of synchronization in all-to-all coupled networks of phase oscillators with random intrinsic frequencies. Specifically, he identified a critical value of the coupling strength, at which the incoherent state loses stability and a gradual build-up of coherence begins. Recently, Kuramoto's scenario was shown to hold for a large class of coupled systems on convergent families of deterministic and random graphs. Guided by these results, in the present work, we study several model problems illustrating the link between network topology and synchronization in coupled dynamical systems. First, we identify several families of graphs, for which the transition to synchronization in the Kuramoto model starts at the same critical value of the coupling strength and proceeds in practically the same way. These examples include Erd\H{o}s-R\'enyi random graphs, Paley graphs, complete bipartite graphs, and certain stochastic block graphs. These examples illustrate that some rather simple structural properties such as the volume of the graph may determine the onset of synchronization, while finer structural features may affect only higher order statistics of the transition to synchronization. Further, we study the transition to synchronization in the Kuramoto model on power law and small-world random graphs. The former family of graphs endows the Kuramoto model with very good synchronizability: the synchronization threshold can be made arbitrarily low by varying the parameter of the power law degree distribution. For the Kuramoto model on small-world graphs, in addition to the transition to synchronization, we identify a new bifurcation leading to stable random twisted states. The examples analyzed in this work complement the results in [Chiba, Medvedev, The mean field analysis for the Kuramoto model on graphs (parts I and II), arxiv].