Critical Coupling and Synchronized Clusters in Arbitrary Networks of Kuramoto Oscillators

abstract: The Kuramoto model is an archetypal model for studying synchronization in groups of nonidentical oscillators where oscillators are imbued with their own frequency and coupled with other oscillators though a network of interactions. As the coupling strength increases, there is a bifurcation to complete synchronization where all oscillators move with the same frequency and show a collective rhythm. Kuramoto-like dynamics are considered a relevant model for instabilities of the AC-power grid which operates in synchrony under standard conditions but exhibits, in a state of failure, segmentation of the grid into desynchronized clusters. In this dissertation the minimum coupling strength required to ensure total frequency synchronization in a Kuramoto system, called the critical coupling, is investigated. For coupling strength below the critical coupling, clusters of oscillators form where oscillators within a cluster are on average oscillating with the same long-term frequency. A unified order parameter based approach is developed to create approximations of the critical coupling. Some of the new approximations provide strict lower bounds for the critical coupling. In addition, these approximations allow for predictions of the partially synchronized clusters that emerge in the bifurcation from the synchronized state. Merging the order parameter approach with graph theoretical concepts leads to a characterization of this bifurcation as a weighted graph partitioning problem on an arbitrary networks which then leads to an optimization problem that can efficiently estimate the partially synchronized clusters. Numerical experiments on random Kuramoto systems show the high accuracy of these methods. An interpretation of the methods in the context of power systems is provided.Dissertation/ThesisDoctoral Dissertation Applied Mathematics 201

Synchronization in complex networks

Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analytical approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.Comment: Final version published in Physics Reports. More information available at http://synchronets.googlepages.com

The Kuramoto model: A simple paradigm for synchronization phenomena

Synchronization phenomena in large populations of interacting elements are the subject of intense research efforts in physical, biological, chemical, and social systems. A successful approach to the problem of synchronization consists of modeling each member of the population as a phase oscillator. In this review, synchronization is analyzed in one of the most representative models of coupled phase oscillators, the Kuramoto model. A rigorous mathematical treatment, specific numerical methods, and many variations and extensions of the original model that have appeared in the last few years are presented. Relevant applications of the model in different contexts are also included