Optimal synchronization of directed complex networks

Abstract

We study optimal synchronization of networks of coupled phase oscillators. We extend previous theory for optimizing the synchronization properties of undirected networks to the important case of directed networks. We derive a generalized synchrony alignment function that encodes the interplay between the network structure and the oscillators' natural frequencies and serves as an objective measure for the network's degree of synchronization. Using the generalized synchrony alignment function, we show that a network's synchronization properties can be systematically optimized. This framework also allows us to study the properties of synchrony-optimized networks, and in particular, investigate the role of directed network properties such as nodal in- and out-degrees. For instance, we find that in optimally rewired networks, the heterogeneity of the in-degree distribution roughly matches the heterogeneity of the natural frequency distribution, but no such relationship emerges for out-degrees. We also observe that a network's synchronization properties are promoted by a strong correlation between the nodal in-degrees and the natural frequencies of oscillators, whereas the relationship between the nodal out-degrees and the natural frequencies has comparatively little effect. This result is supported by our theory, which indicates that synchronization is promoted by a strong alignment of the natural frequencies with the left singular vectors corresponding to the largest singular values of the Laplacian matrix.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 23, 2016
Source ID
10.1063/1.4954221

Entities

People

  • Dane Taylor
  • Jie Sun
  • Per Sebastian Skardal

Organizations

  • Army Research Office
  • Clarkson University
  • Foundation for the National Institutes of Health
  • Simons Foundation
  • Trinity College
  • University of North Carolina

Tags

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Control Systems Engineering.
  • Graph Algorithms and Convex Optimization.