Interplay of degree correlations and cluster synchronization

Sarika Jalan, Anil Kumar, Alexey Zaikin, and Jürgen Kurths
Phys. Rev. E 94, 062202 – Published 1 December 2016

Abstract

We study the evolution of coupled chaotic dynamics on networks and investigate the role of degree-degree correlation in the networks' cluster synchronizability. We find that an increase in the disassortativity can lead to an increase or a decrease in the cluster synchronizability depending on the degree distribution and average connectivity of the network. Networks with heterogeneous degree distribution exhibit significant changes in cluster synchronizability as well as in the phenomena behind cluster synchronization as compared to those of homogeneous networks. Interestingly, cluster synchronizability of a network may be very different from global synchronizability due to the presence of the driven phenomenon behind the cluster formation. Furthermore, we show how degeneracy at the zero eigenvalues provides an understanding of the occurrence of the driven phenomenon behind the synchronization in disassortative networks. The results demonstrate the importance of degree-degree correlations in determining cluster synchronization behavior of complex networks and hence have potential applications in understanding and predicting dynamical behavior of complex systems ranging from brain to social systems.

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  • Received 16 May 2016
  • Revised 9 September 2016

DOI:https://doi.org/10.1103/PhysRevE.94.062202

©2016 American Physical Society

Physics Subject Headings (PhySH)

Nonlinear Dynamics

Authors & Affiliations

Sarika Jalan1,2,*, Anil Kumar1, Alexey Zaikin3,4, and Jürgen Kurths5

  • 1Complex Systems Lab, Discipline of Physics, Indian Institute of Technology Indore, Simrol, Indore 453552, India
  • 2Centre for Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Simrol, Indore 453552, India
  • 3Institute for Women's Health and Department of Mathematics, University College London, London WC1H 0AY, United Kingdom
  • 4Department of Applied Mathematics and Centre of Bioinformatics, Lobachevsky State University of Nizhni Novgorod, Nizhni Novgorod 603950, Russia
  • 5Potsdam Institute for Climate Impact Research, D-14412 Potsdam, Germany

  • *sarikajalan9@gmail.com

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Issue

Vol. 94, Iss. 6 — December 2016

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