English

Speed of complex network synchronization

Disordered Systems and Neural Networks 2015-06-30 v2 Social and Information Networks Chaotic Dynamics Physics and Society

Abstract

Synchrony is one of the most common dynamical states emerging on networks. The speed of convergence towards synchrony provides a fundamental collective time scale for synchronizing systems. Here we study the asymptotic synchronization times for directed networks with topologies ranging from completely ordered, grid-like, to completely disordered, random, including intermediate, partially disordered topologies. We extend the approach of Master Stability Functions to quantify synchronization times. We find that the synchronization times strongly and systematically depend on the network topology. In particular, at fixed in-degree, stronger topological randomness induces faster synchronization, whereas at fixed path length, synchronization is slowest for intermediate randomness in the small-world regime. Randomly rewiring real-world neural, social and transport networks confirms this picture.

Keywords

Cite

@article{arxiv.1106.4337,
  title  = {Speed of complex network synchronization},
  author = {Carsten Grabow and Stefan Grosskinsky and Marc Timme},
  journal= {arXiv preprint arXiv:1106.4337},
  year   = {2015}
}

Comments

14 pages, 7 figures, accepted for publication in EPJB, epj style, v2: typos corrected

R2 v1 2026-06-21T18:25:46.203Z