Issue |
EPL
Volume 107, Number 6, September 2014
|
|
---|---|---|
Article Number | 60006 | |
Number of page(s) | 6 | |
Section | General | |
DOI | https://doi.org/10.1209/0295-5075/107/60006 | |
Published online | 24 September 2014 |
Mean-field theory of assortative networks of phase oscillators
1 Department of Applied Mathematics, University of Colorado - Boulder, CO 80309, USA
2 Institute for Research in Electronics and Applied Physics, University of Maryland - College Park, MD 20742, USA
Received: 22 July 2014
Accepted: 3 September 2014
Employing the Kuramoto model as an illustrative example, we show how the use of the mean-field approximation can be applied to large networks of phase oscillators with assortativity. We then use the ansatz of Ott and Antonsen (Chaos, 19 (2008) 037113) to reduce the mean-field kinetic equations to a system of ordinary differential equations. The resulting formulation is illustrated by application to a network Kuramoto problem with degree assortativity and correlation between the node degrees and the natural oscillation frequencies. Good agreement is found between the solutions of the reduced set of ordinary differential equations obtained from our theory and full simulations of the system. These results highlight the ability of our method to capture all the phase transitions (bifurcations) and system attractors. One interesting result is that degree assortativity can induce transitions from a steady macroscopic state to a temporally oscillating macroscopic state through both (presumed) Hopf and SNIPER (saddle-node, infinite period) bifurcations. Possible use of these techniques to a broad class of phase oscillator network problems is discussed.
PACS: 05.45.-a – Nonlinear dynamics and chaos / 05.45.Xt – Synchronization; coupled oscillators / 64.60.aq – Networks
© EPLA, 2014
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.