4.7 Article

Blinking coupling enhances network synchronization

Journal

PHYSICAL REVIEW E
Volume 105, Issue 5, Pages -

Publisher

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.105.054304

Keywords

-

Funding

  1. Deutsche Forschungsgemeinschaft (DFG) [429685422, 440145547]
  2. Slovenian Research Agency [P1-0403, J1-2457]

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This paper studies the synchronization of a network with linear diffusive coupling that blinks between the variables periodically. The stability of the synchronous solution is shown to depend only on the averaged coupling and not on the instantaneous coupling. The effect of the blinking period on network synchronization is examined using the Hindmarsh-Rose model. The results demonstrate that decreasing the blinking period reduces the required coupling strength for synchrony and leads to enhanced synchronization compared to single-variable coupling.
This paper studies the synchronization of a network with linear diffusive coupling, which blinks between the variables periodically. The synchronization of the blinking network in the case of sufficiently fast blinking is analyzed by showing that the stability of the synchronous solution depends only on the averaged coupling and not on the instantaneous coupling. To illustrate the effect of the blinking period on the network synchronization, the Hindmarsh-Rose model is used as the dynamics of nodes. The synchronization is investigated by considering constant single-variable coupling, averaged coupling, and blinking coupling through a linear stability analysis. It is observed that by decreasing the blinking period, the required coupling strength for synchrony is reduced. It equals that of the averaged coupling model times the number of variables. However, in the averaged coupling, all variables participate in the coupling, while in the blinking model only one variable is coupled at any time. Therefore, the blinking coupling leads to an enhanced synchronization in comparison with the single-variable coupling. Numerical simulations of the average synchronization error of the network confirm the results obtained from the linear stability analysis.

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