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  Optimal time-varying coupling function can enhance synchronization in complex networks

Dayani, Z., Parastesh, F., Nazarimehr, F., Rajagopal, K., Jafari, S., Schöll, E., Kurths, J. (2023): Optimal time-varying coupling function can enhance synchronization in complex networks. - Chaos, 33, 3, 033139.
https://doi.org/10.1063/5.0142891

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 Creators:
Dayani, Zahra1, Author
Parastesh, Fatemeh1, Author
Nazarimehr, Fahimeh1, Author
Rajagopal, Karthikeyan1, Author
Jafari, Sajad1, Author
Schöll, Eckehard2, Author              
Kurths, Jürgen2, Author              
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1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: In this paper, we propose a time-varying coupling function that results in enhanced synchronization in complex networks of oscillators. The stability of synchronization can be analyzed by applying the master stability approach, which considers the largest Lyapunov exponent of the linearized variational equations as a function of the network eigenvalues as the master stability function. Here, it is assumed that the oscillators have diffusive single-variable coupling. All possible single-variable couplings are studied for each time interval, and the one with the smallest local Lyapunov exponent is selected. The obtained coupling function leads to a decrease in the critical coupling parameter, resulting in enhanced synchronization. Moreover, synchronization is achieved faster, and its robustness is increased. For illustration, the optimum coupling function is found for three networks of chaotic Rössler, Chen, and Chua systems, revealing enhanced synchronization.

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Language(s): eng - English
 Dates: 2023-03-222023-03
 Publication Status: Finally published
 Pages: 7
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1063/5.0142891
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
OATYPE: Green Open Access
 Degree: -

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Title: Chaos
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 33 (3) Sequence Number: 033139 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/180808
Publisher: American Institute of Physics (AIP)