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  Effect of diluted connectivities on cluster synchronization of adaptively coupled oscillator networks

Vock, S., Berner, R., Yanchuk, S., Schöll, E. (2021): Effect of diluted connectivities on cluster synchronization of adaptively coupled oscillator networks. - Scientia Iranica D, 28, 3, 1669-1684.
https://doi.org/10.24200/sci.2021.57526.5284

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 Creators:
Vock, S.1, Author
Berner, R.1, Author
Yanchuk, S.1, Author
Schöll, Eckehard2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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Free keywords: Master stability; Phase oscillators; Adaptive networks; Complex networks; Cluster states; Desynchronization; Synaptic plasticity.
 Abstract: Synchronization in networks of oscillatory units is an emergent phenomenon that has been observed in various systems, from power grids to ensembles of nerve cells. Many real-world networks have adaptive properties, meaning that their connectivities change with time, depending on the dynamical state of the system. Networks of adaptively coupled oscillators show various synchronization phenomena, such as hierarchical multifrequency clusters, traveling waves, or chimera states. While these self-organized patterns have been previously studied on all-to-all coupled networks, this work extends the investigations towards more complex networks, analyzing the influence of random network topologies for various degrees of dilution of the connectivities. Using numerical and analytical approaches, we investigate the robustness of multicluster states on networks of adaptively coupled Kuramoto-Sakaguchi oscillators against the random dilution of the underlying network topology. We utilize the master stability approach for adaptive networks in order to highlight the interplay between adaptivity and topology. With this, we show the robustness of multifrequency cluster states to diluted connectivities.

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 Dates: 2021-07-012021-05
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.24200/sci.2021.57526.5284
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Model / method: Quantitative Methods
MDB-ID: No data to archive
 Degree: -

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Title: Scientia Iranica D
Source Genre: Journal, SCI, Scopus, oa
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Pages: - Volume / Issue: 28 (3) Sequence Number: - Start / End Page: 1669 - 1684 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/scientia-iranica-d
Publisher: Sharif University of Technology