Literature DB >> 28952757

Stable Chimeras and Independently Synchronizable Clusters.

Young Sul Cho1,2, Takashi Nishikawa1,3, Adilson E Motter1,3.   

Abstract

Cluster synchronization is a phenomenon in which a network self-organizes into a pattern of synchronized sets. It has been shown that diverse patterns of stable cluster synchronization can be captured by symmetries of the network. Here, we establish a theoretical basis to divide an arbitrary pattern of symmetry clusters into independently synchronizable cluster sets, in which the synchronization stability of the individual clusters in each set is decoupled from that in all the other sets. Using this framework, we suggest a new approach to find permanently stable chimera states by capturing two or more symmetry clusters-at least one stable and one unstable-that compose the entire fully symmetric network.

Year:  2017        PMID: 28952757     DOI: 10.1103/PhysRevLett.119.084101

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  8 in total

1.  Antagonistic Phenomena in Network Dynamics.

Authors:  Adilson E Motter; Marc Timme
Journal:  Annu Rev Condens Matter Phys       Date:  2018-03       Impact factor: 16.109

2.  Matryoshka and disjoint cluster synchronization of networks.

Authors:  Amirhossein Nazerian; Shirin Panahi; Ian Leifer; David Phillips; Hernán A Makse; Francesco Sorrentino
Journal:  Chaos       Date:  2022-04       Impact factor: 3.642

Review 3.  A Brief Review of Chimera State in Empirical Brain Networks.

Authors:  Zhenhua Wang; Zonghua Liu
Journal:  Front Physiol       Date:  2020-06-30       Impact factor: 4.566

4.  Symmetries and cluster synchronization in multilayer networks.

Authors:  Fabio Della Rossa; Louis Pecora; Karen Blaha; Afroza Shirin; Isaac Klickstein; Francesco Sorrentino
Journal:  Nat Commun       Date:  2020-06-23       Impact factor: 14.919

5.  A two-layered brain network model and its chimera state.

Authors:  Ling Kang; Changhai Tian; Siyu Huo; Zonghua Liu
Journal:  Sci Rep       Date:  2019-10-07       Impact factor: 4.379

6.  Analyzing synchronized clusters in neuron networks.

Authors:  Matteo Lodi; Fabio Della Rossa; Francesco Sorrentino; Marco Storace
Journal:  Sci Rep       Date:  2020-10-01       Impact factor: 4.379

7.  Supermodal Decomposition of the Linear Swing Equation for Multilayer Networks.

Authors:  Kshitij Bhatta; Amirhossein Nazerian; Francesco Sorrentino
Journal:  IEEE Access       Date:  2022-07-04       Impact factor: 3.476

8.  One-way dependent clusters and stability of cluster synchronization in directed networks.

Authors:  Matteo Lodi; Francesco Sorrentino; Marco Storace
Journal:  Nat Commun       Date:  2021-07-01       Impact factor: 14.919

  8 in total

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