Emergence of chaotic cluster synchronization in heterogeneous networks
© 2023 Author(s). Published under an exclusive license by AIP Publishing..
Many real-world complex systems rely on cluster synchronization to function properly. A cluster of nodes exhibits synchronous behavior, while others behave erratically. Predicting the emergence of these clusters and understanding the mechanism behind their structure and variation in response to a parameter change is a daunting task in networks that lack symmetry. We unravel the mechanism for the emergence of cluster synchronization in heterogeneous random networks. We develop heterogeneous mean-field approximation together with a self-consistent theory to determine the onset and stability of the cluster. Our analysis shows that cluster synchronization occurs in a wide variety of heterogeneous networks, node dynamics, and coupling functions. The results could lead to a new understanding of the dynamical behavior of networks ranging from neural to social.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2023 |
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Erschienen: |
2023 |
Enthalten in: |
Zur Gesamtaufnahme - volume:33 |
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Enthalten in: |
Chaos (Woodbury, N.Y.) - 33(2023), 9 vom: 01. Sept. |
Sprache: |
Englisch |
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Beteiligte Personen: |
Corder, Rodrigo M [VerfasserIn] |
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Anmerkungen: |
Date Revised 13.09.2023 published: Print Citation Status PubMed-not-MEDLINE |
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doi: |
10.1063/5.0169628 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM362007810 |
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520 | |a Many real-world complex systems rely on cluster synchronization to function properly. A cluster of nodes exhibits synchronous behavior, while others behave erratically. Predicting the emergence of these clusters and understanding the mechanism behind their structure and variation in response to a parameter change is a daunting task in networks that lack symmetry. We unravel the mechanism for the emergence of cluster synchronization in heterogeneous random networks. We develop heterogeneous mean-field approximation together with a self-consistent theory to determine the onset and stability of the cluster. Our analysis shows that cluster synchronization occurs in a wide variety of heterogeneous networks, node dynamics, and coupling functions. The results could lead to a new understanding of the dynamical behavior of networks ranging from neural to social | ||
650 | 4 | |a Journal Article | |
700 | 1 | |a Bian, Zheng |e verfasserin |4 aut | |
700 | 1 | |a Pereira, Tiago |e verfasserin |4 aut | |
700 | 1 | |a Montalbán, Antonio |e verfasserin |4 aut | |
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