Deutsch
 
Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT
  Identification of single- and double-well coherence–incoherence patterns by the binary distance matrix

dos Santos, V., Sales, M. R., Muni, S. S., Szezech, J. D., Batista, A. M., Yanchuk, S., Kurths, J. (2023): Identification of single- and double-well coherence–incoherence patterns by the binary distance matrix. - Communications in Nonlinear Science and Numerical Simulation, 125, 107390.
https://doi.org/10.1016/j.cnsns.2023.107390

Item is

Externe Referenzen

einblenden:

Urheber

einblenden:
ausblenden:
 Urheber:
dos Santos, Vagner1, Autor
Sales, Matheus Rolim1, Autor
Muni, Sishu Shankar1, Autor
Szezech, José Danilo1, Autor
Batista, Antonio Marcos1, Autor
Yanchuk, Serhiy2, Autor              
Kurths, Jürgen2, Autor              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

Inhalt

einblenden:
ausblenden:
Schlagwörter: -
 Zusammenfassung: The study of chimera states or, more generally, coherence–incoherence patterns has led to the development of several tools for their identification and characterization. In this work, we extend the eigenvalue decomposition method to distinguish between single-well (SW) and double-well (DW) patterns. By applying our method, we are able to identify the following four types of dynamical patterns in a ring of nonlocally coupled Chua circuits and nonlocally coupled cubic maps: SW cluster, SW coherence–incoherence pattern, DW cluster, and DW coherence–incoherence. In a ring-star network of Chua circuits, we investigate the influence of adding a central node on the spatio-temporal patterns. Our results show that increasing the coupling with the central node favors the occurrence of SW coherence–incoherence states. We observe that the boundaries of the attraction basins resemble fractal and riddled structures.

Details

einblenden:
ausblenden:
Sprache(n): eng - Englisch
 Datum: 2023-07-072023-10
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1016/j.cnsns.2023.107390
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
Model / method: Open Source Software
Working Group: Network- and machine-learning-based prediction of extreme events
 Art des Abschluß: -

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: Communications in Nonlinear Science and Numerical Simulation
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 125 Artikelnummer: 107390 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/201610061
Publisher: Elsevier