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  Transition from homogeneous to inhomogeneous limit cycles: Effect of local filtering in coupled oscillators

Banerjee, T., Biswas, D., Ghosh, D., Bandyopadhyay, B., Kurths, J. (2018): Transition from homogeneous to inhomogeneous limit cycles: Effect of local filtering in coupled oscillators. - Physical Review E, 97, 4, 042218.
https://doi.org/10.1103/PhysRevE.97.042218

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Banerjee, T.1, Autor
Biswas, D.1, Autor
Ghosh, D.1, Autor
Bandyopadhyay, B.1, Autor
Kurths, Jürgen2, Autor              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: We report an interesting symmetry-breaking transition in coupled identical oscillators, namely, the continuous transition from homogeneous to inhomogeneous limit cycle oscillations. The observed transition is the oscillatory analog of the Turing-type symmetry-breaking transition from amplitude death (i.e., stable homogeneous steady state) to oscillation death (i.e., stable inhomogeneous steady state). This novel transition occurs in the parametric zone of occurrence of rhythmogenesis and oscillation death as a consequence of the presence of local filtering in the coupling path. We consider paradigmatic oscillators, such as Stuart-Landau and van der Pol oscillators, under mean-field coupling with low-pass or all-pass filtered self-feedback and through a rigorous bifurcation analysis we explore the genesis of this transition. Further, we experimentally demonstrate the observed transition, which establishes its robustness in the presence of parameter fluctuations and noise.

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 Datum: 2018
 Publikationsstatus: Final veröffentlicht
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 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1103/PhysRevE.97.042218
PIKDOMAIN: Transdisciplinary Concepts & Methods - Research Domain IV
eDoc: 8232
Research topic keyword: Complex Networks
Research topic keyword: Extremes
Research topic keyword: Nonlinear Dynamics
Organisational keyword: RD4 - Complexity Science
Working Group: Network- and machine-learning-based prediction of extreme events
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Titel: Physical Review E
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 97 (4) Artikelnummer: 042218 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/150218
Publisher: American Physical Society (APS)