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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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???ViewItemFull_lblCiteItemAs???: https://publications.pik-potsdam.de/pubman/item/item_22686 ???ViewItemFull_lblCiteItemVersionAs???: https://publications.pik-potsdam.de/pubman/item/item_22686_3
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Banerjee, T.1, ???ENUM_CREATORROLE_AUTHOR???
Biswas, D.1, ???ENUM_CREATORROLE_AUTHOR???
Ghosh, D.1, ???ENUM_CREATORROLE_AUTHOR???
Bandyopadhyay, B.1, ???ENUM_CREATORROLE_AUTHOR???
Kurths, Jürgen2, ???ENUM_CREATORROLE_AUTHOR???           
???ViewItemFull_lblAffiliations???:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 ???ViewItemFull_lblAbstract???: 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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 ???ViewItemFull_lblDates???: 2018
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 ???ViewItemFull_lblIdentifiers???: ???ENUM_IDENTIFIERTYPE_DOI???: 10.1103/PhysRevE.97.042218
???ENUM_IDENTIFIERTYPE_PIKDOMAIN???: Transdisciplinary Concepts & Methods - Research Domain IV
???ENUM_IDENTIFIERTYPE_EDOC???: 8232
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Complex Networks
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Extremes
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Nonlinear Dynamics
???ENUM_IDENTIFIERTYPE_ORGANISATIONALK???: RD4 - Complexity Science
???ENUM_IDENTIFIERTYPE_WORKINGGROUP???: Network- and machine-learning-based prediction of extreme events
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???ViewItemFull_lblSourceTitle???: Physical Review E
???ViewItemFull_lblSourceGenre???: ???ENUM_GENRE_JOURNAL???, SCI, Scopus, p3
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???ViewItemFull_lblPages???: ???lbl_noEntry??? ???ViewItemFull_lblSourceVolumeIssue???: 97 (4) ???ViewItemFull_lblSourceSequenceNo???: 042218 ???ViewItemFull_lblSourceStartEndPage???: ???lbl_noEntry??? ???ViewItemFull_lblSourceIdentifier???: ???ENUM_IDENTIFIERTYPE_CONE???: https://publications.pik-potsdam.de/cone/journals/resource/150218
???ENUM_IDENTIFIERTYPE_PUBLISHER???: American Physical Society (APS)