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Low-dimensional behavior of Kuramoto model with inertia in complex networks

Low-dimensional behavior of large systems of globally coupled oscillators has been intensively investigated since the introduction of the Ott-Antonsen ansatz. In this report, we generalize the Ott-Antonsen ansatz to second-order Kuramoto models in complex networks. With an additional inertia term, w...

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Detalles Bibliográficos
Autores principales: Ji, Peng, Peron, Thomas K. D. M., Rodrigues, Francisco A., Kurths, Jürgen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4007097/
https://www.ncbi.nlm.nih.gov/pubmed/24786680
http://dx.doi.org/10.1038/srep04783
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author Ji, Peng
Peron, Thomas K. D. M.
Rodrigues, Francisco A.
Kurths, Jürgen
author_facet Ji, Peng
Peron, Thomas K. D. M.
Rodrigues, Francisco A.
Kurths, Jürgen
author_sort Ji, Peng
collection PubMed
description Low-dimensional behavior of large systems of globally coupled oscillators has been intensively investigated since the introduction of the Ott-Antonsen ansatz. In this report, we generalize the Ott-Antonsen ansatz to second-order Kuramoto models in complex networks. With an additional inertia term, we find a low-dimensional behavior similar to the first-order Kuramoto model, derive a self-consistent equation and seek the time-dependent derivation of the order parameter. Numerical simulations are also conducted to verify our analytical results.
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spelling pubmed-40070972014-05-05 Low-dimensional behavior of Kuramoto model with inertia in complex networks Ji, Peng Peron, Thomas K. D. M. Rodrigues, Francisco A. Kurths, Jürgen Sci Rep Article Low-dimensional behavior of large systems of globally coupled oscillators has been intensively investigated since the introduction of the Ott-Antonsen ansatz. In this report, we generalize the Ott-Antonsen ansatz to second-order Kuramoto models in complex networks. With an additional inertia term, we find a low-dimensional behavior similar to the first-order Kuramoto model, derive a self-consistent equation and seek the time-dependent derivation of the order parameter. Numerical simulations are also conducted to verify our analytical results. Nature Publishing Group 2014-05-02 /pmc/articles/PMC4007097/ /pubmed/24786680 http://dx.doi.org/10.1038/srep04783 Text en Copyright © 2014, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by-nc-nd/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. The images in this article are included in the article's Creative Commons license, unless indicated otherwise in the image credit; if the image is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the image. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Article
Ji, Peng
Peron, Thomas K. D. M.
Rodrigues, Francisco A.
Kurths, Jürgen
Low-dimensional behavior of Kuramoto model with inertia in complex networks
title Low-dimensional behavior of Kuramoto model with inertia in complex networks
title_full Low-dimensional behavior of Kuramoto model with inertia in complex networks
title_fullStr Low-dimensional behavior of Kuramoto model with inertia in complex networks
title_full_unstemmed Low-dimensional behavior of Kuramoto model with inertia in complex networks
title_short Low-dimensional behavior of Kuramoto model with inertia in complex networks
title_sort low-dimensional behavior of kuramoto model with inertia in complex networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4007097/
https://www.ncbi.nlm.nih.gov/pubmed/24786680
http://dx.doi.org/10.1038/srep04783
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