IDEAS home Printed from https://ideas.repec.org/a/spr/pardea/v4y2023i1d10.1007_s42985-022-00219-7.html
   My bibliography  Save this article

On the rigorous derivation of hydrodynamics of the Kuramoto model for synchronization phenomena

Author

Listed:
  • Young-Pil Choi

    (Yonsei University)

Abstract

We study the rigorous derivation of hydrodynamics of the Kuramoto model for synchronization phenomena, introduced by Choi and Lee (Math Models Methods Appl Sci 30: 2175–2227, 2020), which is pressureless Euler equations with nonlocal interaction forces. We present two different ways of deriving that hydrodynamic model. We first discuss the asymptotic analysis for the inertial kinetic Kuramoto equation with a strong local frequency alignment force. We show that a weak solution to the kinetic equation converges to the classical solution of that hydrodynamic synchronization model under certain assumptions on the initial data. We also provide the derivation from the particle Kuramoto model with inertia as the number of oscillators goes to infinity in the mono-kinetic case. Our proofs are based on a modulated energy-type estimate combined with the bounded Lipschitz distance between local densities.

Suggested Citation

  • Young-Pil Choi, 2023. "On the rigorous derivation of hydrodynamics of the Kuramoto model for synchronization phenomena," Partial Differential Equations and Applications, Springer, vol. 4(1), pages 1-20, February.
  • Handle: RePEc:spr:pardea:v:4:y:2023:i:1:d:10.1007_s42985-022-00219-7
    DOI: 10.1007/s42985-022-00219-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s42985-022-00219-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s42985-022-00219-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Alessandro Pluchino & Vito Latora & Andrea Rapisarda, 2005. "Changing Opinions In A Changing World: A New Perspective In Sociophysics," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 515-531.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tlaie, A. & Ballesteros-Esteban, L.M. & Leyva, I. & Sendiña-Nadal, I., 2019. "Statistical complexity and connectivity relationship in cultured neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 284-290.
    2. Guzmán-Vargas, L. & Hernández-Pérez, R., 2006. "Small-world topology and memory effects on decision time in opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 372(2), pages 326-332.
    3. Biondo, A.E. & Pluchino, A. & Rapisarda, A., 2018. "Modeling surveys effects in political competitions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 714-726.
    4. Le Pira, Michela & Inturri, Giuseppe & Ignaccolo, Matteo & Pluchino, Alessandro & Rapisarda, Andrea, 2017. "Finding shared decisions in stakeholder networks: An agent-based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 277-287.
    5. Yao-feng Zhang & Hong-ye Duan & Zhi-lin Geng, 2017. "Evolutionary Mechanism of Frangibility in Social Consensus System Based on Negative Emotions Spread," Complexity, Hindawi, vol. 2017, pages 1-8, June.
    6. Huang, Changwei & Luo, Yijun & Han, Wenchen, 2023. "Cooperation and synchronization in evolutionary opinion changing rate games," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    7. Yaofeng Zhang & Renbin Xiao, 2015. "Modeling and Simulation of Polarization in Internet Group Opinions Based on Cellular Automata," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-15, August.
    8. Lacerda, Juliana C. & Freitas, Celso & Macau, Elbert E.N., 2022. "Elementary changes in topology and power transmission capacity can induce failures in power grids," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    9. Pawel Sobkowicz, 2009. "Modelling Opinion Formation with Physics Tools: Call for Closer Link with Reality," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-11.
    10. Xiao, Feng & Xie, Lingyun & Wei, Bo, 2022. "Explosive synchronization of weighted mobile oscillators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:pardea:v:4:y:2023:i:1:d:10.1007_s42985-022-00219-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.