IDEAS home Printed from https://ideas.repec.org/a/spr/eurphb/v98y2025i10d10.1140_epjb_s10051-025-01060-8.html
   My bibliography  Save this article

Mean-field theory of the general-spin Ising model

Author

Listed:
  • Lourens Waldorp

    (University of Amsterdam)

  • Tuan Pham

    (University of Amsterdam)

  • Han L. J. Maas

    (University of Amsterdam)

Abstract

Motivated by modelling in physics and other disciplines, such as sociology and psychology, we derive the mean field of the general-spin Ising model from the variational principle of the Gibbs free energy. The general-spin Ising model has $$2k+1$$ 2 k + 1 spin values, generated by $$-(k-j)/k$$ - ( k - j ) / k , with $$j=0,1,2\ldots ,2k$$ j = 0 , 1 , 2 … , 2 k , such that for $$k=1$$ k = 1 we obtain $$-1,0,1$$ - 1 , 0 , 1 , for example; the Hamiltonian is identical to that of the standard Ising model. The general-spin Ising model exhibits spontaneous magnetisation, similar to the standard Ising model, but with the location translated by a factor depending on the number of categories $$2k+1$$ 2 k + 1 . We also show how the accuracy of the mean field depends on both the number of nodes and node degree, and that the hysteresis effect decreases and saturates with the number of categories $$2k+1$$ 2 k + 1 . Monte Carlo simulations confirm the theoretical results. Graphic abstract

Suggested Citation

  • Lourens Waldorp & Tuan Pham & Han L. J. Maas, 2025. "Mean-field theory of the general-spin Ising model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 98(10), pages 1-10, October.
  • Handle: RePEc:spr:eurphb:v:98:y:2025:i:10:d:10.1140_epjb_s10051-025-01060-8
    DOI: 10.1140/epjb/s10051-025-01060-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1140/epjb/s10051-025-01060-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1140/epjb/s10051-025-01060-8?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

    for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    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:eurphb:v:98:y:2025:i:10:d:10.1140_epjb_s10051-025-01060-8. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.