IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v603y2022ics0378437122005386.html
   My bibliography  Save this article

Non-equilibrium kinetic Biswas–Chatterjee–Sen model on complex networks

Author

Listed:
  • Raquel, M.T.S.A.
  • Lima, F.W.S.
  • Alves, T.F.A.
  • Alves, G.A.
  • Macedo-Filho, A.
  • Plascak, J.A.

Abstract

The phase transition of a discrete version of the non-equilibrium Biswas–Chatterjee–Sen model, defined on Erdös–Rényi random graphs (ERRGs) and directed ERRGs random graphs (DERRGs), has been studied. The mutual interactions (or affinities) can be both positive and negative, depending on the noise parameter value. Through extensive Monte Carlo simulations and finite-size scaling analysis, the continuous phase transitions and the corresponding critical exponent ratios have been obtained for several values of the average connectivity z. The effective dimensionality of the system has been found to be Deff≈1.0 for all values of z, which is similar to the one obtained on Barabási–Albert networks. The present results show that kinetic models of discrete opinion dynamics belong to a different universality class as the corresponding equilibrium Ising and Potts, and non-equilibrium majority-vote models on the same ERRGs and DERRGs. It is also noticed that the kinetic model here studied on ERRGs and DERRGs is in different universality classes for connectivities z<20, while for z≥20 the critical exponents are the same for both random graphs.

Suggested Citation

  • Raquel, M.T.S.A. & Lima, F.W.S. & Alves, T.F.A. & Alves, G.A. & Macedo-Filho, A. & Plascak, J.A., 2022. "Non-equilibrium kinetic Biswas–Chatterjee–Sen model on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    • Handle: RePEc:eee:phsmap:v:603:y:2022:i:c:s0378437122005386
    DOI: 10.1016/j.physa.2022.127825
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437122005386
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2022.127825?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Oestereich, André L. & Crokidakis, Nuno & Cajueiro, Daniel O., 2022. "Impact of memory and bias in kinetic exchange opinion models on random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(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:eee:phsmap:v:603:y:2022:i:c:s0378437122005386. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.