[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v654y2024ics0378437124006599.html
   My bibliography  Save this article

Block approximations for probabilistic mixtures of elementary cellular automata

Author

Listed:
  • Cirillo, Emilio N.M.
  • Lancia, Giacomo
  • Spitoni, Cristian
Abstract
Probabilistic Cellular Automata are a generalization of Cellular Automata. Despite their simple definition, they exhibit fascinating and complex behaviours. The stationary behaviour of these models changes when model parameters are varied, making the study of their phase diagrams particularly interesting. The block approximation method, also known in this context as the local structure approach, is a powerful tool for studying the main features of these diagrams, improving upon Mean Field results. This work considers systems with multiple stationary states, aiming to understand how their interactions give rise to the structure of the phase diagram. Additionally, it shows how a simple algorithmic implementation of the block approximation allows for the effective study of the phase diagram even in the presence of several absorbing states.

Suggested Citation

  • Cirillo, Emilio N.M. & Lancia, Giacomo & Spitoni, Cristian, 2024. "Block approximations for probabilistic mixtures of elementary cellular automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 654(C).
    • Handle: RePEc:eee:phsmap:v:654:y:2024:i:c:s0378437124006599
    DOI: 10.1016/j.physa.2024.130150
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124006599
    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.2024.130150?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.

    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:654:y:2024:i:c:s0378437124006599. 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.