IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v240y2026icp473-493.html

Discretization of invariant measures for stochastic lattice dynamical systems

Author

Listed:
  • Li, Dingshi
  • Pu, Zhe

Abstract

This paper is devoted to studying the numerical approximation for stochastic reaction–diffusion lattice dynamical systems. The existence of numerical invariant measures for stochastic models with nonlinear noise is presented, where the backward Euler–Maruyama (BEM) method is applied for time discretization. Both the infinite dimensional discrete stochastic models and the related finite dimensional truncations are considered. A classical path convergence technique is applied to establish the convergence between invariant measures of numerical approximation and stochastic reaction–diffusion lattice model. By this procedure, the invariant measure of the stochastic reaction–diffusion lattice dynamical systems can be approximated by the numerical invariant measure of a finite dimensional truncated system as the discrete step size tends to zero.

Suggested Citation

  • Li, Dingshi & Pu, Zhe, 2026. "Discretization of invariant measures for stochastic lattice dynamical systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 240(C), pages 473-493.
    • Handle: RePEc:eee:matcom:v:240:y:2026:i:c:p:473-493
    DOI: 10.1016/j.matcom.2025.07.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475425002733
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.matcom.2025.07.008?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

    Keywords

    ;
    ;
    ;

    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:eee:matcom:v:240:y:2026:i:c:p:473-493. 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/mathematics-and-computers-in-simulation/ .

    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.