IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v326y2003i1p25-36.html
   My bibliography  Save this article

Long time coarse grain leads to large deviation statistics and statistical mechanics

Author

Listed:
  • Shibata, Hiroshi

Abstract

The long time coarse grain of the observables often shows the large deviation statistics. A reason for this is that the long time coarse grained observables lose their correlations or memories. The establishment of the large deviation statistics leads to the statistical mechanics. In this paper, we show examples to prove that the probability distribution functions are well-defined for the nonlinear dynamical systems as a result of the coarse grained time being longer than the correlation time of the systems.

Suggested Citation

  • Shibata, Hiroshi, 2003. "Long time coarse grain leads to large deviation statistics and statistical mechanics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 326(1), pages 25-36.
    • Handle: RePEc:eee:phsmap:v:326:y:2003:i:1:p:25-36
    DOI: 10.1016/S0378-4371(03)00270-X
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037843710300270X
    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/S0378-4371(03)00270-X?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:326:y:2003:i:1:p:25-36. 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.