IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v323y2003icp487-503.html
   My bibliography  Save this article

A Bayesian analysis of Monte Carlo correlation times for the two-dimensional Ising model

Author

Listed:
  • Arjunwadkar, Mihir
  • Fasnacht, Marc
  • Kadane, Joseph B.
  • Swendsen, Robert H.

Abstract

We present a new Bayesian analysis of the high-accuracy data of Nightingale and Blöte for the correlation times of the two-dimensional Ising model to determine the value of the dynamical critical exponent. We demonstrate the crucial role played by the Nightingale/Blöte assumption that odd terms disappear in their expression for the correlation time as a function of the size of the system. We obtain differing results for the existence of logarithmic corrections and the value of the dynamical critical exponent, depending on whether or not that assumption is valid.

Suggested Citation

  • Arjunwadkar, Mihir & Fasnacht, Marc & Kadane, Joseph B. & Swendsen, Robert H., 2003. "A Bayesian analysis of Monte Carlo correlation times for the two-dimensional Ising model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 323(C), pages 487-503.
  • Handle: RePEc:eee:phsmap:v:323:y:2003:i:c:p:487-503
    DOI: 10.1016/S0378-4371(03)00007-4
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437103000074
    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)00007-4?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. Huang, Zhaodong & Chien, Steven & Zhu, Wei & Zheng, Pengjun, 2022. "Scheduling wheel inspection for sustainable urban rail transit operation: A Bayesian approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(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:323:y:2003:i:c:p:487-503. 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.