IDEAS home Printed from https://ideas.repec.org/a/bpj/mcmeap/v14y2008i3p269-279n2.html
   My bibliography  Save this article

Exploitation of sensitivity derivatives via randomized quasi-Monte Carlo methods

Author

Listed:
  • Cao Y.

    (Department of Mathematics and Statistics, Auburn University, AL 36830, USA. Email: caoy@scs.fsu.edu)

  • Chi H.

    (Department of Computer and Information Sciences, Florida A&M University, Tallahassee, FL 32307-5100, USA. Email: hongmei.chi@famu.edu)

  • Milton C.

    (Department of Mathematics, Florida A&M University, Tallahassee, FL 32307, USA.)

  • Zhao W.

    (School of Mathematics and System Sciences, Shandong University, Jinan, Shandong, 250100, China. Email: wdzhao@sdu.edu.cn)

Abstract

Monte Carlo methods are now widely used in solving various computational fluid dynamics systems. This paper presents an improved scrambled quasi-Monte Carlo method for solving fluid dynamics applications. In our parallel implementation we use an independent scrambled quasirandom sequence for each processor. We explore the use of both scrambled quasi-Monte Carlo and variance reduction methods to improve the accuracy for Monte Carlo schemes. We also present theoretical analyses and numerical experiments to validate our numerical algorithms.

Suggested Citation

  • Cao Y. & Chi H. & Milton C. & Zhao W., 2008. "Exploitation of sensitivity derivatives via randomized quasi-Monte Carlo methods," Monte Carlo Methods and Applications, De Gruyter, vol. 14(3), pages 269-279, January.
    • Handle: RePEc:bpj:mcmeap:v:14:y:2008:i:3:p:269-279:n:2
    DOI: 10.1515/MCMA.2008.011
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/MCMA.2008.011
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/MCMA.2008.011?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.

    More about this item

    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:bpj:mcmeap:v:14:y:2008:i:3:p:269-279:n:2. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.