IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-642-18743-8_9.html
   My bibliography  Save this book chapter

Generalized Mersenne Prime Number and Its Application to Random Number Generation

In: Monte Carlo and Quasi-Monte Carlo Methods 2002

Author

Listed:
  • Lih-Yuan Deng

    (The University of Memphis, Department of Mathematical Sciences)

Abstract

Summary A Mersenne prime number is a prime number of the form 2k — 1. In this paper, we consider a Generalized Mersenne Prime (GMP) which is of the form R(k,p) = (p k -l)/(p - 1), where k,p and R(k,p) are prime numbers. For such a GMP, we then propose a much more efficient search algorithm for a special form of Multiple Recursive Generator (MRG) with the property of an extremely large period length and a high dimension of equidistribution. In particular, we find that (p k - l)/(p - 1) is a GMP, for k = 1511 and p = 2147427929. We then find a special form of MRG with order k = 1511 and modulus p = 2147427929 with the period length 1014100.5.Many other efficient and portable generators with various k ≤ 1511 are found and listed. Finally, for such a GMP and generator, we propose a simple and quick method of generating maximum period MRGs with the same order k. The readers are advised not to confuse GMP defined in this paper with other generalizations of the Mersenne Prime. For example, the term “Generalized Mersenne Number” (GMN) is used in Appendix 6.1 of FIPS-186-2, a publication by National Institute of Standards and Technology (NIST). In that document, GMN is a prime number that can be written as 2k ± 1 plus or minus a few terms of the form 2r.

Suggested Citation

  • Lih-Yuan Deng, 2004. "Generalized Mersenne Prime Number and Its Application to Random Number Generation," Springer Books, in: Harald Niederreiter (ed.), Monte Carlo and Quasi-Monte Carlo Methods 2002, pages 167-180, Springer.
  • Handle: RePEc:spr:sprchp:978-3-642-18743-8_9
    DOI: 10.1007/978-3-642-18743-8_9
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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:spr:sprchp:978-3-642-18743-8_9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.