IDEAS home Printed from https://ideas.repec.org/a/bpj/mcmeap/v31y2025i4p265-277n1002.html
   My bibliography  Save this article

Moving permuted congruential generators beyond linear congruential generators

Author

Listed:
  • Draper Christopher

    (Department of Computer Science, Florida State University, Tallahassee, FL 32304, USA)

  • Mascagni Michael

    (Department of Computer Science, Florida State University, Tallahassee, FL 32304, USA)

Abstract

The permuted congruential generators is a set of pseudorandom number generators released by Melissa E. O’Neill in 2014. The original technical report outlined several lightweight scrambling techniques designed for the linear congruential generator. Each scrambling technique offered some improvement to the quality of the linear congruential generator. However, the real strength of the scrambling techniques was that they could be combined into multiple overall stronger scramblers. The technical report concludes with the creation of the PCG library, a popular pseudorandom number generation library that implements several generators described in the technical report. Starting from the observation that the paper’s work was narrowly focused on implementing their scrambling techniques for specific linear congruential generators, we explore the permuted congruential generator scrambling techniques and their potential for being applied to other pseudorandom number generators by generalizing the scrambling techniques to work across different pseudorandom number generators.

Suggested Citation

  • Draper Christopher & Mascagni Michael, 2025. "Moving permuted congruential generators beyond linear congruential generators," Monte Carlo Methods and Applications, De Gruyter, vol. 31(4), pages 265-277.
    • Handle: RePEc:bpj:mcmeap:v:31:y:2025:i:4:p:265-277:n:1002
    DOI: 10.1515/mcma-2025-2017
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/mcma-2025-2017
    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-2025-2017?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:bpj:mcmeap:v:31:y:2025:i:4:p:265-277:n:1002. 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.degruyterbrill.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.