{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T16:56:22Z","timestamp":1766076982910,"version":"3.48.0"},"reference-count":27,"publisher":"Walter de Gruyter GmbH","issue":"4","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The permuted congruential generators is a set of pseudorandom number generators released by Melissa E. O\u2019Neill 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\u2019s 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.<\/jats:p>","DOI":"10.1515\/mcma-2025-2017","type":"journal-article","created":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T22:15:20Z","timestamp":1759270520000},"page":"265-277","source":"Crossref","is-referenced-by-count":0,"title":["Moving permuted congruential generators beyond linear congruential generators"],"prefix":"10.1515","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-9422-350X","authenticated-orcid":false,"given":"Christopher","family":"Draper","sequence":"first","affiliation":[{"name":"Department of Computer Science , Florida State University , Tallahassee , FL 32304 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3058-4580","authenticated-orcid":false,"given":"Michael","family":"Mascagni","sequence":"additional","affiliation":[{"name":"Department of Computer Science , Florida State University , Tallahassee , FL 32304 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2025,10,1]]},"reference":[{"key":"2025121816431990628_j_mcma-2025-2017_ref_001","doi-asserted-by":"crossref","unstructured":"H.  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Das,\nA search for good pseudo-random number generators: Survey and empirical studies,\nComput. Sci. Rev. 45 (2018), Article ID 100471.","DOI":"10.1016\/j.cosrev.2022.100471"},{"key":"2025121816431990628_j_mcma-2025-2017_ref_005","doi-asserted-by":"crossref","unstructured":"C.  Bouillaguet, F.  Martinez and J.  Sauvage,\nPractical seed-recovery for the pcg pseudo-random number generator,\nIACR Trans. Symmetric Cryptol. 2020 (2020), 175\u2013196.","DOI":"10.46586\/tosc.v2020.i3.175-196"},{"key":"2025121816431990628_j_mcma-2025-2017_ref_006","doi-asserted-by":"crossref","unstructured":"H.  Chi, M.  Mascagni and T.  Warnock,\nOn the optimal halton sequence,\nMath. Comput. Simulation 70 (2005), no. 1, 9\u201321.","DOI":"10.1016\/j.matcom.2005.03.004"},{"key":"2025121816431990628_j_mcma-2025-2017_ref_007","doi-asserted-by":"crossref","unstructured":"C. R.  Harris, K. J.  Millman, S. J.  van der Walt, R.  Gommers, P.  Virtanen, D.  Cournapeau, E.  Wieser, J.  Taylor, S.  Berg, N. J.  Smith, R.  Kern, M.  Picus, S.  Hoyer, M. H.  van Kerkwijk, M.  Brett, A.  Haldane, J. F.  del R\u00edo, M.  Wiebe, P.  Peterson, P.  G\u00e9rard-Marchant, K.  Sheppard, T.  Reddy, W.  Weckesser, H.  Abbasi, C.  Gohlke and T. E.  Oliphant,\nArray programming with NumPy,\nNature 585 (2020), no. 7825, 357\u2013362.","DOI":"10.1038\/s41586-020-2649-2"},{"key":"2025121816431990628_j_mcma-2025-2017_ref_008","doi-asserted-by":"crossref","unstructured":"P.  L\u2019Ecuyer,\nRandom numbers for simulation,\nCommun. ACM 33 (1990), no. 10, 85\u201397.","DOI":"10.1145\/84537.84555"},{"key":"2025121816431990628_j_mcma-2025-2017_ref_009","doi-asserted-by":"crossref","unstructured":"P.  L\u2019Ecuyer,\nTables of linear congruential generators of different sizes and good lattice structure,\nMath. Comp. 68 (1999), 249\u2013260.","DOI":"10.1090\/S0025-5718-99-00996-5"},{"key":"2025121816431990628_j_mcma-2025-2017_ref_010","doi-asserted-by":"crossref","unstructured":"P.  L\u2019Ecuyer and R.  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