On the generation of high-quality random numbers by two-dimensional cellular automata

Marco Tomassini, Moshe Sipper, Mathieu Perrenoud

Research output: Contribution to journalArticlepeer-review

145 Scopus citations


Finding good random number generators (RNGs) is a hard problem that is of crucial import in several fields, ranging from large-scale statistical physics simulations to hardware self-test. In this paper, we employ the cellular programming evolutionary algorithm to automatically generate two-dimensional cellular automata (CA) RNGs. Applying an extensive suite of randomness tests to the evolved CAs, we demonstrate that they rapidly produce high-quality random-number sequences. Moreover, based on observations of the evolved CAs, we are able to handcraft even better RNGs, which not only outperform previously demonstrated high-quality RNGs, but can be potentially tailored to satisfy given hardware constraints.

Original languageEnglish
Pages (from-to)1146-1151
Number of pages6
JournalIEEE Transactions on Computers
Issue number10
StatePublished - 1 Oct 2000
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics


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