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DESCRIPTION:Pseudorandom number generators\n\nBiscuits et café à partir de 
 15 h\n	Linear pseudorandom number generators are very popular due to their 
 high speed\, to the ease with which generators with a sizable state space 
 can be created\, and to their provable theoretical properties. However\, t
 hey suffer from linear artefactsi\, which show as failures in linearity-re
 lated statistical tests such as the binary-rank and the linear-complexity 
 test. We describe three new contributions. First\, we introduce two new li
 near transformations that have been handcrafted to have good statistical p
 roperties and at the same time to be programmable very efficiently on supe
 rscalar processors\, or even directly in hardware. Then\, we describe a ne
 w test for Hamming-weight dependencies that is able to discover subtle\, p
 reviously unknown biases in existing generators. Finally\, we describe a n
 umber of scramblers\, that is\, nonlinear functions applied to the state a
 rray that reduce or delete the linear artefacts\, and propose combinations
  of linear transformations and scramblers that give extremely fast pseudor
 andom generators of high quality. A novelty in our approach is that we use
  ideas from the theory of filtered linear-feedback shift registers to prov
 e some properties of our scramblers\, rather than relying purely on heuris
 tics. In the end\, we provide extremely fast generators that use few hundr
 ed bits of memory\, have provable properties and pass very strong statisti
 cal tests.\n
DTSTART:20180517T193000Z
DTEND:20180517T203000Z
LOCATION:Room 3195\, CA\, Pav. André-Aisenstadt
SUMMARY:Sebastiano Vigna\, Dipartimento di Informatica\, Università degli S
 tudi di Milano
URL:/mathstat/channels/event/sebastiano-vigna-dipartim
 ento-di-informatica-universita-degli-studi-di-milano-287136
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