X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/prng_gpu.git/blobdiff_plain/3abda4f59d76446238e6b891bc14e1ac7b44c34a..725505ba2683a3f4a5a00955d99b175d2a141d69:/reponse.tex diff --git a/reponse.tex b/reponse.tex index dbe927a..a0d3da6 100644 --- a/reponse.tex +++ b/reponse.tex @@ -47,7 +47,7 @@ Done. \bigskip \textit{There seems to have been no effort in showing how the new PRNG improves on a single (say) xorshift generator, considering the slowdown of calling 3 of them per iteration (cf. Listing 1). This could be done, if not with the mathematical rigor of chaos theory, then with simpler bit diffusion metrics, often used in cryptography to evaluate building blocks of ciphers.} -A large section (Section 5) has been added, using and extending some previous works. It explains with more details why topological chaos +A large section (Section 2 of the Annex document) has been provided, using and extending some previous works. It explains with more details why topological chaos is useful to pass statistical tests. This new section contains both qualitative explanations and quantitative (experimental) evaluations. Using several examples, this section illustrates that defective PRNGs are always improved, according to the NIST, DieHARD, and TestU01 batteries.