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Spectral Analysis of the MIXMAX Random Number Generators

Abstract : We study the lattice structure of random number generators of the MIXMAX family, a class of matrix linear congruential generators that produce a vector of random numbers at each step. These generators were initially proposed and justified as close approximations to certain ergodic dynamical systems having the Kolmogorov K-mixing property, which implies a chaotic (fast-mixing) behavior. But for a K-mixing system, the matrix must have irrational entries, whereas for the MIXMAX it has only integer entries. As a result, the MIXMAX has a lattice structure just like linear congruential and multiple recursive generators. Its matrix entries were also selected in a special way to allow a fast implementation and this has an impact on the lattice structure. We study this lattice structure for vectors of successive and non-successive output values in various dimensions. We show in particular that for coordinates at specific lags not too far apart, in three dimensions, all the nonzero points lie in only two hyperplanes. This is reminiscent of the behavior of lagged-Fibonacci and AWC/SWB generators. And even if we skip the output coordinates involved in this bad structure, other highly structured projections often remain, depending on the choice of parameters. We show that empirical statistical tests can easily detect this structure.
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Submitted on : Monday, December 10, 2018 - 2:23:23 PM
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  • HAL Id : hal-01634350, version 3


Pierre L'Ecuyer, Paul Wambergue, Erwan Bourceret. Spectral Analysis of the MIXMAX Random Number Generators. INFORMS Journal on Computing, Institute for Operations Research and the Management Sciences (INFORMS), 2018, pp.1-18. ⟨hal-01634350v3⟩



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