6,844 research outputs found
Review of High-Quality Random Number Generators
This is a review of pseudorandom number generators (RNG's) of the highest
quality, suitable for use in the most demanding Monte Carlo calculations. All
the RNG's we recommend here are based on the Kolmogorov-Anosov theory of mixing
in classical mechanical systems, which guarantees under certain conditions and
in certain asymptotic limits, that points on the trajectories of these systems
can be used to produce random number sequences of exceptional quality. We
outline this theory of mixing and establish criteria for deciding which RNG's
are sufficiently good approximations to the ideal mathematical systems that
guarantee highest quality. The well-known RANLUX (at highest luxury level) and
its recent variant RANLUX++ are seen to meet our criteria, and some of the
proposed versions of MIXMAX can be modified easily to meet the same criteria.Comment: 21 pages, 4 figure
A Comparative Study of Some Pseudorandom Number Generators
We present results of an extensive test program of a group of pseudorandom
number generators which are commonly used in the applications of physics, in
particular in Monte Carlo simulations. The generators include public domain
programs, manufacturer installed routines and a random number sequence produced
from physical noise. We start by traditional statistical tests, followed by
detailed bit level and visual tests. The computational speed of various
algorithms is also scrutinized. Our results allow direct comparisons between
the properties of different generators, as well as an assessment of the
efficiency of the various test methods. This information provides the best
available criterion to choose the best possible generator for a given problem.
However, in light of recent problems reported with some of these generators, we
also discuss the importance of developing more refined physical tests to find
possible correlations not revealed by the present test methods.Comment: University of Helsinki preprint HU-TFT-93-22 (minor changes in Tables
2 and 7, and in the text, correspondingly
Periodic orbits of the ensemble of Sinai-Arnold cat maps and pseudorandom number generation
We propose methods for constructing high-quality pseudorandom number
generators (RNGs) based on an ensemble of hyperbolic automorphisms of the unit
two-dimensional torus (Sinai-Arnold map or cat map) while keeping a part of the
information hidden. The single cat map provides the random properties expected
from a good RNG and is hence an appropriate building block for an RNG, although
unnecessary correlations are always present in practice. We show that
introducing hidden variables and introducing rotation in the RNG output,
accompanied with the proper initialization, dramatically suppress these
correlations. We analyze the mechanisms of the single-cat-map correlations
analytically and show how to diminish them. We generalize the Percival-Vivaldi
theory in the case of the ensemble of maps, find the period of the proposed RNG
analytically, and also analyze its properties. We present efficient practical
realizations for the RNGs and check our predictions numerically. We also test
our RNGs using the known stringent batteries of statistical tests and find that
the statistical properties of our best generators are not worse than those of
other best modern generators.Comment: 18 pages, 3 figures, 9 table
A Portable High-Quality Random Number Generator for Lattice Field Theory Simulations
The theory underlying a proposed random number generator for numerical
simulations in elementary particle physics and statistical mechanics is
discussed. The generator is based on an algorithm introduced by Marsaglia and
Zaman, with an important added feature leading to demonstrably good statistical
properties. It can be implemented exactly on any computer complying with the
IEEE--754 standard for single precision floating point arithmetic.Comment: pages 0-19, ps-file 174404 bytes, preprint DESY 93-13
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