Random numbers are a fundamental resource in science and engineering with important
applications in simulation and cryptography. The inherent randomness at the core of …

Random numbers are needed in many areas: cryptography, Monte Carlo computation and
simulation, industrial testing and labeling, hazard games, gambling, etc. Our assumption has …

In this article we present background, rationale, and a description of the Scalable Parallel
Random Number Generators (SPRNG) library. We begin by presenting some methods for …

Modeling obstructed diffusion is essential to the understanding of diffusion-mediated
processes in the crowded cellular environment. Simple Monte Carlo techniques for …

Correlations in the generalized feedback shift-register random-number generator are shown
to be greatly reduced when the number of feedback taps is increased from two to four (or …

Random number generators are used in many applications, from slot machines to
simulations of nuclear reactors. For many computational science applications, such as …

Monte Carlo computations are considered easy to parallelize. However, the results can be
adversely affected by defects in the parallel pseudorandom number generator used. A …

Random number generators (RNG) are an important resource in many areas: cryptography
(both quantum and classical), probabilistic computation (Monte Carlo methods), numerical …

Monte Carlo computations are commonly considered to be naturally parallel. However, one
needs to exercise care in parallelizing the underlying pseudorandom number generator …

A compact, fast, and accurate realization of a digital Gaussian variate generator (GVG)
based on the Box-Muller algorithm is presented. The proposed GVG has a faster Gaussian …