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A class of xorshift random number generators (RNGs) are introduced by Marsaglia. We have proposed an algorithm which constructs a full period xorshift RNG from a given primitive polynomial. It is shown there is a weakness present in those…

Cryptography and Security · Computer Science 2017-08-08 Susil Kumar Bishoi , Surya Narayan Maharana

Marsaglia proposed recently xorshift generators as a class of very fast, good-quality pseudorandom number generators. Subsequent analysis by Panneton and L'Ecuyer has lowered the expectations raised by Marsaglia's paper, showing several…

Data Structures and Algorithms · Computer Science 2016-10-14 Sebastiano Vigna

xorshift* generators are a variant of Marsaglia's xorshift generators that eliminate linear artifacts typical of generators based on $\mathbf Z/2\mathbf Z$-linear operations using multiplication by a suitable constant. Shortly after…

Data Structures and Algorithms · Computer Science 2016-05-24 Sebastiano Vigna

Many Random Number Generators (RNG) are available nowadays; they are divided in two categories, hardware RNG, that provide "true" random numbers, and algorithmic RNG, that generate pseudo random numbers (PRNG). Both types usually generate…

Information Theory · Computer Science 2018-09-28 Andrea C. G. Mennucci

In this article, we propose a new counter-based implementation of John von Neumann's middle-square random number generator (RNG). Several rounds of squaring are applied to a counter to produce a random output. We discovered that four rounds…

Data Structures and Algorithms · Computer Science 2022-03-15 Bernard Widynski

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

Quantum Physics · Physics 2015-05-27 Mario Stipcevic

A novel Mathematical Random Number Generator (MRNG) is presented here. In this case, "mathematical" refers to the fact that to construct that generator it is not necessary to resort to a physical phenomenon, such as the thermal noise of an…

Numerical Analysis · Computer Science 2012-11-22 Osvaldo Skliar , Ricardo E. Monge , Sherry Gapper , Guillermo Oviedo

We introduce the Romu family of pseudo-random number generators (PRNGs) which combines the nonlinear operation of rotation with the linear operations of multiplication and (optionally) addition. Compared to conventional linear-only PRNGs,…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-02-27 Mark A. Overton

High quality random numbers are necessary in the modern world. Ranging from encryption keys in cyber security to models and simulations for scientific use: it's important that these random numbers are of high quality and quickly attainable.…

Cryptography and Security · Computer Science 2024-05-16 Dmitriy Beznosko , Keith Driscoll , Fernando Guadarrama , Steven Mai , Nikolas Thornton

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…

Computational Physics · Physics 2019-05-30 Frederick James , Lorenzo Moneta

L'Ecuyer & Simard's Big Crush statistical test suite has revealed statistical flaws in many popular random number generators including Marsaglia's Xorshift generators. Vigna recently proposed some 64-bit variations on the Xorshift scheme…

Data Structures and Algorithms · Computer Science 2019-01-08 Daniel Lemire , Melissa E. O'Neill

In this work it is shown how 128 bit SSE2 multimedia extension registers, present in Pentium IV class 32 bit processors, may be used to generate random numbers at several times greater speed then when regular general purpose registers are…

Computational Physics · Physics 2007-05-23 Borko D. Stosic

Pseudo-Random Numbers Generators (PRNGs) are algorithms produced to generate long sequences of statistically uncorrelated numbers, i.e. Pseudo-Random Numbers (PRNs). These numbers are widely employed in mid-level cryptography and in…

Cryptography and Security · Computer Science 2019-12-30 Luca Pasqualini , Maurizio Parton

We combine the design of two \emph{random number generators}, \emph{Mersenne Twister} and \emph{Xorgens}, to obtain a new class of generators with heavy-weight characteristic polynomials (exceeded only by the {\sc well} generators) and high…

Data Structures and Algorithms · Computer Science 2020-11-17 Marcel Van de Vel

Pulsars exhibit signals with precise inter-arrival times that are on the order of milliseconds to seconds, depending on the individual pulsar. There are subtle variations in the timing of pulsar signals. We show that these variations can…

Cryptography and Security · Computer Science 2025-04-24 Hayder Tirmazi

CPUs and operating systems are moving from 32 to 64 bits, and hence it is important to have good pseudorandom number generators designed to fully exploit these word lengths. However, existing 64-bit very long period generators based on…

Numerical Analysis · Mathematics 2019-01-25 Shin Harase , Takamitsu Kimoto

Conventional random number generators provide the speed but not necessarily the high quality output streams needed for large-scale stochastic simulations. Cryptographically-based generators, on the other hand, provide superior quality…

Numerical Analysis · Mathematics 2013-07-17 William K. Cochran , Michael T. Heath , Kyle W. McKiou

True random number generators (TRNGs) underpin modern cryptography, yet existing implementations face fundamental trade-offs between speed, scalability, and entropy quality. Here, we demonstrate that stochastic switching in the bistable…

In this paper, a new pseudo-random number generator (PRNG) based on chaotic iterations is proposed. This method also combines the digits of two XORshifts PRNGs. The statistical properties of this new generator are improved: the generated…

Cryptography and Security · Computer Science 2010-12-22 Christophe Guyeux , Qianxue Wang , Jacques M. Bahi

Random numbers are an essential resource to many applications, including cryptography and Monte Carlo simulations. Quantum random number generators (QRNGs) represent the ultimate source of randomness, as the numbers are obtained by sampling…

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