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Machine learning (ML) frameworks rely heavily on pseudorandom number generators (PRNGs) for tasks such as data shuffling, weight initialization, dropout, and optimization. Yet, the statistical quality and reproducibility of these…

Other Computer Science · Computer Science 2025-07-08 Benjamin A. Antunes

We propose an approach to realize a quantum random number generator (QRNG) based on the photon number decision of weak laser pulses. This type of QRNG can generate true random numbers at a high speed and can be adjusted to zero bias…

Quantum Physics · Physics 2008-11-07 Wei Wei , J. W. Zhang , Tian Liu , Hong Guo

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

The future of high-performance computing is aligning itself towards the efficient use of highly parallel computing environments. One application where the use of massive parallelism comes instinctively is Monte Carlo simulations, where a…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-01-11 S. Hissoiny , P. Després , B. Ozell

We describe a high-speed physical random number generator based on a hybrid Boolean network with autonomous and clocked logic gates, realized on a reconfigurable chip. The autonomous logic gates are arranged in a bidirectional ring topology…

Chaotic Dynamics · Physics 2013-04-30 David P. Rosin , Damien Rontani , Daniel J. Gauthier

Random numbers are widely used for information security, cryptography, stochastic modeling, and quantum simulations. Key technical challenges for physical random number generation are speed and scalability. We demonstrate a method for…

We introduce a method for non-uniform random number generation based on sampling a physical process in a controlled environment. We demonstrate one proof-of-concept implementation of the method that reduces the error of Monte Carlo…

Other Computer Science · Computer Science 2020-04-24 James Timothy Meech , Phillip Stanley-Marbell

Randomness extraction is a key problem in cryptography and theoretical computer science. With the recent rapid development of quantum cryptography, quantum-proof randomness extraction has also been widely studied, addressing the security…

Quantum Physics · Physics 2024-01-15 Qian Li , Xiaoming Sun , Xingjian Zhang , Hongyi Zhou

It seems surprising that when applying widely used random number generators to generate one million random numbers on modern architectures, one obtains, on average, about 116 collisions. This article explains why, how to mathematically…

Computation · Statistics 2020-06-11 Marius Hofert

In many publications, authors showed that chaotic pseudo random number generators (PRNGs) may improve performance of the evolutionary algorithms. In this paper, we use two chaotic maps Gingerbread man and Tinkerbell as the chaotic PRNGs…

Neural and Evolutionary Computing · Computer Science 2014-12-22 Lenka Skanderova , Tomas Fabian

The pseudo-random number generators (PRNGs), sampling algorithms, and algorithms for generating random integers in some common statistical packages and programming languages are unnecessarily inaccurate, by an amount that may matter for…

Computation · Statistics 2018-10-29 Philip B. Stark , Kellie Ottoboni

We investigate solutions of backward stochastic differential equations (BSDE) with time delayed generators driven by Brownian motions and Poisson random measures, that constitute the two components of a Levy process. In this new type of…

Probability · Mathematics 2010-05-27 Łukasz Delong , Peter Imkeller

In this paper, we develop an information entropy based metric that represents the statistical quality of the generated binary sequence in Truly Random Number Generators (TRNG). The metric can be used for the design and optimization of the…

Information Theory · Computer Science 2015-03-20 Ahmad Beirami , Hamid Nejati , Yehia Massoud

This paper targets to search so-called \emph{good} generators by doing a brief survey over the generators developed in the history of pseudo-random number generators (PRNGs), verify their claims and rank them based on strong empirical tests…

Cryptography and Security · Computer Science 2025-08-19 Kamalika Bhattacharjee , Sukanta Das

With a growing interest in securing user data within the internet-of-things (IoT), embedded encryption has become of paramount importance, requiring light-weight high-quality Random Number Generators (RNGs). Emerging stochastic device…

Emerging Technologies · Computer Science 2026-03-03 Furqan Zahoor , Ibrahim A. Albulushi , Saleh Bunaiyan , Anupam Chattopadhyay , Hesham ElSawy , Feras Al-Dirini

Navigation of mobile robots within crowded environments is an essential task in various use cases, such as delivery, health care, or logistics. Deep Reinforcement Learning (DRL) emerged as an alternative method to replace overly…

Robotics · Computer Science 2021-09-27 Linh Kästner , Xinlin Zhao , Zhengcheng Shen , Jens Lambrecht

Non-deterministic random bits are needed in many scientific fields. Unfortunately today's computers are very limited in ability to produce them. We present here a method for extraction of non-deterministic random bits from random physics…

Computational Physics · Physics 2015-05-21 Mario Stipčević

Quantum random number generators (QRNGs) use the inherent unpredictability of quantum mechanics to generate true randomness, as opposed to classical random number generators. However, ensuring the authenticity of this randomness still…

This paper presents the physical concept and test results of sample data of the high-speed hardware true random number generator design based on typically used for High Energy Physics hardware. Main features of this concept are the high…

Instrumentation and Detectors · Physics 2016-11-18 D. Beznosko , T. Beremkulov , A. Duspayev , A. Iakovlev , A. Tailakov , M. Yessenov

We introduce new families of enhanced chaotic number generators in order to compute very fast long series of pseudorandom numbers. The key feature of these generators being the use of chaotic numbers themselves for sampling chaotic…

Dynamical Systems · Mathematics 2008-02-20 R. Lozi