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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

We present an exact Bayesian inference method for inferring posterior distributions encoded by probabilistic programs featuring possibly unbounded loops. Our method is built on a denotational semantics represented by probability generating…

Programming Languages · Computer Science 2024-03-06 Lutz Klinkenberg , Christian Blumenthal , Mingshuai Chen , Darion Haase , Joost-Pieter Katoen

We obtain new bounds on complete rational exponential sums with sparse polynomials modulo a prime, under some mild conditions on the degrees of the monomials of such polynomials. These bounds, when they apply, give explicit versions of a…

Number Theory · Mathematics 2024-12-31 Subham Bhakta , Igor Shparlinski

We initiate the study of \emph{inverse} problems in approximate uniform generation, focusing on uniform generation of satisfying assignments of various types of Boolean functions. In such an inverse problem, the algorithm is given uniform…

Computational Complexity · Computer Science 2012-11-09 Anindya De , Ilias Diakonikolas , Rocco A. Servedio

Deep generative models (DGMs) for graphs achieve impressively high expressive power thanks to very efficient and scalable neural networks. However, these networks contain non-linearities that prevent analytical computation of many standard…

Machine Learning · Computer Science 2025-08-12 Martin Rektoris , Milan Papež , Václav Šmídl , Tomáš Pevný

In this work, we continue the line of research on the complexity of distributions (Viola, Journal of Computing 2012), and study samplers defined by low degree polynomials. An $n$-tuple $P = (P_1,\dots, P_n)$ of functions $P_i \colon…

Computational Complexity · Computer Science 2026-05-05 Mohammad Mahdi Khodabandeh , Igor Shinkar

Current techniques for formally verifying circuits implemented in Galois field (GF) arithmetic are limited to those with a known irreducible polynomial P(x). This paper presents a computer algebra based technique that extracts the…

Symbolic Computation · Computer Science 2016-12-15 Cunxi Yu , Daniel Holcomb , Maciej Ciesielski

Probabilistic dependency graphs (PDGs) are a flexible class of probabilistic graphical models, subsuming Bayesian Networks and Factor Graphs. They can also capture inconsistent beliefs, and provide a way of measuring the degree of this…

Data Structures and Algorithms · Computer Science 2023-11-10 Oliver E. Richardson , Joseph Y. Halpern , Christopher De Sa

This work addresses the problem of simulating Gaussian random fields that are continuously indexed over a class of metric graphs, termed graphs with Euclidean edges, being more general and flexible than linear networks. We introduce three…

Statistics Theory · Mathematics 2024-04-29 Alfredo Alegría , Xavier Emery , Tobia Filosi , Emilio Porcu

The aim of this paper is to present a new design for a pseudorandom number generator (PRNG) that is cryptographically secure, passes all of the usual statistical tests referenced in the literature and hence generates high quality random…

Cryptography and Security · Computer Science 2025-03-25 Juan Di Mauro , Eduardo Salazar , Hugo D. Scolnik

Goldreich suggested candidates of one-way functions and pseudorandom generators included in $\mathsf{NC}^0$. It is known that randomly generated Goldreich's generator using $(r-1)$-wise independent predicates with $n$ input variables and…

Cryptography and Security · Computer Science 2014-06-03 Ryuhei Mori , Takeshi Koshiba , Osamu Watanabe , Masaki Yamamoto

The generation of pseudo-random discrete probability distributions is of paramount importance for a wide range of stochastic simulations spanning from Monte Carlo methods to the random sampling of quantum states for investigations in…

Quantum Physics · Physics 2015-07-02 Jonas Maziero

Generalized Prolate Spheroidal Functions (GPSF) are the eigenfunctions of the truncated Fourier transform, restricted to D-dimensional balls in the spatial domain and frequency domain. Despite their useful properties in many applications,…

Numerical Analysis · Mathematics 2017-10-10 Roy R. Lederman

The advantages of quantum random number generators (QRNGs) over pseudo-random number generators (PRNGs) are normally attributed to the nature of quantum measurements. This is often seen as implying the superiority of the sequences of bits…

Quantum Physics · Physics 2019-02-04 Alastair A. Abbott , Cristian S. Calude , Michael J. Dinneen , Nan Huang

The gap probability generating function has as its coefficients the probability of an interval containing exactly $k$ eigenvalues. For scaled random matrices with orthogonal symmetry, and the interval at the hard or soft spectrum edge, the…

Mathematical Physics · Physics 2007-08-14 Peter J. Forrester

In the present paper we generate binary pseudorandom sequences using generalized polynomials. A generalized polynomial is a function in whose description we not only allow addition and product (as it is the case in usual polynomials) but…

Number Theory · Mathematics 2025-09-25 Manfred G. Madritsch , Robert F. Tichy

We study the arithmetic complexity of hitting set generators, which are pseudorandom objects used for derandomization of the polynomial identity testing problem. We give new explicit constructions of hitting set generators whose outputs are…

Computational Complexity · Computer Science 2025-08-19 Robert Andrews

Constructing a spanning tree of a graph is one of the most basic tasks in graph theory. We consider this problem in the setting of local algorithms: one wants to quickly determine whether a given edge $e$ is in a specific spanning tree,…

Data Structures and Algorithms · Computer Science 2021-04-28 Reut Levi , Dana Ron , Ronitt Rubinfeld

In this paper, we consider situations in which a given logical function is realized by a multithreshold threshold function. In such situations, constant functions can be easily obtained from multithreshold threshold functions, and…

Neural and Evolutionary Computing · Computer Science 2013-01-03 Yukihiro Kamada , Kiyonori Miyasaki

Sums of independent random variables form the basis of many fundamental theorems in probability theory and statistics, and therefore, are well understood. The related problem of characterizing products of independent random variables seems…

Probability · Mathematics 2018-05-29 Željka Stojanac , Daniel Suess , Martin Kliesch