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The unfolding of detector effects is a key aspect of comparing experimental data with theoretical predictions. In recent years, different Machine-Learning methods have been developed to provide novel features, e.g. high dimensionality or a…

Data Analysis, Statistics and Probability · Physics 2024-12-17 Mathias Backes , Anja Butter , Monica Dunford , Bogdan Malaescu

We develop a method for the random sampling of (multimode) Gaussian states in terms of their covariance matrix, which we refer to as a random quantum covariance matrix (RQCM). We analyze the distribution of marginals and demonstrate that…

Quantum Physics · Physics 2024-08-19 Leevi Leppäjärvi , Ion Nechita , Ritabrata Sengupta

Diagrammatic techniques to compute perturbatively the spectral properties of Euclidean Random Matrices in the high-density regime are introduced and discussed in detail. Such techniques are developed in two alternative and very different…

Disordered Systems and Neural Networks · Physics 2011-08-31 T. S. Grigera , V. Martin-Mayor , G. Parisi , P. Urbani , P. Verrocchio

For a prime $p$ and a positive integer $s$ consider a homogeneous linear system over the ring $\mathbb{Z}_{p^s}$ (the ring of integers modulo $p^s$) described by an $n \times m$-matrix. The possible number of solutions to such a system is…

Number Theory · Mathematics 2025-07-08 Marcus Nilsson

New criteria are shown that certain combinations of finite unimodal polynomials are unimodal. %Given unimodal polynomials with explicit expressions and dependent recursion relations, we propose an approach to determine their modes. As…

Combinatorics · Mathematics 2014-01-23 Liangxia Wan

An M-sequence generated by a primitive polynomial has many interesting and desirable properties. A pseudo-random array is the two-dimensional generalization of an M-sequence. There are non-primitive polynomials all of whose non-zero…

Information Theory · Computer Science 2025-08-20 Simon Blackburn , Yeow Meng Chee , Tuvi Etzion , Huimin Lao

We study semiorders induced by points drawn from a uniform random distribution. Of particular interest in this paper are the probabilities of generating specific semiorders and the equivalence classes they produce. We present a method for…

Combinatorics · Mathematics 2025-09-25 Csaba Biró , Caroline E. Boone

We study two families of QBD processes with linear rates: (A) the multiserver retrial queue and its easier relative; and (B) the multiserver M/M/infinity Markov modulated queue. The linear rates imply that the stationary probabilities…

Quantum Algebra · Mathematics 2014-03-11 F. Avram , D. Matei , Y. Q. Zhao

This paper presents an algorithm to simulate Gaussian random vectors whose precision matrix can be expressed as a polynomial of a sparse matrix. This situation arises in particular when simulating Gaussian Markov random fields obtained by…

Methodology · Statistics 2020-04-07 Mike Pereira , Nicolas Desassis

A general explicit form for generating functions for approximating fractional derivatives is derived. To achieve this, an equivalent characterisation for consistency and order of approximations established on a general generating function…

Numerical Analysis · Mathematics 2021-05-31 W. A. Gunarathna , H. M. Nasir , W. B. Daundasekera

Conditional on the extended Riemann hypothesis, we show that with high probability, the characteristic polynomial of a random symmetric $\{\pm 1\}$-matrix is irreducible. This addresses a question raised by Eberhard in recent work. The main…

Probability · Mathematics 2021-06-09 Asaf Ferber , Vishesh Jain , Ashwin Sah , Mehtaab Sawhney

We investigate the space of $U(N)$ gauge-invariant operators in coupled matrix-vector systems at finite $N$, extending previous work on single matrix models. By using the Molien-Weyl formula, we compute the partition function and identify…

High Energy Physics - Theory · Physics 2025-06-30 Robert de Mello Koch , Animik Ghosh , Hendrik J. R. Van Zyl

The purpose of the present paper is to establish moderate deviation principles for a rather general class of random variables fulfilling certain bounds of the cumulants. We apply a celebrated lemma of the theory of large deviations…

Probability · Mathematics 2012-09-28 Hanna Doering , Peter Eichelsbacher

We study the uniform distribution of the polynomial sequence $\lambda(P)=(\lfloor P(k) \rfloor )_{k\geq 1}$ modulo integers, where $P(x)$ is a polynomial with real coefficients. In the nonlinear case, we show that $\lambda(P)$ is uniformly…

Number Theory · Mathematics 2018-12-18 Mohammad Javaheri

We study the ability of Transformer models to learn sequences generated by Permuted Congruential Generators (PCGs), a widely used family of pseudo-random number generators (PRNGs). PCGs introduce substantial additional difficulty over…

Machine Learning · Computer Science 2026-02-18 Tao Tao , Maissam Barkeshli

We analyze the structure of the periodic trajectories of the K-system generator of pseudorandom numbers on rational sublattice which coincides with the Galois field. The period of the trajectories increases as a function of lattice size and…

Computational Physics · Physics 2009-10-30 G. G. Athanasiu , E. G. Floratos , G. K. Savvidy

Parallel supercomputer-based Monte Carlo applications depend on pseudorandom number generators that produce independent pseudorandom streams across many separate processes. We propose a new scalable class of parallel pseudorandom number…

Computational Physics · Physics 2015-02-03 Paul D. Beale

We suggest fast algorithm for the matrix generator of pseudorandom numbers based on Kolmogorov-Anosov K systems which has been proposed earlier. This algorithm reduces $N^{2}$ operation of the matrix generator to $NlnN$ and essentially…

High Energy Physics - Lattice · Physics 2022-04-06 N. Z. Akopov , E. M. Madounts , A. B. Nersesian , G. K. Savvidy , W. Greiner

We investigate the statistical properties of $C=uvu^{-1}v^{-1}$, when $u$ and $v$ are independent random matrices, uniformly distributed with respect to the Haar measure of the groups $U(N)$ and $O(N)$. An exact formula is derived for the…

Mathematical Physics · Physics 2022-11-07 Pedro H. S. Palheta , Marcelo R. Barbosa , Marcel Novaes

We introduce a variational Bayesian neural network where the parameters are governed via a probability distribution on random matrices. Specifically, we employ a matrix variate Gaussian \cite{gupta1999matrix} parameter posterior…

Machine Learning · Statistics 2016-06-24 Christos Louizos , Max Welling