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A discrete Gelfand-Tsetlin pattern is a configuration of particles in Z^2. The particles are arranged in a finite number of consecutive rows, numbered from the bottom. There is one particle on the first row, two particles on the second row,…

Probability · Mathematics 2015-07-24 Erik Duse , Anthony Metcalfe

In this paper, we investigate the eigenvalue distribution of a class of kernel random matrices whose $(i,j)$-th entry is $f(X_i,X_j)$ where $f$ is a symmetric function belonging to the Paley-Wiener space $\mathcal{B}_c$ and $(X_i)_{1\leq i…

Statistics Theory · Mathematics 2025-07-22 Jebalia Mohamed , Ahmed Souabni

This paper aims to examine the characteristics of the posterior distribution of covariance/precision matrices in a "large $p$, large $n$" scenario, where $p$ represents the number of variables and $n$ is the sample size. Our analysis…

Statistics Theory · Mathematics 2026-02-02 Partha Sarkar , Kshitij Khare , Malay Ghosh , Matt P. Wand

We study an "inner-product kernel" random matrix model, whose empirical spectral distribution was shown by Xiuyuan Cheng and Amit Singer to converge to a deterministic measure in the large $n$ and $p$ limit. We provide an interpretation of…

Probability · Mathematics 2017-02-03 Zhou Fan , Andrea Montanari

We formulate a model for the average behaviour of ray class groups of real quadratic fields with respect to a fixed rational modulus, locally at a finite set $S$ of odd primes. To that end, we introduce Arakelov ray class groups of a number…

Number Theory · Mathematics 2025-09-25 Alex Bartel , Carlo Pagano

The scaled standard Wigner matrix (symmetric with mean zero, variance one i.i.d. entries), and its limiting eigenvalue distribution, namely the semi-circular distribution, has attracted much attention. The $2k$th moment of the limit equals…

Probability · Mathematics 2021-03-18 Arup Bose , Koushik Saha , Arusharka Sen , Priyanka Sen

We study asymptotic zero distribution of random Laurent polynomials whose support are contained in dilates of a fixed integral polytope $P$ as their degree grow. We consider a large class of probability distributions including the ones…

Complex Variables · Mathematics 2017-06-06 Turgay Bayraktar

We consider discrete orthogonal polynomial ensembles which are discrete analogues of the orthogonal polynomial ensembles in random matrix theory. These ensembles occur in certain problems in combinatorial probability and can be thought of…

Combinatorics · Mathematics 2007-05-23 Kurt Johansson

We consider Kasteleyn and Kasteleyn-Percus matrices, which arise in enumerating matchings of planar graphs, up to matrix operations on their rows and columns. If such a matrix is defined over a principal ideal domain, this is equivalent to…

Combinatorics · Mathematics 2007-05-23 Greg Kuperberg

Permanents of random matrices with independent and identically distributed (i.i.d.) entries have extensively studied in literature and convergence and concentration properties are known under varying assumptions on the distributions. In…

Probability · Mathematics 2021-12-13 Ghurumuruhan Ganesan

We consider unitary invariant random matrix ensembles which obey spectral statistics different from the Wigner-Dyson, including unitary ensembles with slowly (~(log x)^2) growing potentials and the finite-temperature fermi gas model. If the…

Disordered Systems and Neural Networks · Physics 2009-10-31 Shinsuke M. Nishigaki

We study random vectors of the form $(\operatorname {Tr}(A^{(1)}V),...,\operatorname {Tr}(A^{(r)}V))$, where $V$ is a uniformly distributed element of a matrix version of a classical compact symmetric space, and the $A^{(\nu)}$ are…

Probability · Mathematics 2016-08-16 Benoît Collins , Michael Stolz

Patterned random matrices such as the reverse circulant, the symmetric circulant, the Toeplitz and the Hankel matrices and their almost sure limiting spectral distribution (LSD), have attracted much attention. Under the assumption that the…

Probability · Mathematics 2022-03-14 Arup Bose , Koushik Saha , Priyanka Sen

As in real microlocal analysis, we prove a Schwartz kernel theorem for $p$-adic distributions. We extend this result for motivic distributions using Cluckers-Loeser's motivic integration. In both settings, we give also a relation between…

Number Theory · Mathematics 2026-04-01 Téofil Adamski

We consider n-by-n matrices whose (i, j)-th entry is f(X_i^T X_j), where X_1, ...,X_n are i.i.d. standard Gaussian random vectors in R^p, and f is a real-valued function. The eigenvalue distribution of these random kernel matrices is…

Probability · Mathematics 2012-03-26 Xiuyuan Cheng , Amit Singer

We provide a determination of the isotriplet quark distribution from available deep--inelastic data using neural networks. We give a general introduction to the neural network approach to parton distributions, which provides a solution to…

High Energy Physics - Phenomenology · Physics 2010-10-27 The NNPDF Collaboration , Luigi Del Debbio , Stefano Forte , Jose I. Latorre , Andrea Piccione , Joan Rojo

We consider the roots of uniformly chosen complex and real reciprocal polynomials of degree $N$ whose Mahler measure is bounded by a constant. After a change of variables this reduces to a generalization of Ginibre's complex and real…

Classical Analysis and ODEs · Mathematics 2019-12-02 Christopher D. Sinclair , Maxim L. Yattselev

A standard Gelfand-Tsetlin pattern of depth $n$ is a configuration of particles in $\{1,...,n\} \times \R$. For each $r \in \{1,...,n\}$, $\{r\} \times \R$ is referred to as the $r^\text{th}$ level of the pattern. A standard Gelfand-Tsetlin…

Probability · Mathematics 2011-11-15 Anthony Metcalfe

We examine a class of embeddings based on structured random matrices with orthogonal rows which can be applied in many machine learning applications including dimensionality reduction and kernel approximation. For both the…

Machine Learning · Statistics 2018-09-05 Krzysztof Choromanski , Mark Rowland , Adrian Weller

We consider the problem of clustering a sample of probability distributions from a random distribution on $\mathbb R^p$. Our proposed partitioning method makes use of a symmetric, positive-definite kernel $k$ and its associated reproducing…

Machine Learning · Statistics 2025-09-23 Amparo Baíllo , Jose R. Berrendero , Martín Sánchez-Signorini