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This paper is concerned with the asymptotic empirical eigenvalue distribution of a non linear random matrix ensemble. More precisely we consider $M= \frac{1}{m} YY^*$ with $Y=f(WX)$ where $W$ and $X$ are random rectangular matrices with…

Probability · Mathematics 2022-01-14 Lucas Benigni , Sandrine Péché

Let $M_n$ be a $n \times n$ Wigner or sample covariance random matrix, and let $\mu_1(M_n), \mu_2(M_n), ..., \mu_n(M_n)$ denote the unordered eigenvalues of $M_n$. We study the fluctuations of the partial linear eigenvalue statistics $$…

Probability · Mathematics 2015-08-06 Sean O'Rourke , Alexander Soshnikov

We study the probability distribution of the index ${\mathcal N}_+$, i.e., the number of positive eigenvalues of an $N\times N$ Gaussian random matrix. We show analytically that, for large $N$ and large $\mathcal{N}_+$ with the fraction…

Statistical Mechanics · Physics 2015-03-17 Satya N. Majumdar , Céline Nadal , Antonello Scardicchio , Pierpaolo Vivo

The second author had previously obtained explicit generating functions for moments of characteristic polynomials of permutation matrices (n points). In this paper, we generalize many aspects of this situation. We introduce random shifts of…

Probability · Mathematics 2009-11-23 Paul-Olivier Dehaye , Dirk Zeindler

Wright-Fisher diffusions and their dual ancestral graphs occupy a central role in the study of allele frequency change and genealogical structure, and they provide expressions, explicit in some special cases but generally implicit, for the…

Probability · Mathematics 2025-03-25 Martina Favero , Paul A. Jenkins

Covariances and variances of linear statistics of a point process can be written as integrals over the truncated two-point correlation function. When the point process consists of the eigenvalues of a random matrix ensemble, there are often…

Mathematical Physics · Physics 2022-05-04 Peter J. Forrester

We present a comprehensive extension of the latent position network model known as the random dot product graph to accommodate multiple graphs -- both undirected and directed -- which share a common subset of nodes, and propose a method for…

Machine Learning · Statistics 2021-01-26 Andrew Jones , Patrick Rubin-Delanchy

The distribution of the ratios of consecutive eigenvalue spacings of random matrices has emerged as an important tool to study spectral properties of many-body systems. This article numerically investigates the eigenvalue ratios…

Disordered Systems and Neural Networks · Physics 2022-07-13 Ankit Mishra , Tanu Raghav , Sarika Jalan

A version of ``preferential attachment'' random graphs, corresponding to linear ``weights'' with random ``edge additions,'' which generalizes some previously considered models, is studied. This graph model is embedded in a continuous-time…

Probability · Mathematics 2007-05-23 K. B. Athreya , A. P. Ghosh , S. Sethuraman

We introduce a powerful analytic method to study the statistics of the number $\mathcal{N}_{\textbf{A}}(\gamma)$ of eigenvalues inside any contour $\gamma \in \mathbb{C}$ for infinitely large non-Hermitian random matrices ${\textbf A}$. Our…

Disordered Systems and Neural Networks · Physics 2021-06-09 Antonio Tonatiúh Ramos Sánchez , Edgar Guzmán-González , Isaac Pérez Castillo , Fernando L. Metz

Consider a deterministic self-adjoint matrix X_n with spectral measure converging to a compactly supported probability measure, the largest and smallest eigenvalues converging to the edges of the limiting measure. We perturb this matrix by…

Probability · Mathematics 2011-09-05 Florent Benaych-Georges , Alice Guionnet , Mylène Maïda

We introduce a large class of random Young diagrams which can be regarded as a natural one-parameter deformation of some classical Young diagram ensembles; a deformation which is related to Jack polynomials and Jack characters. We show that…

Probability · Mathematics 2022-12-12 Maciej Dołęga , Piotr Śniady

We prove Gaussian fluctuation for pair counting statistics of the form $ \sum_{1\leq i\neq j\leq N} f(\theta_i-\theta_j)$ for the Circular Unitary Ensemble (CUE) of random matrices in the case of a slowly growing variance in the limit of…

Probability · Mathematics 2021-02-03 Ander Aguirre , Alexander Soshnikov

Let $G=(V,E)$ be a $d$-regular graph on $n$ vertices and let $\mu_0$ be a probability measure on $V$. The act of moving to a randomly chosen neighbor leads to a sequence of probability measures supported on $V$ given by $\mu_{k+1} = A…

Combinatorics · Mathematics 2022-06-14 Stefan Steinerberger , Rekha R. Thomas

We consider the uniform random $d$-regular graph on $N$ vertices, with $d \in [N^\alpha, N^{2/3-\alpha}]$ for arbitrary $\alpha > 0$. We prove that in the bulk of the spectrum the local eigenvalue correlation functions and the distribution…

Probability · Mathematics 2019-08-21 Roland Bauerschmidt , Jiaoyang Huang , Antti Knowles , Horng-Tzer Yau

We further investigate properties of the Gaussian free field (GFF) on the metric graph associated to a discrete weighted graph (where the edges of the latter are replaced by continuous line-segments of appropriate length) that has been…

Probability · Mathematics 2020-06-11 Titus Lupu , Wendelin Werner

Given an $n\times n$ symmetric matrix $W\in [0,1]^{[n]\times [n]}$, let $\mathcal{G}(n,W)$ be the random graph obtained by independently including each edge $jk$ with probability $W_{jk}$. Given a degree sequence ${\bf d}=(d_1,\ldots,…

Combinatorics · Mathematics 2024-12-11 Pu Gao , Yuval Ohapkin

Let $G$ be a dense graph with good expansion properties and not too close to being bipartite. Let $\boldsymbol d$ be a graphical degree sequence. Under very weak conditions, we find the number of subgraphs of $G$ with degree sequence…

Combinatorics · Mathematics 2025-08-27 Mikhail Isaev , Brendan D. McKay

We consider the fluctuations of the largest eigenvalue of sparse random matrices, the class of random matrices that includes the normalized adjacency matrices of the Erd\H{o}s-R\'enyi graph $G(N, p)$. We show that the fluctuations of the…

Probability · Mathematics 2025-07-28 Teodor Bucht , Kevin Schnelli , Yuanyuan Xu

In this paper, we consider a data matrix $X_N\in\mathbb{R}^{N\times p}$ where all the rows are i.i.d. samples in $\mathbb{R}^p$ of mean zero and covariance matrix $\Sigma\in\mathbb{R}^{p\times p}$. Here the population matrix $\Sigma$ is of…

Probability · Mathematics 2013-05-06 Dai Shi
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