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Related papers: Finite N Fluctuation Formulas for Random Matrices

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We study the fluctuations of certain random matrix products $\Pi_N=M_N\cdots M_2M_1$ of $\mathrm{SL}(2,\mathbb{R})$, describing localisation properties of the one-dimensional Dirac equation with random mass. In the continuum limit, i.e.…

Disordered Systems and Neural Networks · Physics 2014-10-02 Kabir Ramola , Christophe Texier

We study the global fluctuations for linear statistics of the form $\sum_{i=1}^n f(\lambda_i)$ as $n \rightarrow \infty$, for $C^1$ functions $f$, and $\lambda_1, ..., \lambda_n$ being the eigenvalues of a (general) $\beta$-Jacobi ensemble,…

Probability · Mathematics 2012-10-04 Ioana Dumitriu , Elliot Paquette

One of the main concepts in quantum physics is a density matrix, which is a symmetric positive definite matrix of trace one. Finite probability distributions are a special case where the density matrix is restricted to be diagonal. Density…

Quantum Physics · Physics 2014-08-14 Manfred K. Warmuth , Dima Kuzmin

Let $P_n^1,\dots, P_n^d$ be $n\times n$ permutation matrices drawn independently and uniformly at random, and set $S_n^d:=\sum_{\ell=1}^d P_n^\ell$. We show that if $\log^{12}n/(\log \log n)^{4} \le d=O(n)$, then the empirical spectral…

Probability · Mathematics 2018-04-05 Anirban Basak , Nicholas Cook , Ofer Zeitouni

We establish large deviation formulas for linear statistics on the $N$ transmission eigenvalues $\{T_i\}$ of a chaotic cavity, in the framework of Random Matrix Theory. Given any linear statistics of interest $A=\sum_{i=1}^N a(T_i)$, the…

Mesoscale and Nanoscale Physics · Physics 2015-05-14 Pierpaolo Vivo , Satya N. Majumdar , Oriol Bohigas

Consider the product $X = X_{1}\cdots X_{m}$ of $m$ independent $n\times n$ iid random matrices. When $m$ is fixed and the dimension $n$ tends to infinity, we prove Gaussian limits for the centered linear spectral statistics of $X$ for…

Probability · Mathematics 2019-04-11 Natalie Coston , Sean O'Rourke

Consider $N\times N$ Hermitian or symmetric random matrices $H$ where the distribution of the $(i,j)$ matrix element is given by a probability measure $\nu_{ij}$ with a subexponential decay. Let $\sigma_{ij}^2$ be the variance for the…

Mathematical Physics · Physics 2011-09-27 Laszlo Erdos , Horng-Tzer Yau , Jun Yin

We compute the joint probability density function (jpdf) P_N(M, \tau_M) of the maximum M and its position \tau_M for N non-intersecting Brownian excursions, on the unit time interval, in the large N limit. For N \to \infty, this jpdf is…

Mathematical Physics · Physics 2015-06-04 Gregory Schehr

We give a generalization of the random matrix ensembles, including all lassical ensembles. Then we derive the joint density function of the generalized ensemble by one simple formula, which give a direct and unified way to compute the…

Mathematical Physics · Physics 2007-05-23 Jinpeng An , Zhengdong Wang , Kuihua Yan

We consider a class of sparse random matrices, which includes the adjacency matrix of Erd\H{o}s-R\'enyi graphs $\mathcal G(N,p)$ for $p \in [N^{\varepsilon-1},N^{-\varepsilon}]$. We identify the joint limiting distributions of the…

Probability · Mathematics 2020-03-13 Yukun He

Linear statistics of eigenvalues in many familiar classes of random matrices are known to obey gaussian central limit theorems. The proofs of such results are usually rather difficult, involving hard computations specific to the model in…

Probability · Mathematics 2007-11-25 Sourav Chatterjee

In this article we generalize the classical Edgeworth expansion for the probability density function (PDF) of sums of a finite number of symmetric independent identically distributed random variables with a finite variance to sums of…

Statistical Mechanics · Physics 2015-05-20 Netanel Hazut , Shlomi Medalion , David A. Kessler , Eli Barkai

We compute exact asymptotic of the statistical density of random matrices belonging to the Generalized Gaussian orthogonal, unitary and symplectic ensembles such that there no eigenvalues in the interval $[\sigma, +\infty[$. In particular,…

Probability · Mathematics 2015-01-27 Mohamed Bouali

In this paper, we compute the probability that an $N \times N$ matrix from the generalised Gaussian Unitary Ensemble (gGUE) is positive definite, extending a previous result of Dean and Majumdar \cite{DM}. For this purpose, we work out the…

Mathematical Physics · Physics 2017-05-25 Alfredo Deaño , Nick Simm

In this paper, we study the large $N$ behavior of the moment-generating function (MGF) of the linear statistics of $N\times N$ Hermitian matrices in the Gaussian unitary, symplectic, orthogonal ensembles (GUE, GSE, GOE) and Laguerre…

Mathematical Physics · Physics 2019-12-17 Chao Min , Yang Chen

In this paper, we analyze the random fluctuations in a one dimensional stochastic homogenization problem and prove a central limit result, i.e., the first order fluctuations can be described by a Gaussian process that solves an SPDE with…

Probability · Mathematics 2015-08-24 Yu Gu

We introduce the notion of a Young generating function for a probability measure on integer partitions. We use this object to characterize probability distributions over integer partitions satisfying a law of large numbers and those that…

Probability · Mathematics 2025-09-12 Gabriel Raposo

For normalized sums $Z_n$ of i.i.d. random variables, we explore necessary and sufficient conditions which guarantee the normal approximation with respect to the R\'enyi divergence of infinite order. In terms of densities $p_n$ of $Z_n$,…

Probability · Mathematics 2024-06-21 Sergey G. Bobkov , Friedrich Götze

Multivariate distributions are explored using the joint distributions of marginal sample quantiles. Limit theory for the mean of a function of order statistics is presented. The results include a multivariate central limit theorem and a…

Statistics Theory · Mathematics 2011-04-25 G. Jogesh Babu , Zhidong Bai , Kwok Pui Choi , Vasudevan Mangalam

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