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Related papers: Universality for Random Tensors

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In a recent paper the author obtained optimal bounds for the strong Gaussian approximation of sums of independent $\R^d$-valued random vectors with finite exponential moments. The results may be considered as generalizations of well-known…

Probability · Mathematics 2007-05-23 A. Yu. Zaitsev

Consider a random matrix of the form $W_n = M_n + D_n$, where $M_n$ is a Wigner matrix and $D_n$ is a real deterministic diagonal matrix ($D_n$ is commonly referred to as an external source in the mathematical physics literature). We study…

Probability · Mathematics 2014-08-18 Sean O'Rourke , Van Vu

In a random unitary matrix model at large N, we study the properties of the expectation value of the character of the unitary matrix in the rank k symmetric tensor representation. We address the problem of whether the standard semiclassical…

High Energy Physics - Theory · Physics 2015-05-30 Joanna L. Karczmarek , Gordon W. Semenoff

Nourdin et al. [9] established the following universality result: if a sequence of off-diagonal homogeneous polynomial forms in i.i.d. standard normal random variables converges in distribution to a normal, then the convergence also holds…

Probability · Mathematics 2015-05-15 Shuyang Bai , Murad S. Taqqu

Gurau (2020) proposed a generalization of the trace of the matrix resolvent to tensors of higher order, and recent work has explored analogs of the Wigner semicircle and Marchenko-Pastur distributions from random matrix theory as well as…

Probability · Mathematics 2026-03-09 Maximilian Jerdee , Dmitriy Kunisky , Cristopher Moore

This paper is devoted to the Gaussian fluctuations and deviations of the traces of tridiagonal random matrix. Under quite general assumptions, we prove that the traces are approximately normal distributed. Multi-dimensional central limit…

Probability · Mathematics 2015-06-16 Deng Zhang

Consider $(X_{i}(t))$ solving a system of $N$ stochastic differential equations interacting through a random matrix $\mathbf J = (J_{ij})$ with independent (not necessarily identically distributed) random coefficients. We show that the…

Probability · Mathematics 2021-02-03 Amir Dembo , Reza Gheissari

We address the question of the asymptotic description of random tensors that are local-unitary invariant, that is, invariant by conjugation by tensor products of independent unitary matrices. We consider both the mixed case of a tensor with…

Mathematical Physics · Physics 2025-04-04 Benoit Collins , Razvan Gurau , Luca Lionni

We consider 1d random Hermitian $N\times N$ block band matrices consisting of $W\times W$ random Gaussian blocks (parametrized by $j,k \in\Lambda=[1,n]\cap \mathbb{Z}$, $N=nW$) with a fixed entry's variance…

Mathematical Physics · Physics 2019-10-09 Mariya Shcherbina , Tatyana Shcherbina

In this paper we calculate, in the large N limit, the eigenvalue density of an infinite product of random unitary matrices, each of them generated by a random hermitian matrix. This is equivalent to solving unitary diffusion generated by a…

Mathematical Physics · Physics 2009-11-10 Romuald A. Janik , Waldemar Wieczorek

We consider the local eigenvalue distribution of large self-adjoint $N\times N$ random matrices $\mathbf{H}=\mathbf{H}^*$ with centered independent entries. In contrast to previous works the matrix of variances $s_{ij} = \mathbb{E}\,…

Probability · Mathematics 2017-08-09 Oskari Ajanki , Laszlo Erdos , Torben Krüger

This paper is aimed at deriving the universality of the largest eigenvalue of a class of high-dimensional real or complex sample covariance matrices of the form $\mathcal{W}_N=\Sigma^{1/2}XX^*\Sigma ^{1/2}$. Here, $X=(x_{ij})_{M,N}$ is an…

Probability · Mathematics 2015-03-06 Zhigang Bao , Guangming Pan , Wang Zhou

We present a self-contained proof of a uniform bound on multi-point correlations of trigonometric functions of a class of Gaussian random fields. It corresponds to a special case of the general situation considered in [Hairer-Xu], but with…

Probability · Mathematics 2018-10-10 Weijun Xu

We analyze in full mathematical rigor the most general quartically perturbed invariant probability measure for a random tensor. Using a version of the Loop Vertex Expansion (which we call the mixed expansion) we show that the cumulants…

Mathematical Physics · Physics 2015-06-15 Razvan Gurau

Let A be an n by n random matrix with iid entries taken from the p-adic integers or Z/NZ. Then under mild non-degeneracy conditions the cokernel of A has a universal probability distribution. In particular, the p-part of an iid random…

Combinatorics · Mathematics 2013-07-08 Kenneth Maples

We consider a Gaussian rotationally invariant ensemble of random real totally symmetric tensors with independent normally distributed entries, and estimate the largest eigenvalue of a typical tensor in this ensemble by examining the rate of…

Mathematical Physics · Physics 2021-05-12 Oleg Evnin

We apply random matrix theory to complex networks. We show that nearest neighbor spacing distribution of the eigenvalues of the adjacency matrices of various model networks, namely scale-free, small-world and random networks follow…

Adaptation and Self-Organizing Systems · Physics 2016-09-08 Jayendra N. Bandyopadhyay , Sarika Jalan

We prove that for Gaussian random normal matrices the correlation function has universal behavior. Using the technique of orthogonal polynomials and identities similar to the Christoffel-Darboux formula, we find that in the limit, as the…

Mathematical Physics · Physics 2013-12-03 Roman Riser

Let $G, G_1,\dots,G_N$ be independent copies of a standard gaussian random vector in $\mathbb{R}^d$ and denote by $\Gamma = \sum_{i=1}^N \langle G_i,\cdot\rangle e_i$ the standard gaussian ensemble. We show that, for any set $A\subset…

Probability · Mathematics 2026-03-19 Daniel Bartl , Shahar Mendelson

One of the key problems in tensor completion is the number of uniformly random sample entries required for recovery guarantee. The main aim of this paper is to study $n_1 \times n_2 \times n_3$ third-order tensor completion based on…

Machine Learning · Statistics 2022-01-25 Guang-Jing Song , Michael K. Ng , Xiongjun Zhang