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We study a generalization of the Langevin equation, that describes fluctuations, of commuting degrees of freedom, for scalar field theories with worldvolumes of arbitrary dimension, following Parisi and Sourlas and correspondingly…

High Energy Physics - Theory · Physics 2018-10-15 Stam Nicolis

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

For a general class of large non-Hermitian random block matrices $\mathbf{X}$ we prove that there are no eigenvalues away from a deterministic set with very high probability. This set is obtained from the Dyson equation of the Hermitization…

Probability · Mathematics 2018-02-27 Johannes Alt , Laszlo Erdos , Torben Krüger , Yuriy Nemish

Using large $N$ arguments, we propose a scheme for calculating the two-point eigenvector correlation function for non-normal random matrices in the large $N$ limit. The setting generalizes the quaternionic extension of free probability to…

Mathematical Physics · Physics 2018-07-03 Maciej A. Nowak , Wojciech Tarnowski

We prove the existence as well as regularity of a finite range decomposition for the resolvent $G_{\alpha} (x-y,m^2) = ((-\Delta)^{\alpha\over 2} + m^{2})^{-1} (x-y) $, for $0<\alpha<2$ and all real $m$, in the lattice ${\mathbf Z}^{d}$ as…

Mathematical Physics · Physics 2016-12-12 P. K. Mitter

We prove multi-dimensional central limit theorems for the spectral moments (of arbitrary degrees) associated with random matrices with real-valued i.i.d. entries, satisfying some appropriate moment conditions. Our techniques rely on a…

Probability · Mathematics 2009-09-30 Ivan Nourdin , Giovanni Peccati

We consider the spectral statistics of large random band matrices on mesoscopic energy scales. We show that the two-point correlation function of the local eigenvalue density exhibits a universal power law behaviour that differs from the…

Probability · Mathematics 2015-06-17 Laszlo Erdos , Antti Knowles

The goal of this article is to study how much the eigenvalues of large Hermitian random matrices deviate from certain deterministic locations -- or in other words, to investigate optimal rigidity estimates for the eigenvalues. We do this in…

Probability · Mathematics 2019-06-05 Tom Claeys , Benjamin Fahs , Gaultier Lambert , Christian Webb

We address the question of how the celebrated universality of local correlations for the real eigenvalues of Hermitian random matrices of size NxN can be extended to complex eigenvalues in the case of random matrices without symmetry.…

Mathematical Physics · Physics 2015-04-20 G. Akemann , M. J. Phillips

By applying the supersymmetric approach we rigorously prove smoothness of the averaged density of states for a three dimensional random band matrix ensemble, in the limit of infinite volume and fixed band width. We also prove that the…

Mathematical Physics · Physics 2009-11-07 M. Disertori , H. Pinson , T. Spencer

Let us consider i.i.d. random variables $\{a_k,b_k\}_{k \geq 1}$ defined on a common probability space $(\Omega, \mathcal F, \mathbb P)$, following a symmetric Rademacher distribution and the associated random trigonometric polynomials…

Probability · Mathematics 2021-11-25 Jürgen Angst , Guillaume Poly

We study the asymptotic distribution of level crossings for random matrix pencils A_n+\lambda B_n in several ensembles, including complex and real i.i.d. matrices and Gaussian/Hermitian settings. We derive a representation of the normalized…

Mathematical Physics · Physics 2026-04-29 B. Shapiro

We survey recent mathematical results about the spectrum of random band matrices. We start by exposing the Erd{\H o}s-Schlein-Yau dynamic approach, its application to Wigner matrices, and extension to other mean-field models. We then…

Probability · Mathematics 2018-08-31 Paul Bourgade

We discuss an application of the transfer operator approach to the analysis of the different spectral characteristics of 1d random band matrices (correlation functions of characteristic polynomials, density of states, spectral correlation…

Mathematical Physics · Physics 2019-05-22 Mariya Shcherbina , Tatyana Shcherbina

We study the eigenvectors of generalized Wigner matrices with subexponential entries and prove that they delocalize at the optimal rate with overwhelming probability. We also prove high probability delocalization bounds with sharp…

Probability · Mathematics 2021-09-10 Lucas Benigni , Patrick Lopatto

The power-law random banded matrix (PLRBM) is a paradigmatic ensemble to study the Anderson localization transition (AT). In $d$-dimension the PLRBM are random matrices with algebraic decaying off-diagonal elements $H_{\vec{n}\vec{m}}\sim…

Disordered Systems and Neural Networks · Physics 2023-12-01 Giuseppe De Tomasi , Ivan M. Khaymovich

We consider the spreading of the wave packet in the generalized Rosenzweig-Porter random matrix ensemble in the region of non-ergodic extended states $1<\gamma<2$. We show that despite non-trivial fractal dimensions $0 < D_{q}=2-\gamma<1$…

Disordered Systems and Neural Networks · Physics 2017-06-08 Mohsen Amini Abchuyeh

We study random one-Lipschitz integer functions $f$ on the vertices of a finite connected graph, sampled according to the weight $W(f) = \prod_{\langle v, w \rangle \in E} \mathbf{c}^{ \mathbb{I} \{ f(v) = f(w) \} }$ where $\mathbf{c} \geq…

Probability · Mathematics 2023-09-27 Alex M. Karrila

We present some applications of central limit theorems on mesoscopic scales for random matrices. When combined with the recent theory of "homogenization" for Dyson Brownian Motion, this yields the universality of quantities which depend on…

Probability · Mathematics 2019-11-28 Benjamin Landon , Philippe Sosoe

Randomized Hadamard Transforms (RHTs) have emerged as a computationally efficient alternative to the use of dense unstructured random matrices across a range of domains in computer science and machine learning. For several applications such…

Machine Learning · Computer Science 2022-03-04 Yeshwanth Cherapanamjeri , Jelani Nelson
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