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In this paper we discuss general tridiagonal matrix models which are natural extensions of the ones given by Dumitriu and Edelman. We prove here the convergence of the distribution of the eigenvalues and compute the limiting distributions…

Probability · Mathematics 2008-02-18 Ionel Popescu

In this paper we give a simple, short, and self-contained proof for a non-trivial upper bound on the probability that a random $\pm 1$ symmetric matrix is singular.

Probability · Mathematics 2020-06-16 Asaf Ferber

We consider the problem of reconstructing an infinite set of sparse, finite-dimensional vectors, that share a common sparsity pattern, from incomplete measurements. This is in contrast to the work [17], where the single vector signal can be…

Optimization and Control · Mathematics 2021-11-29 Nick Dexter , Hoang Tran , Clayton Webster

The scattering properties of randomly layered optical media with ${\cal PT}$-symmetric index of refraction are studied using the transfer-matrix method. We find that the transmitance decays exponentially as a function of the system size,…

Optics · Physics 2012-05-10 Samuel Kalish , Zin Lin , Tsampikos Kottos

In this paper, we derive a joint central limit theorem for random vector whose components are function of random sesquilinear forms. This result is a natural extension of the existing central limit theory on random quadratic forms. We also…

Probability · Mathematics 2014-11-06 Qinwen Wang , Zhonggen Su , Jianfeng Yao

Let $F_n$ be an $n$ by $n$ symmetric matrix whose entries are bounded by $n^{\gamma}$ for some $\gamma>0$. Consider a randomly perturbed matrix $M_n=F_n+X_n$, where $X_n$ is a random symmetric matrix whose upper diagonal entries $x_{ij}$…

Combinatorics · Mathematics 2011-03-18 Hoi H. Nguyen

Let $M_n$ be a class of symmetric sparse random matrices, with independent entries $M_{ij} = \delta_{ij} \xi_{ij}$ for $i \leq j$. $\delta_{ij}$ are i.i.d. Bernoulli random variables taking the value $1$ with probability $p \geq…

Probability · Mathematics 2018-02-20 Kyle Luh , Van Vu

We study the limiting spectral distribution of sample covariance matrices $XX^T$, where $X$ are $p\times n$ random matrices with correlated entries, for the cases $p/n\to y\in [0,\infty)$. If $y>0$, we obtain the Mar\v{c}enko-Pastur…

Probability · Mathematics 2019-10-29 Michael Fleermann , Johannes Heiny

We consider random Hermitian matrices with independent upper triangular entries. Wigner's semicircle law says that under certain additional assumptions, the empirical spectral distribution converges to the semicircle distribution. We…

Probability · Mathematics 2022-06-14 Calvin Wooyoung Chin

We study two spiked models of random matrices under general frameworks corresponding respectively to additive deformation of random symmetric matrices and multiplicative perturbation of random covariance matrices. In both cases, the…

Probability · Mathematics 2020-10-14 Nathan Noiry

This paper is a continuation of the previous one [Journal xx, xxxxx (2022)]. Here, we reformulate the same J-matrix theory by regularizing the inverse square singular potential. The objective is to restore rapid convergence of the…

Mathematical Physics · Physics 2022-08-25 Abdulaziz D. Alhaidari , Hocine Bahlouli , S. M. Al-Marzoug , Carlos P. Aparicio

In this paper we define distributions on moment spaces corresponding to measures on the real line with an unbounded support. We identify these distributions as limiting distributions of random moment vectors defined on compact moment spaces…

Probability · Mathematics 2012-11-14 Holger Dette , Jan Nagel

Conditional on the extended Riemann hypothesis, we show that with high probability, the characteristic polynomial of a random symmetric $\{\pm 1\}$-matrix is irreducible. This addresses a question raised by Eberhard in recent work. The main…

Probability · Mathematics 2021-06-09 Asaf Ferber , Vishesh Jain , Ashwin Sah , Mehtaab Sawhney

Consider a square matrix with independent and identically distributed entries of zero mean and unit variance. It is well known that if the entries have a finite fourth moment, then, in high dimension, with high probability, the spectral…

Combinatorics · Mathematics 2018-05-31 Charles Bordenave , Pietro Caputo , Djalil Chafai , Konstantin Tikhomirov

The limiting distribution of eigenvalues of N x N random matrices has many applications. One of the most studied ensembles are real symmetric matrices with independent entries iidrv; the limiting rescaled spectral measure (LRSM)…

Probability · Mathematics 2012-12-27 Olivia Beckwith , Victor Luo , Steven J. Miller , Karen Shen , Nicholas Triantafillou

We report broadband characterization of the propagation of light through a multiply scattering medium by means of its Multi-Spectral Transmission Matrix. Using a single spatial light modulator, our approach enables the full control of both…

This paper adapts the recently developed rigorous application of the supersymmetric transfer matrix approach for the 1d band matrices to the case of the orthogonal symmetry. We consider $N\times N$ block band matrices consisting of $W\times…

Mathematical Physics · Physics 2020-11-30 Tatyana Shcherbina

In this paper, we introduce a joint central limit theorem (CLT) for specific bilinear forms, encompassing the resolvent of the sample covariance matrix under an elliptical distribution. Through an exhaustive exploration of our theoretical…

Statistics Theory · Mathematics 2023-12-29 Yanqing Yin , Wang Zhou

We show that the spectral radius of an $N\times N$ random symmetric matrix with i.i.d. bounded centered but non-symmetrically distributed entries is bounded from above by $ 2 \*\sigma + o(N^{-6/11+\epsilon}), $ where $\sigma^2 $ is the…

Probability · Mathematics 2007-05-23 Sandrine Peche , Alexander Soshnikov

A new approach is developed within the first-order Born approximation to light scattering from a collection of particles with $\mathcal{L}$ types. Two $\mathcal{L}\times\mathcal{L}$ matrices called pair-potential matrix (PPM) and…

Optics · Physics 2023-07-19 Yi Ding