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We take a random matrix theory approach to random sketching and show an asymptotic first-order equivalence of the regularized sketched pseudoinverse of a positive semidefinite matrix to a certain evaluation of the resolvent of the same…

Numerical Analysis · Mathematics 2023-10-09 Daniel LeJeune , Pratik Patil , Hamid Javadi , Richard G. Baraniuk , Ryan J. Tibshirani

We deal with a random graph model evolving in discrete time steps by duplicating and deleting the edges of randomly chosen vertices. We prove the existence of an a.s. asymptotic degree distribution, with streched exponential decay; more…

Probability · Mathematics 2014-11-10 Ágnes Backhausz , Tamás F. Móri

The density matrix for the impenetrable Bose gas in Dirichlet and Neumann boundary conditions can be written in terms of $<\prod_{l=1}^n| \cos\phi_1-\cos\theta_l| |\cos\phi_2-\cos\theta_l|>$, where the average is with respect to the…

Mathematical Physics · Physics 2015-06-26 P. J. Forrester , N. E. Frankel , T. M. Garoni

We establish some conditions under which $\text{GL}(d,\mathbb{R})$-valued cocycles over a subshift of finite type, equipped with an equilibrium state, exhibit exponential asymptotics for the spectral radius. Specifically, we show that the…

Dynamical Systems · Mathematics 2026-03-26 Nicolas Martinez Ramos

The largest eigenvalue of random tensors is an important feature of systems involving disorder, equivalent to the ground state energy of glassy systems or to the injective norm of quantum states. For symmetric Gaussian random tensors of…

High Energy Physics - Theory · Physics 2024-12-16 Nicolas Delporte , Naoki Sasakura

One of the major themes of random matrix theory is that many asymptotic properties of traditionally studied distributions of random matrices are universal. We probe the edges of universality by studying the spectral properties of random…

Probability · Mathematics 2014-06-30 Tobias Johnson

In this article we focus on estimating the quadratic covariation of continuous semimartingales from discrete observations that take place at asynchronous observation times. The Hayashi-Yoshida estimator serves as synchronized realized…

Statistics Theory · Mathematics 2011-06-22 Markus Bibinger

In this work we study the spectral density of products of Wishart diluted random matrices of the form $X(1)\cdots X(M)(X(1)\cdots X(M))^T$ using the Edwards-Jones trick to map this problem into a system of interacting particles with random…

Disordered Systems and Neural Networks · Physics 2014-07-25 Thomas Dupic , Isaac Pérez Castillo

We consider two $n\times n$ non-Hermitian random matrices such that the $ij$th entry of one matrix is correlated with the $ij$th entry of the other matrix. However, the entries of any particular matrix are i.i.d. random variables. We study…

Probability · Mathematics 2025-04-08 Indrajit Jana , Sunita Rani

In this paper we show that the empirical eigenvalue distribution of any sample covariance matrix generated by independent copies of a stationary regular sequence has a limiting distribution depending only on the spectral density of the…

Probability · Mathematics 2014-08-12 Florence Merlevede , Magda Peligrad

We investigate the spectral statistics of the difference of two density matrices, each of which is independently obtained by partially tracing a random bipartite pure quantum state. We first show how a closed-form expression for the exact…

Mathematical Physics · Physics 2016-12-12 José Mejía , Camilo Zapata , Alonso Botero

We undertake a precise study of the asymptotic and non-asymptotic properties of stochastic approximation procedures with Polyak-Ruppert averaging for solving a linear system $\bar{A} \theta = \bar{b}$. When the matrix $\bar{A}$ is Hurwitz,…

Machine Learning · Statistics 2020-04-10 Wenlong Mou , Chris Junchi Li , Martin J. Wainwright , Peter L. Bartlett , Michael I. Jordan

We study the distributional properties of the linear discriminant function under the assumption of normality by comparing two groups with the same covariance matrix but different mean vectors. A stochastic representation for the…

Statistics Theory · Mathematics 2017-05-09 Taras Bodnar , Stepan Mazur , Edward Ngailo , Nestor Parolya

We provide optimal rates of convergence to the asymptotic distribution of the (properly scaled) degree of a fixed vertex in two preferential attachment random graph models. Our approach is to show that these distributions are unique fixed…

Probability · Mathematics 2013-03-15 Erol A. Peköz , Adrian Röllin , Nathan Ross

Wishart correlation matrices are the standard model for the statistical analysis of time series. The ensemble averaged eigenvalue density is of considerable practical and theoretical interest. For complex time series and correlation…

Mathematical Physics · Physics 2011-01-28 Christian Recher , Mario Kieburg , Thomas Guhr

We show that an independent family of uniformly distributed random permutation matrices is asymptotically *-free from an independent family of square complex Gaussian matrices and from an independent family of complex Wishart matrices, and…

Operator Algebras · Mathematics 2007-05-23 Mihail G. Neagu

Results on the spectral behavior of random matrices as the dimension increases are applied to the problem of detecting the number of sources impinging on an array of sensors. A common strategy to solve this problem is to estimate the…

Statistics Theory · Mathematics 2022-12-09 J. W. Silverstein , P. L. Combettes

It is shown that a Wishart matrix of standard complex normal random variables is asymptotically freely independent of an independent random matrix, under minimal conditions, in two different sense of asymptotic free independence.

Probability · Mathematics 2018-02-06 Arijit Chakrabarty , Sukrit Chakraborty , Rajat Subhra Hazra

We obtain explicit expressions for positive integer moments of the probability density of eigenvalues of the Jacobi and Laguerre random matrix ensembles, in the asymptotic regime of large dimension. These densities are closely related to…

Mathematical Physics · Physics 2011-11-23 Marcel Novaes

We study alternating minimization for matrix completion in the simplest possible setting: completing a rank-one matrix from a revealed subset of the entries. We bound the asymptotic convergence rate by the variational characterization of…

Machine Learning · Computer Science 2020-08-13 Rui Liu , Alex Olshevsky
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