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We consider the spectrum of additive, polynomially vanishing random perturbations of deterministic matrices, as follows. Let $M_N$ be a deterministic $N\times N$ matrix, and let $G_N$ be a complex Ginibre matrix. We consider the matrix…

Probability · Mathematics 2018-12-17 Anirban Basak , Elliot Paquette , Ofer Zeitouni

We study unitary random matrix ensembles of the form $Z_{n,N}^{-1} |\det M|^{2\alpha} e^{-N \Tr V(M)}dM$, where $\alpha>-1/2$ and $V$ is such that the limiting mean eigenvalue density for $n,N\to\infty$ and $n/N\to 1$ vanishes quadratically…

Mathematical Physics · Physics 2010-07-30 T. Claeys , A. B. J. Kuijlaars , M. Vanlessen

Suppose that $X_1,\...,X_n,\...$ are i.i.d. rotationally invariant $N$-by-$N$ matrices. Let $\Pi_n=X_n\... X_1$. It is known that $n^{-1}\log |\Pi_n|$ converges to a nonrandom limit. We prove that under certain additional assumptions on…

Probability · Mathematics 2010-10-20 Vladislav Kargin

This paper is about the relation of random matrix theory and the subordination phenomenon in complex analysis. We find that the resolvent of the sum of two random matrices is approximately subordinated to the resolvents of the original…

Probability · Mathematics 2015-06-22 V. Kargin

We study a trilinear singular integral form acting on two-dimensional functions and possessing invariances under arbitrary matrix dilations and linear modulations. One part of the motivation for introducing it lies in its large symmetry…

Classical Analysis and ODEs · Mathematics 2016-05-20 Philip Gressman , Danqing He , Vjekoslav Kovač , Brian Street , Christoph Thiele , Po-Lam Yung

We develop a perturbative approach to study the supersymmetric non-linear sigma model characterized by a generic coupling matrix in the strong coupling limit. The method allows us to calculate explicitly the moments of the eigenfunctions…

Disordered Systems and Neural Networks · Physics 2012-08-14 A. Ossipov

It is known that the joint limit distribution of independent Wigner matrices satisfies a very special asymptotic independence, called freeness. We study the joint convergence of a few other patterned matrices, providing a framework to…

Probability · Mathematics 2012-11-19 Arup Bose , Rajat Subhra Hazra , Koushik Saha

For fixed positive integers m, we consider the product of m independent n by n random matrices with iid entries as in the limit as n tends to infinity. Under suitable assumptions on the entries of each matrix, it is known that the limiting…

Probability · Mathematics 2017-11-21 Natalie Coston , Sean O'Rourke , Philip Matchett Wood

We study the joint distribution of the input sum and the output sum of a deterministic transducer. Here, the input of this finite-state machine is a uniformly distributed random sequence. We give a simple combinatorial characterization of…

Combinatorics · Mathematics 2015-04-14 Clemens Heuberger , Sara Kropf , Stephan Wagner

Algebraic statistics for binary random variables is concerned with highly structured algebraic varieties in the space of 2x2x...x2-tensors. We demonstrate the advantages of representing such varieties in the coordinate system of binary…

Combinatorics · Mathematics 2011-09-06 Bernd Sturmfels , Piotr Zwiernik

We continue the study of the Hermitian random matrix ensemble with external source $\frac{1}{Z_n} e^{-n \Tr({1/2}M^2 -AM)} dM$ where $A$ has two distinct eigenvalues $\pm a$ of equal multiplicity. This model exhibits a phase transition for…

Mathematical Physics · Physics 2010-07-29 Alexander I. Aptekarev , Pavel M. Bleher , Arno B. J. Kuijlaars

We give a new method for the evaluation of a class of integrals of rational symmetric functions in N pairs of variables {x_a, y_a}_{a=1,... N} arising in coupled matrix models, valid for a broad class of two-variable measures. The result is…

Mathematical Physics · Physics 2007-05-23 J. Harnad , A. Yu. Orlov

Let $U$ be a random unitary matrix drawn from the Hua-Pickrell distribution $\mu_{\mathrm{U}(n+m)}^{(\delta)}$ on the unitary group $\mathrm{U}(n+m)$. We show that the eigenvalues of the truncated unitary matrix $[U_{i,j}]_{1\leq i,j\leq…

Probability · Mathematics 2022-05-17 Zhaofeng Lin , Yanqi Qiu , Kai Wang

Suppose that A_1,\dots, A_N are independent random matrices whose atoms are iid copies of a random variable \xi of mean zero and variance one. It is known from the works of Newman et. al. in the late 80s that when \xi is gaussian then…

Probability · Mathematics 2016-07-13 Hoi H. Nguyen

We give simple criteria to identify the exponential order of magnitude of the absolute value of the determinant for wide classes of random matrix models, not requiring the assumption of invariance. These include Gaussian matrices with…

Probability · Mathematics 2023-02-22 Gérard Ben Arous , Paul Bourgade , Benjamin McKenna

In many interesting systems, the fermion determinant becomes complex and its phase plays a crucial role in the determination of the vacuum. For instance, in finite density QCD at low temperature and high density, exotic fermion condensates…

High Energy Physics - Lattice · Physics 2016-12-05 Yuta Ito , Jun Nishimura

In this paper, we explain the dependance of the fluctuations of the largest eigenvalues of a Deformed Wigner model with respect to the eigenvectors of the perturbation matrix. We exhibit quite general situations that will give rise to…

Probability · Mathematics 2011-09-16 Mireille Capitaine , Catherine Donati-Martin , Delphine Féral

Consider a smooth manifold with a smooth metric which changes bilinear type from Riemann to Lorentz on a hypersurface $\Sigma$ with radical tangent to $\Sigma$. Two natural bilinear symmetric forms appear there, and we use it to analyze the…

Differential Geometry · Mathematics 2007-05-23 E. Aguirre-Daban , J. Lafuente-Lopez

We show in this paper that after proper scalings, the characteristic polynomial of a random unitary matrix converges almost surely to a random analytic function whose zeros, which are on the real line, form a determinantal point process…

Probability · Mathematics 2018-08-07 Reda Chhaibi , Joseph Najnudel , Ashkan Nikeghbali

We consider sample covariance matrices $S_N=\frac{1}{p}\Sigma_N^{1/2}X_NX_N^* \Sigma_N^{1/2}$ where $X_N$ is a $N \times p$ real or complex matrix with i.i.d. entries with finite $12^{\rm th}$ moment and $\Sigma_N$ is a $N \times N$…

Probability · Mathematics 2009-11-17 Olivier Ledoit , Sandrine Péché
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