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This paper considers random matrices distributed according to Haar measure in different classical compact groups. Utilizing the determinantal point structures of their nontrivial eigenangles, with respect to the $L_1$-Wasserstein distance,…

Probability · Mathematics 2026-02-19 Mengchun Cai

We prove a local central limit theorem (LCLT) for the number of points $N(J)$ in a region $J$ in $\mathbb R^d$ specified by a determinantal point process with an Hermitian kernel. The only assumption is that the variance of $N(J)$ tends to…

Mathematical Physics · Physics 2015-06-18 Peter J. Forrester , Joel L. Lebowitz

We find the probability of two gaps of the form $(sc,sb)\cup (sa,+\infty)$, $c<b<a<0$, for large $s>0$, in the edge scaling limit of the Gaussian Unitary Ensemble of random matrices, including the multiplicative constant in the asymptotics.

Functional Analysis · Mathematics 2021-08-11 Igor Krasovsky , Theo-Harris Maroudas

A family of random matrix ensembles interpolating between the GUE and the Ginibre ensemble of $n\times n$ matrices with iid centered complex Gaussian entries is considered. The asymptotic spectral distribution in these models is uniform in…

Probability · Mathematics 2010-03-23 Martin Bender

For a pair of coupled rectangular random matrices we consider the squared singular values of their product, which form a determinantal point process. We show that the limiting mean distribution of these squared singular values is described…

Mathematical Physics · Physics 2020-06-24 Guilherme L. F. Silva , Lun Zhang

We introduce a family of discrete determinantal point processes related to orthogonal polynomials on the real line, with correlation kernels defined via spectral projections for the associated Jacobi matrices. For classical weights, we show…

Mathematical Physics · Physics 2019-08-12 Alexei Borodin , Grigori Olshanski

We establish sharp global rigidity upper bounds for universal determinantal point processes describing edge eigenvalues of random matrices. For this, we first obtain a general result which can be applied to general (not necessarily…

Mathematical Physics · Physics 2021-06-02 Christophe Charlier , Tom Claeys

In Random Matrix Theory the local correlations of the Laguerre and Jacobi Unitary Ensemble in the hard edge scaling limit can be described in terms of the Bessel kernel (containing a parameter $\alpha$). In particular, the so-called hard…

Functional Analysis · Mathematics 2010-01-15 Torsten Ehrhardt

We investigate a two-dimensional statistical model of N charged particles interacting via logarithmic repulsion in the presence of an oppositely charged compact region K whose charge density is determined by its equilibrium potential at an…

Classical Analysis and ODEs · Mathematics 2012-07-04 Christopher D. Sinclair , Maxim L. Yattselev

We introduce and study a family of random processes with a discrete time related to products of random matrices. Such processes are formed by singular values of random matrix products, and the number of factors in a random matrix product…

Mathematical Physics · Physics 2015-11-06 Eugene Strahov

We describe a new universality class for unitary invariant random matrix ensembles. It arises in the double scaling limit of ensembles of random $n \times n$ Hermitian matrices $Z_{n,N}^{-1} |\det M|^{2\alpha} e^{-N \Tr V(M)} dM$ with…

Classical Analysis and ODEs · Mathematics 2010-07-30 A. R. Its , A. B. J. Kuijlaars , J. Ostensson

The eigenvalues for the minors of real symmetric ($\beta=1$) and complex Hermitian ($\beta=2$) Wigner matrices form the Wigner corner process, which is a multilevel interlacing particle system. In this paper, we study the microscopic…

Probability · Mathematics 2019-07-25 Jiaoyang Huang

Covariances and variances of linear statistics of a point process can be written as integrals over the truncated two-point correlation function. When the point process consists of the eigenvalues of a random matrix ensemble, there are often…

Mathematical Physics · Physics 2022-05-04 Peter J. Forrester

The (BC type) z-measures are a family of four parameter $z, z', a, b$ probability measures on the path space of the nonnegative Gelfand-Tsetlin graph with Jacobi-edge multiplicities. We can interpret the $z$-measures as random point…

Representation Theory · Mathematics 2018-06-15 Cesar Cuenca

We study some random interlaced configurations considering the eigenvalues of the main minors of Hermitian random matrices of the classical complex Lie algebras. We claim that these random configurations are determinantal and give their…

Probability · Mathematics 2008-02-29 Manon Defosseux

We consider a particle system with weights and the scaling limits derived from its occupation time. We let the particles perform independent recurrent L\'evy motions and we assume that their initial positions and weights are given by a…

Probability · Mathematics 2018-01-29 Łukasz Treszczotko

In a recent article, Alishahi and Zamani discuss the spherical ensemble, a rotationally invariant determinantal point process on the 2-sphere. In this paper we extend this process in a natural way to the 2d-dimensional sphere. We prove that…

Probability · Mathematics 2018-06-28 Carlos Beltrán , Ujué Etayo

We consider the eigenvalues of symplectic elliptic Ginibre matrices which are known to form a Pfaffian point process whose correlation kernel can be expressed in terms of the skew-orthogonal Hermite polynomials. We derive the scaling limits…

Probability · Mathematics 2022-08-23 Sung-Soo Byun , Markus Ebke

In this paper, we study the expected value of the pair correlation statistics of randomized point configurations on the sphere, with the emphasis on point configurations generated by determinantal point processes. We study the cases of the…

Probability · Mathematics 2026-04-22 Maryna Manskova

For a broad class of point processes, including determinantal point processes, we construct associated marked and conditional ensembles, which allow to study a random configuration in the point process, based on information about a randomly…

Probability · Mathematics 2022-11-01 Tom Claeys , Gabriel Glesner