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Related papers: Generic Cuspidal Points and Their Localization

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We have discussed earlier the correlation functions of the random variables $\det(\la-X)$ in which $X$ is a random matrix. In particular the moments of the distribution of these random variables are universal functions, when measured in the…

Mathematical Physics · Physics 2009-10-31 E. Brezin , S. Hikami

We give a method for taking microscopic limits of normal matrix ensembles. We apply this method to study the behaviour near certain types of singular points on the boundary of the droplet. Our investigation includes ensembles without…

Probability · Mathematics 2019-10-10 Yacin Ameur , Nam-Gyu Kang , Nikolai Makarov , Aron Wennman

Critical points of a scalar quantitiy are either extremal points or saddle points. The character of the critical points is determined by the sign distribution of the eigenvalues of the Hessian matrix. For a two-dimensional homogeneous and…

Fluid Dynamics · Physics 2009-11-13 H. Vogel , W. Mohring

We investigate geometric invariants of cuspidal edges on focal surfaces of regular surface. In particular, we shall clarify the sign of the singular curvature at a cuspidal edge on a focal surface using singularities of parallel surface of…

Differential Geometry · Mathematics 2026-05-19 Keisuke Teramoto

A recursive method is derived to calculate all eigenvalue correlation functions of a random hermitian matrix in the large size limit, and after smoothing of the short scale oscillations. The property that the two-point function is…

High Energy Physics - Theory · Physics 2008-02-03 B. Eynard

We consider quantum walks defined on arbitrary infinite graphs, parameterized by a family of scattering matrices attached to the vertices. Multiplying each scattering matrix by an i.i.d. random phase, we obtain a random scattering quantum…

Mathematical Physics · Physics 2026-02-16 Alain Joye , Andreas Schaefer , Simone Warzel

A set of discrete individual points located in an embedding continuum space can be seen as percolating or non-percolating, depending on the radius of the discs/spheres associated with each of them. This problem is relevant in theoretical…

Statistical Mechanics · Physics 2022-07-21 Pablo Villegas , Tommaso Gili , Andrea Gabrielli , Guido Caldarelli

Euclidean random matrices arise in a wide range of physical systems where interactions are determined by spatial configurations, including disordered media and cooperative phenomena in atomic ensembles. Unlike classical random matrix…

Statistical Mechanics · Physics 2026-05-08 Pasquale Casaburi , Pierpaolo Vivo

Spatial Poisson point processes on finite-dimensional Euclidean space provide fundamental mathematical tools for modeling random spatial point patterns. In this paper, we introduce and analyze several Poisson-type spatial point processes.…

Probability · Mathematics 2026-01-26 Pradeep Vishwakarma

A numerical algorithm is proposed to deal with parametric eigenvalue problems involving non-Hermitian matrices and is exploited to find location of defective eigenvalues in the parameter space of non-Hermitian parametric eigenvalue…

Computational Physics · Physics 2026-01-23 Benoit Nennig , Martin Ghienne , Emmanuel Perrey-Debain

We discuss on general grounds some local indicators of entanglement, that have been proposed recently for the study and classification of quantum phase transitions. In particular, we focus on the capability of entanglement in detecting…

Quantum Physics · Physics 2007-05-23 L. Campos Venuti , C. Degli Esposti Boschi , G. Morandi , M. Roncaglia , A. Scaramucci

In the past we have considered Gaussian random matrix ensembles in the presence of an external matrix source. The reason was that it allowed, through an appropriate tuning of the eigenvalues of the source, to obtain results on non-trivial…

High Energy Physics - Theory · Physics 2018-09-26 E. Brezin , S. Hikami

The $k$ principal points of a random vector $\mathbf{X}$ are defined as a set of points which minimize the expected squared distance between $\mathbf{X}$ and the nearest point in the set. They are thoroughly studied in Flury (1990, 1993),…

Probability · Mathematics 2020-06-09 Juan Lucas Bali , Graciela Boente

Using our previously published algorithm, we analyze the eigenvectors of the generalized Laplacian for two metric graphs occurring in practical applications. As expected, localization of an eigenvector is rare and the network should be…

Mathematical Physics · Physics 2023-02-08 H. Kravitz , M. Brio , J. -G. Caputo

We establish universal Gaussian fluctuations for the mesoscopic linear eigenvalue statistics in the vicinity of the cusp-like singularities of the limiting spectral density for Wigner-type random matrices. Prior to this work, the linear…

Probability · Mathematics 2023-08-25 Volodymyr Riabov

We study random points on the real line generated by the eigenvalues in unitary invariant random matrix ensembles or by more general repulsive particle systems. As the number of points tends to infinity, we prove convergence of the…

Probability · Mathematics 2015-11-11 Kristina Schubert , Martin Venker

We present a generalization of the method of the local relaxation flow to establish the universality of local spectral statistics of a broad class of large random matrices. We show that the local distribution of the eigenvalues coincides…

Mathematical Physics · Physics 2010-08-20 Laszlo Erdos , Benjamin Schlein , Horng-Tzer Yau , Jun Yin

In many problems of quantum chaos the calculation of sums of products of periodic orbit contributions is required. A general method of computation of these sums is proposed for generic integrable models where the summation over periodic…

chao-dyn · Physics 2009-10-31 E. Bogomolny

We study the spectral measure of large Euclidean random matrices. The entries of these matrices are determined by the relative position of $n$ random points in a compact set $\Omega_n$ of $\R^d$. Under various assumptions we establish the…

Probability · Mathematics 2007-12-12 Charles Bordenave

This paper investigates the asymptotics of eigenstructure of sample covariance matrix under the spiked covariance matrix model in ultra-high-dimensional settings, where the dimensionality can grow much faster than the sample size with $ p…

Statistics Theory · Mathematics 2026-04-30 Wonjun Seo