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Related papers: Empirical Spacings of Unfolded Eigenvalues

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We consider density estimators based on the nearest neighbors method applied to discrete point distibutions in spaces of arbitrary dimensionality. If the density is constant, the volume of a hypersphere centered at a random location is…

Instrumentation and Methods for Astrophysics · Physics 2013-01-24 Przemek Wozniak , Andrzej Kruszewski

Understanding the limiting behavior of eigenvalues of random matrices is the central problem of random matrix theory. Classical limit results are known for many models, and there has been significant recent progress in obtaining more…

Probability · Mathematics 2017-09-05 Elizabeth S. Meckes , Mark W. Meckes

We consider a random interval splitting process, in which the splitting rule depends on the empirical distribution of interval lengths. We show that this empirical distribution converges to a limit almost surely as the number of intervals…

Probability · Mathematics 2018-06-20 Pascal Maillard , Elliot Paquette

We derive distributional limits for empirical transport distances between probability measures supported on countable sets. Our approach is based on sensitivity analysis of optimal values of infinite dimensional mathematical programs and a…

Probability · Mathematics 2018-09-18 Carla Tameling , Max Sommerfeld , Axel Munk

The local spectral statistics of random matrices forms distinct universality classes, strongly depending on the position in the spectrum. Surprisingly, the spacing between consecutive eigenvalues at the spectral edges has received little…

Mathematical Physics · Physics 2022-04-12 G. Akemann , V. Gorski , M. Kieburg

We consider a collection of weakly interacting diffusion processes moving in a two-scale locally periodic environment. We study the large deviations principle of the empirical distribution of the particles' positions in the combined limit…

Probability · Mathematics 2022-11-03 Zachary Bezemek , Konstantinos Spiliopoulos

The scaled standard Wigner matrix (symmetric with mean zero, variance one i.i.d. entries), and its limiting eigenvalue distribution, namely the semi-circular distribution, has attracted much attention. The $2k$th moment of the limit equals…

Probability · Mathematics 2021-03-18 Arup Bose , Koushik Saha , Arusharka Sen , Priyanka Sen

We find the precise rate at which the empirical measure associated to a $\beta$-ensemble converges to its limiting measure. In our setting the $\beta$-ensemble is a random point process on a compact complex manifolds distributed according…

Complex Variables · Mathematics 2018-10-24 T. Carroll , J. Marzo , X. Massaneda , J. Ortega-Cerdà

We investigate a branching random walk where the displacements are independent from the branching mechanism and have a stretched exponential distribution. We describe the positions of the particles in the vicinity of the rightmost particle…

Probability · Mathematics 2024-01-26 Piotr Dyszewski , Nina Gantert

We study the problem of distributional matrix completion: Given a sparsely observed matrix of empirical distributions, we seek to impute the true distributions associated with both observed and unobserved matrix entries. This is a…

Machine Learning · Statistics 2025-06-09 Jacob Feitelberg , Kyuseong Choi , Anish Agarwal , Raaz Dwivedi

We generally study the density of eigenvalues in unitary ensembles of random matrices from the recurrence coefficients with regularly varying conditions for the orthogonal polynomials. First we calculate directly the moments of the density.…

Mathematical Physics · Physics 2008-10-31 Dang-Zheng Liu , Zheng-Dong Wang , Kui-Hua Yan

In a recent paper the author proved a theorem to the effect that the matrix of normalized Euclidean distances on the set of specially distributed random points in the $n$-dimensional Euclidean space $\mathbb R^{n}$ with independent…

Mathematical Physics · Physics 2015-09-07 A. P. Zubarev

We describe a previously unexplored effect of the continuous spontaneous localization model whereby a correlation develops in the distributions of two nearby non-interacting particles following a period of diffusion. We propose the use of…

Quantum Physics · Physics 2014-11-27 Daniel Bedingham

In this paper, we characterize the convergence of the (rescaled logarithmic) empirical spectral distribution of wavelet random matrices. We assume a moderately high-dimensional framework where the sample size $n$, the dimension $p(n)$ and,…

Probability · Mathematics 2024-01-08 Patrice Abry , Gustavo Didier , Oliver Orejola , Herwig Wendt

Basing on our recent results on the $1/n$-expansion in unitary invariant random matrix ensembles, known as matrix models, we prove that the local eigenvalue statistic, arising in a certain neighborhood of the edges of the support of the…

Mathematical Physics · Physics 2007-05-23 L. Pastur , M. Shcherbina

We consider finite Bernoulli convolutions with a parameter $1/2 < r < 1$ supported on a discrete point set, generically of size $2^N$. These sequences are uniformly distributed with respect to the infinite Bernoulli convolution measure…

Number Theory · Mathematics 2011-07-20 Itai Benjamini , Boris Solomyak

We compute analytically the joint probability density of eigenvalues and the level spacing statistics for an ensemble of random matrices with interesting features. It is invariant under the standard symmetry groups (orthogonal and unitary)…

Statistical Mechanics · Physics 2015-07-21 Zdzisław Burda , Giacomo Livan , Pierpaolo Vivo

We study the probability distribution of the ratio of consecutive level spacings for embedded one plus two-body random matrix ensembles with and without spin degree of freedom and for both fermion and boson systems. The agreement between…

Chaotic Dynamics · Physics 2015-06-16 N. D. Chavda , V. K. B. Kota

We consider the empirical eigenvalue distribution of an $m\times m$ principal submatrix of an $n\times n$ random unitary matrix distributed according to Haar measure. For $n$ and $m$ large with $\frac{m}{n}=\alpha$, the empirical spectral…

Probability · Mathematics 2019-05-08 Elizabeth Meckes , Kathryn Stewart

How many samples are sufficient to guarantee that the eigenvectors and eigenvalues of the sample covariance matrix are close to those of the actual covariance matrix? For a wide family of distributions, including distributions with finite…

Machine Learning · Statistics 2017-02-20 Andreas Loukas