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The log-Gaussian Cox process is a flexible and popular class of point pattern models for capturing spatial and space-time dependence for point patterns. Model fitting requires approximation of stochastic integrals which is implemented…

Computation · Statistics 2018-10-24 Shinichiro Shirota , Sudipto Banerjee

We consider weighted graphs satisfying sub-Gaussian estimate for the natural random walk. On such graphs, we study symmetric Markov chains with heavy tailed jumps. We establish a threshold behavior of such Markov chains when the index…

Probability · Mathematics 2015-09-03 Mathav Murugan , Laurent Saloff-Coste

We study mesoscopic linear statistics for a class of determinantal point processes which interpolates between Poisson and Gaussian Unitary Ensemble statistics. These processes are obtained by modifying the spectrum of the correlation kernel…

Probability · Mathematics 2019-07-23 Kurt Johansson , Gaultier Lambert

For random matrices with block correlation structure we show that the fluctuations of linear eigenvalue statistics are Gaussian on all mesoscopic scales with universal variance which coincides with that of the Gaussian unitary or Gaussian…

Probability · Mathematics 2023-06-30 Torben Krüger , Yuriy Nemish

I argue that conventional estimates of the criterion for classical behavior of a macroscopic body are incorrect in most circumstances,because they do not take into account the locality of interactions, which characterizes the behavior of…

Quantum Physics · Physics 2009-07-07 T. Banks

In this paper, we derive a unified method for establishing the distributional convergence of linear eigenvalue statistics (LES) for generalized patterned random matrices. We prove that for an $N \times N$ generalized patterned random matrix…

Probability · Mathematics 2025-03-14 Kiran Kumar A. S. , Shambhu Nath Maurya , Koushik Saha

We analyse the limiting behavior of the eigenvalue and singular value distribution for random convolution operators on large (not necessarily Abelian) groups, extending the results by M. Meckes for the Abelian case. We show that for regular…

Probability · Mathematics 2017-12-21 Radosław Adamczak

This paper deals with the optimization of trial states for the computation of dominant eigenvalues of operators and very large matrices. In addition to preliminary results for the energy spectrum of van der Waals clusters, we review results…

Chemical Physics · Physics 2007-05-23 Vilen Melik-Alaverdian , M. P. Nightingale

We study the zeroes of a family of random holomorphic functions on the unit disc, distinguished by their invariance with respect to the hyperbolic geometry. Our main finding is a transition in the limiting behaviour of the number of zeroes…

Probability · Mathematics 2023-02-22 Jeremiah Buckley , Alon Nishry

We develop a method to compute the moments of the eigenvalue densities of matrices in the Gaussian, Laguerre and Jacobi ensembles for all the symmetry classes beta = 1,2, 4 and finite matrix dimension n. The moments of the Jacobi ensembles…

Mathematical Physics · Physics 2012-07-02 F. Mezzadri , N. J. Simm

With large-scale Monte Carlo simulations, we investigate the nonsteady relaxation at the dynamic depinning transition in the two-dimensional Gaussian random-field Ising model. The dynamic scaling behavior is carefully analyzed, and the…

Statistical Mechanics · Physics 2023-06-21 Xiaohui Qian , Gaotian Yu , Nengji Zhou

The time-evolving precision matrix of a piecewise-constant Gaussian graphical model encodes the dynamic conditional dependency structure of a multivariate time-series. Traditionally, graphical models are estimated under the assumption that…

Methodology · Statistics 2017-11-01 Alexander J. Gibberd , James D. B. Nelson

A numerical study of low-lying glueball masses of compact U(1) lattice gauge theory in (2+1) dimensions is performed using Standard Path integral Monte Carlo techniques. The masses are extracted, at fixed (low) temperature, from simulations…

High Energy Physics - Lattice · Physics 2007-05-23 Mushtaq Loan , Michael Brunner , Chris Hamer

In this short note we study the asymptotic behaviour of the minima over compact intervals of Gaussian processes, whose paths are not necessarily smooth. We show that, beyond the logarithmic large deviation Gaussian estimates, this problem…

Probability · Mathematics 2019-08-27 Zhixin Wu , Arijit Chakrabarty , Gennady Samorodnitsky

Non-Gaussian likelihoods are essential for modelling complex real-world observations but pose significant computational challenges in learning and inference. Even with Gaussian priors, non-Gaussian likelihoods often lead to analytically…

Machine Learning · Statistics 2024-10-29 Thang D. Bui

This paper studies the asymptotic behavior of eigenvalues of random abelian G-circulant matrices, that is, matrices whose structure is related to a finite abelian group G in a way that naturally generalizes the relationship between…

Probability · Mathematics 2012-08-17 Mark W. Meckes

In previous work Majda and McLaughlin computed explicit expressions for the $2N$th moments of a passive scalar advected by a linear shear flow in the form of an integral over ${\bf R}^N$. In this paper we first compute the asymptotics of…

Fluid Dynamics · Physics 2007-05-23 J. C. Bronski , R. M. McLaughlin

In studying the enumerative theory of super characters' of the group of upper triangular matrices over a finite field we found that the moments (mean, variance and higher moments) of novel statistics on set partitions have simple closed…

Combinatorics · Mathematics 2013-06-12 Bobbie Chern , Persi Diaconis , Daniel M. Kane , Robert C. Rhoades

We prove the Central Limit Theorem for the number of eigenvalues near the spectrum edge for hermitian ensembles of random matrices. To derive our results, we use a general theorem, essentially due to Costin and Lebowitz, concerning the…

Mathematical Physics · Physics 2007-05-23 Alexander B. Soshnikov

We revisit here the problem of the collective non-equilibrium dynamics of a classical statistical system at a critical point and in the presence of surfaces. The effects of breaking separately space- and time-translational invariance are…

Statistical Mechanics · Physics 2014-11-24 Matteo Marcuzzi , Andrea Gambassi