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A "mysterious" relation between the number variance and the variance of the $L$-th ordered eigenvalue, first suggested by French et al. [Ann. Phys. 113, 277 (1978)], is revisited and proven to be asymptotically exact for the $\beta=2$ Dyson…

Mathematical Physics · Physics 2026-04-21 Peng Tian , Roman Riser , Eugene Kanzieper

Asymptotic expansions are given for large values of $n$ of the generalized Bessel polynomials $Y_n^\mu(z)$. The analysis is based on integrals that follow from the generating functions of the polynomials. A new simple expansion is given…

Classical Analysis and ODEs · Mathematics 2011-01-26 José Luis López , Nico M. Temme

The large-time asymptotics of the density matrix solving a drift-diffusion-Poisson model for the spin-polarized electron transport in semiconductors is proved. The equations are analyzed in a bounded domain with initial and Dirichlet…

Analysis of PDEs · Mathematics 2019-08-28 Philipp Holzinger , Ansgar Jüngel

In this paper we propose a Bayesian answer to testing problems when the hypotheses are not well separated. The idea of the method is to study the posterior distribution of a discrepancy measure between the parameter and the model we want to…

Statistics Theory · Mathematics 2017-06-28 Jean-Bernard Salomond

Consider $ m $ copies of an irreducible, aperiodic Markov chain $ Y $ taking values in a finite state space. The asymptotics as $ m $ tends to infinity, of the first time from which on the trajectories of the $ m $ copies differ, have been…

Probability · Mathematics 2023-06-22 Silvia Businger

We prove large (and moderate) deviations for a class of linear combinations of spacings generated by i.i.d. exponentially distributed random variables. We allow a wide class of coefficients which can be expressed in terms of continuous…

Probability · Mathematics 2021-09-07 Camilla Calì , Maria Longobardi , Claudio Macci , Barbara Pacchiarotti

We study the first and second orders of the asymptotic expansion, as the dimension goes to infinity, of the moments of the Hilbert-Schmidt norm of a uniformly distributed matrix in the p-Schatten unit ball. We consider the case of matrices…

Functional Analysis · Mathematics 2022-02-17 Benjamin Dadoun , Matthieu Fradelizi , Olivier Guédon , Pierre-André Zitt

Making use of a Rice-like series expansion, for a class of stationary Gaussian processes the asymptotic behavior of the first passage time probability density function through certain time-varying boundaries, including periodic boundaries,…

Probability · Mathematics 2007-05-23 E. Di Nardo , A. G. Nobile , E. Pirozzi , L. M. Ricciardi

We study the distribution of the 'gap time', the first time that a large gap appears, in the spatial birth and death point process on $[0,1]$ in which particles are added uniformly in space at rate $\lambda$ and are removed independently at…

Probability · Mathematics 2025-12-05 Eric Foxall , Clément Soubrier

Physical systems exhibiting stochastic or chaotic behavior are often amenable to treatment by random matrix models. In deciding on a good choice of model, random matrix physics is constrained and guided by symmetry considerations. The…

Mathematical Physics · Physics 2010-01-06 Martin R. Zirnbauer

The problem of binary hypothesis testing between two probability measures is considered. New sharp bounds are derived for the best achievable error probability of such tests based on independent and identically distributed observations.…

Information Theory · Computer Science 2024-05-30 Valentinian Lungu , Ioannis Kontoyiannis

Random fields play a central role in the analysis of spatially correlated data and, as a result, have a significant impact on a broad array of scientific applications. This paper studies the cepstral random field model, providing recursive…

Statistics Theory · Mathematics 2014-01-17 Tucker S. McElroy , Scott H. Holan

The spectra of empirical correlation matrices, constructed from multivariate data, are widely used in many areas of sciences, engineering and social sciences as a tool to understand the information contained in typically large datasets. In…

Data Analysis, Statistics and Probability · Physics 2021-08-12 Udaysinh T. Bhosale , S. Harshini Tekur , M. S. Santhanam

The number partitioning problem can be interpreted physically in terms of a thermally isolated non-interacting Bose gas trapped in a one-dimensional harmonic oscillator potential. We exploit this analogy to characterize, by means of a…

Statistical Mechanics · Physics 2007-05-23 C. Weiss , M. Holthaus

We study a family of parametric statistical models based on gamma distributions, which do give realistic descriptions for other stochastic porous media. Gamma distributions contain as a special case the exponential distributions, which…

Astrophysics · Physics 2016-08-30 C. T. J. Dodson

We study the large-$N$ behavior of random matrix tuples $Y^N = (Y_1^N,\dots,Y_d^N)$ with joint density proportional to $e^{-N^2 V}$ for some convex function $V$ in non-commuting variables satisfying certain bounds on its second derivative.…

Probability · Mathematics 2026-04-06 David Jekel , Evangelos A. Nikitopoulos , Félix Parraud

We present a Gaussian ensemble of random cyclic matrices on the real field and study their spectral fluctuations. These cyclic matrices are shown to be pseudo-symmetric with respect to generalized parity. We calculate the joint probability…

Mathematical Physics · Physics 2013-02-13 Sudhir R. Jain , Shashi C. L. Srivastava

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 distribution of cycle counts in a random regular graph, which is closely linked to the graph's spectral properties. We broaden the asymptotic regime in which the cycle counts are known to be approximately Poisson, and we…

Combinatorics · Mathematics 2023-07-14 Tobias Johnson

The Poisson distribution arises naturally when dealing with data involving counts, and it has found many applications in inverse problems and imaging. In this work, we develop an approximate Bayesian inference technique based on expectation…

Numerical Analysis · Mathematics 2019-09-04 Chen Zhang , Simon Arridge , Bangti Jin