English
Related papers

Related papers: Central limit theorem for the determinantal point …

200 papers

We consider a family of linear operators, diagonalized by the Hankel transform. The Fredholm determinants of these operators, restricted to $L_2[0, R]$, are expressed in a convenient form for asymptotic analysis as $R\to\infty$. The result…

Functional Analysis · Mathematics 2025-04-15 Sergei M. Gorbunov

We consider the determinantal point process with the confluent hypergeometric kernel. This process is a universal point process in random matrix theory and describes the distribution of eigenvalues of large random Hermitian matrices near…

Mathematical Physics · Physics 2024-02-20 Shuai-Xia Xu , Shu-Quan Zhao , Yu-Qiu Zhao

In this paper, we consider the deformed Fredholm determinant of the confluent hypergeometric kernel. This determinant represents the gap probability of the corresponding determinantal point process where each particle is removed…

Mathematical Physics · Physics 2022-07-28 Dan Dai , Yu Zhai

For rescaled additive functionals of the sine-process, upper bounds are obtained for their speed of convergence to the Gaussian distribution with respect to the Kolmogorov-Smirnov metric. Under scaling with coefficient $R$ the…

Probability · Mathematics 2024-12-31 Alexander I. Bufetov

The main result of this paper is that determinantal point processes on the real line corresponding to projection operators with integrable kernels are quasi-invariant, in the continuous case, under the group of diffeomorphisms with compact…

Probability · Mathematics 2016-12-01 Alexander I. Bufetov

The paper establishes a functional version of the Hoeffding combinatorial central limit theorem. First, a pre-limiting Gaussian process approximation is defined, and is shown to be at a distance of the order of the Lyapounov ratio from the…

Probability · Mathematics 2009-07-03 A. D. Barbour , Svante Janson

We study Fredholm determinants of a class of integral operators, whose kernels can be expressed as double contour integrals of a special type. Such Fredholm determinants appear in various random matrix and statistical physics models. We…

Mathematical Physics · Physics 2020-10-29 Mattia Cafasso , Tom Claeys , Manuela Girotti

The confluent hypergeometric point process represents a universality class which arises in a variety of different but related areas. It particularly describes the local statistics of eigenvalues in the bulk of spectrum near a Fisher-Hartwig…

Mathematical Physics · Physics 2025-08-15 Taiyang Xu , Lun Zhang , Zhengyang Zhao

Determinantal point processes are characterized by a special structural property of the correlation functions: they are given by minors of a correlation kernel. However, unlike the correlation functions themselves, this kernel is not…

Probability · Mathematics 2022-06-15 Grigori Olshanski

In this paper, we investigate a determinantal point process on the interval $(-s,s)$, associated with the confluent hypergeometric kernel. Let $\mathcal{K}^{(\alpha,\beta)}_s$ denote the trace class integral operator acting on $L^2(-s, s)$…

Probability · Mathematics 2024-05-07 Dan Dai , Luming Yao , Yu Zhai

In this paper we prove a criterion of convergence in distribution in Skorokhod space. We apply this criterion to some special Levy processes and obtain almost-sure versions of limit theorems for these processes.

Probability · Mathematics 2009-08-10 E. E. Permyakova

We obtain "large gap" asymptotics for a Fredholm determinant with a confluent hypergeometric kernel. We also obtain asymptotics for determinants with two types of Bessel kernels which appeared in random matrix theory.

Mathematical Physics · Physics 2010-10-28 P. Deift , I. Krasovsky , J. Vasilevska

We provide a condition for f-ergodicity of strong Markov processes at a subgeometric rate. This condition is couched in terms of a supermartingale property for a functional of the Markov process. Equivalent formulations in terms of a drift…

Statistics Theory · Mathematics 2007-06-13 Randal Douc , Gersende Fort , Arnaud Guillin

Some significant quantities in mathematics and physics are most naturally expressed as the Fredholm determinant of an integral operator, most notably many of the distribution functions in random matrix theory. Though their numerical values…

Numerical Analysis · Mathematics 2010-06-01 Folkmar Bornemann

The purpose of this article is to develop a theory behind the occurrence of "path-integral" kernels in the study of extended determinantal point processes and non-intersecting line ensembles. Our first result shows how determinants…

Probability · Mathematics 2020-10-15 Alexei Borodin , Ivan Corwin , Daniel Remenik

We consider determinantal point processes on a compact complex manifold X in the limit of many particles. The correlation kernels of the processes are the Bergman kernels associated to a a high power of a given Hermitian holomorphic line…

Complex Variables · Mathematics 2016-12-15 Robert J. Berman

The main result of this paper is a functional limit theorem for the sine-process. In particular, we study the limit distribution, in the space of trajectories, for the number of particles in a growing interval. The sine-process has the…

Dynamical Systems · Mathematics 2018-01-12 Alexander I. Bufetov , Andrey V. Dymov

Let $F_n$ denote the distribution function of the normalized sum $Z_n = (X_1 + \dots + X_n)/\sigma\sqrt{n}$ of i.i.d. random variables with finite fourth absolute moment. In this paper, polynomial rates of convergence of $F_n$ to the normal…

Probability · Mathematics 2017-06-30 Sergey G. Bobkov

We construct inner products by the Bernstein-Markov inequality on spaces of holomorphic sections of high powers of a line bundle. The corresponding weighted Bergman kernel functions converge to an extremal function. We obtain a uniform…

Complex Variables · Mathematics 2017-05-23 Guokuan Shao

We study the approximation of a square-integrable function from a finite number of evaluations on a random set of nodes according to a well-chosen distribution. This is particularly relevant when the function is assumed to belong to a…

Machine Learning · Statistics 2024-11-13 Ayoub Belhadji , Rémi Bardenet , Pierre Chainais
‹ Prev 1 2 3 10 Next ›