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The Bessel point process is a rigid point process on the positive real line and its conditional measure on a bounded interval $[0,R]$ is almost surely an orthogonal polynomial ensemble. In this article, we show that if $R$ tends to…

Probability · Mathematics 2021-05-14 Leslie Molag , Marco Stevens

We investigate the limiting behavior of discrete determinantal point processes (DPPs) towards continuous DPPs when the size of the set to sample from goes to infinity. We propose a non-asymptotic characterization of this limit in terms of…

Probability · Mathematics 2026-03-03 Hugo Jaquard , Nicolas Keriven

We prove the Bernoulli property for determinantal point processes on $ \mathbb{R}^d $ with translation-invariant kernels. For the determinantal point processes on $ \mathbb{Z}^d $ with translation-invariant kernels, the Bernoulli property…

Probability · Mathematics 2019-09-17 Shota Osada

We characterize a Hawkes point process with kernel proportional to the probability density function of Mittag-Leffler random variables. This kernel decays as a power law with exponent $\beta +1 \in (1,2]$. Several analytical results can be…

We study fixed points of contractive convolution operators associated to contractive quantum measures on locally compact quantum groups. We characterise the existence of non-zero fixed points respectively on $L^\infty(\mathbb{G})$ and on…

Operator Algebras · Mathematics 2020-04-20 Matthias Neufang , Pekka Salmi , Adam Skalski , Nico Spronk

We study some variants of the Erd\H{o}s similarity problem. We pose the question if every measurable subset of the real line with positive measure contains a similar copy of an infinite geometric progression. We construct a compact subset…

Metric Geometry · Mathematics 2023-10-20 Alex Burgin , Samuel Goldberg , Tamás Keleti , Connor MacMahon , Xianzhi Wang

We prove that the spectrum of the stochastic Airy operator is rigid in the sense of Ghosh and Peres (Duke Math. J., 166(10):1789--1858, 2017) for Dirichlet and Robin boundary conditions. This proves the rigidity of the Airy-$\beta$ point…

Probability · Mathematics 2022-09-27 Pierre Yves Gaudreau Lamarre , Promit Ghosal , Wenxuan Li , Yuchen Liao

In this note we consider a certain class of Gaussian entire functions, characterized by some asymptotic properties of their covariance kernels, which we call admissible (as defined by Hayman). A notable example is the Gaussian Entire…

Probability · Mathematics 2019-04-24 Avner Kiro , Alon Nishry

In this note we study a natural measure on plane partitions giving rise to a certain discrete-time Muttalib-Borodin process (MBP): each time-slice is a discrete version of a Muttalib-Borodin ensemble (MBE). The process is determinantal with…

Probability · Mathematics 2020-10-30 Dan Betea , Alessandra Occelli

We consider a kernel based harmonic analysis of "boundary," and boundary representations. Our setting is general: certain classes of positive definite kernels. Our theorems extend (and are motivated by) results and notions from classical…

Functional Analysis · Mathematics 2016-11-15 Palle Jorgensen , Feng Tian

We construct a class of homogeneous Cantor-Moran measures with all contraction ratios being reciprocal of integers, and prove that they are pointwise absolutely normal. Our approach relies on methods developed by Davenport, Erd{\H{o}}s, and…

Classical Analysis and ODEs · Mathematics 2026-01-08 Chun-Kit Lai , Yu-Hao Xie

We study the local statistics of orthogonal polynomial ensembles near a hard edge, subject to a multiplicative deformation of the measure. Probabilistically, this deformation corresponds to a position-dependent conditional thinning of the…

Mathematical Physics · Physics 2026-02-23 Leslie Molag , Guilherme L. F. Silva , Lun Zhang

We show that the symplectic and orthogonal character analogues of Okounkov's Schur measure (on integer partitions) are determinantal, with explicit correlation kernels. We apply this to prove certain Borodin-Okounkov-Gessel-type results…

Probability · Mathematics 2020-01-31 Dan Betea

We define the epsilon-distortion complexity of a set as the shortest program, running on a universal Turing machine, which produces this set at the precision epsilon in the sense of Hausdorff distance. Then, we estimate the…

Dynamical Systems · Mathematics 2007-05-23 C. Bonanno , J. -R. Chazottes , P. Collet

In this paper, we introduce a two-parameters determinantal point process in the Poincar\'e disc and compute the asymptotics of the variance of its number of particles inside a disc centered at the origin and of radius $r$ as $r$ tends to…

Probability · Mathematics 2017-12-14 Nizar Demni , Pierre Lazag

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

Determinantal point processes have arisen in diverse settings in recent years and have been investigated intensively. We study basic combinatorial and probabilistic aspects in the discrete case. Our main results concern relationships with…

Probability · Mathematics 2010-04-27 Russell Lyons

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

Generalized inverses of tensors play increasingly important roles in computational mathematics and numerical analysis. It is appropriate to develop the theory of generalized inverses of tensors within the algebraic structure of a ring. In…

Rings and Algebras · Mathematics 2021-09-24 Ratikanta Behera , Jajati Keshari Sahoo , R. N. Mohapatra , M. Zuhair Nashed

We consider the product of determinantal point processes (DPPs), a point process whose probability mass is proportional to the product of principal minors of multiple matrices, as a natural, promising generalization of DPPs. We study the…

Machine Learning · Computer Science 2021-11-30 Naoto Ohsaka , Tatsuya Matsuoka