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We define a determinantal point process on the complex projective space that reduces to the so-called spherical ensemble for complex dimension 1 under identification of the 2-sphere with the Riemann sphere. Through this determinantal point…

Classical Analysis and ODEs · Mathematics 2017-03-02 Carlos Beltrán , Ujué Etayo

We consider determinantal point processes on the $d$-dimensional unit sphere $\mathbb S^d$. These are finite point processes exhibiting repulsiveness and with moment properties determined by a certain determinant whose entries are specified…

Methodology · Statistics 2016-07-14 Jesper Møller , Morten Nielsen , Emilio Porcu , Ege Rubak

We study expected Riesz s-energies and linear statistics of some determinantal processes on the sphere. In particular, we compute the expected Riesz and logarithmic energies of the determinantal processes given by the reproducing kernel of…

Classical Analysis and ODEs · Mathematics 2016-10-21 Carlos Beltrán , Jordi Marzo , Joaquim Ortega-Cerdà

In this paper, we study the expected value of the pair correlation statistics of randomized point configurations on the sphere, with the emphasis on point configurations generated by determinantal point processes. We study the cases of the…

Probability · Mathematics 2026-04-22 Maryna Manskova

The unitary group with the Haar probability measure is called Circular Unitary Ensemble. All the eigenvalues lie on the unit circle in the complex plane and they can be regarded as a determinantal point process on $\mathbb{S}^1$. It is also…

Probability · Mathematics 2022-03-16 Makoto Katori , Tomoyuki Shirai

We study the asymptotic behavior of the fluctuations of smooth and rough linear statistics for determinantal point processes on the sphere and on the Euclidean space. The main tool is the generalization of some norm representation results…

Classical Analysis and ODEs · Mathematics 2024-10-18 Matteo Levi , Jordi Marzo , Joaquim Ortega-Cerdà

Herein, we address the expectations of frame potentials of three types of determinantal point processes(DPPs) on the d-dimensional unit sphere: (i) spherical ensembles on the 2-dimensional unit sphere; (ii) harmonic ensembles on the…

Probability · Mathematics 2021-05-13 Masatake Hirao

The goal of this paper is to quantitatively describe some statistical properties of higher-dimensional determinantal point processes with a primary focus on the nearest-neighbor distribution functions. Toward this end, we express these…

Statistical Mechanics · Physics 2009-11-13 A. Scardicchio , C. E. Zachary , S. Torquato

We compute the full off-diagonal asymptotics of the equivariant and partial Bergman kernels associated with a circle action on a prequantized K\"ahler manifold with bounded geometry at infinity, then use these results to compute the…

Differential Geometry · Mathematics 2025-11-26 Louis Ioos

Determinantal point processes are point processes whose correlation functions are given by determinants of matrices. The entries of these matrices are given by one fixed function of two variables, which is called the kernel of the point…

Classical Analysis and ODEs · Mathematics 2019-06-27 Marco Stevens

We study the $L^{\infty}$ discrepancy of point sets generated by determinantal point processes on all compact, connected two-point homogeneous spaces, namely spheres and projective spaces. Using concentration inequalities and variance…

Classical Analysis and ODEs · Mathematics 2026-05-22 Carlos Beltrán , Ujué Etayo , Giacomo Gigante , Pedro R. López-Gómez , Ryan W. Matzke

We study point processes on $\mathbb S^d$, the $d$-dimensional unit sphere $\mathbb S^d$, considering both the isotropic and the anisotropic case, and focusing mostly on the spherical case $d=2$. The first part studies reduced Palm…

Methodology · Statistics 2016-06-14 Jesper Møller , Ege Rubak

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

We study the multiplicative statistics associated to the limiting determinantal point process describing unitary random matrices with a critical edge point, where limiting density vanishes like a power 5/2. We prove that these statistics…

Mathematical Physics · Physics 2026-02-05 Mattia Cafasso , Carla Mariana da Silva Pinheiro

We consider a family {P} of determinantal point processes arising in representation theory and random matrix theory. The processes live on the one-dimensional lattice and their correlation kernels correspond to projection operators in the…

Probability · Mathematics 2013-03-04 Grigori Olshanski

Two central objects in constructive approximation, the Christoffel-Darboux kernel and the Christoffel function, are encoding ample information about the associated moment data and ultimately about the possible generating measures. We…

Complex Variables · Mathematics 2019-04-30 Bernhard Beckermann , Mihai Putinar , Edward B. Saff , Nikos Stylianopoulos

In a recent article, Alishahi and Zamani discuss the spherical ensemble, a rotationally invariant determinantal point process on the 2-sphere. In this paper we extend this process in a natural way to the 2d-dimensional sphere. We prove that…

Probability · Mathematics 2018-06-28 Carlos Beltrán , Ujué Etayo

For a class of one-dimensional determinantal point processes including those induced by orthogonal projections with integrable kernels satisfying a growth condition, it is proved that their conditional measures, with respect to the…

Probability · Mathematics 2016-05-05 Alexander I. Bufetov

Determinantal point processes (DPPs) offer a powerful approach to modeling diversity in many applications where the goal is to select a diverse subset. We study the problem of learning the parameters (the kernel matrix) of a DPP from…

Machine Learning · Statistics 2014-11-10 Boqing Gong , Wei-lun Chao , Kristen Grauman , Fei Sha

We present eigenvalue decay estimates of integral operators associated with compositional dot-product kernels. The estimates improve on previous ones established for power series kernels on spheres. This allows us to obtain the volumes of…

Machine Learning · Statistics 2021-03-01 Meyer Scetbon , Zaid Harchaoui
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