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When identical particles on a line collide, they merge and continue as one. Exact determinantal formulas have long been available for particles conditioned never to collide, but collisions change the number of particles, and exact…

Probability · Mathematics 2026-03-10 Piotr Śniady

We consider kernels of discrete convolution operators or, equivalently, homogeneous solutions of partial difference operators and show that these solutions always have to be exponential polynomials. The respective polynomial space in…

Numerical Analysis · Mathematics 2014-04-01 Tomas Sauer

Determinantal point processes (DPPs) are repulsive point processes where the interaction between points depends on the determinant of a positive-semi definite matrix. In this paper, we study the limiting process of L-ensembles based on…

Probability · Mathematics 2022-06-01 Simon Barthelmé , Nicolas Tremblay , Konstantin Usevich , Pierre-Olivier Amblard

Determinantal and permanental processes are point processes with a correlation function given by a determinant or a permanent. Their atoms exhibit mutual attraction of repulsion, thus these processes are very far from the uncorrelated…

Probability · Mathematics 2010-04-19 Isabelle Camilier , Laurent Decreusefond

We study normal approximations for a class of discrete-time occupancy processes, namely, Markov chains with transition kernels of product Bernoulli form. This class encompasses numerous models which appear in the complex networks…

Probability · Mathematics 2018-11-13 Liam Hodgkinson , Ross McVinish , Philip K. Pollett

In this paper we investigate the class of invariant positive definite kernels on the free semigroup on N generators. We provide a combinatorial description of the positivity of the kernel in terms of Dyck paths and then we find a…

Functional Analysis · Mathematics 2007-05-23 T. Banks , T. Constantinescu , Nermine El-Sissi

We study the singular values of the product of two coupled rectangular random matrices as a determinantal point process. Each of the two factors is given by a parameter dependent linear combination of two independent, complex Gaussian…

Mathematical Physics · Physics 2016-07-11 Gernot Akemann , Eugene Strahov

When particles on a line collide, they may coalesce into one. Such systems arise in the voter model, where boundaries between opinion clusters perform coalescing random walks, and in reaction-diffusion theory, where diffusing particles…

Probability · Mathematics 2026-03-10 Piotr Śniady

A determinantal point process (DPP) is an ensemble of random nonnegative-integer-valued Radon measures, whose correlation functions are all given by determinants specified by an integral kernel called the correlation kernel. First we show…

Probability · Mathematics 2020-03-11 Makoto Katori

In this note, we recall the definition of the binary branching model with Moran type interactions (BBMMI) introduced in [8]. In this interacting particle system, particles evolve, reproduce and die independently and, with a probability that…

Probability · Mathematics 2025-01-31 A M G Cox , E Horton , D Villemonais

The Determinantal Point Process (DPP) is a parameterized model for multivariate binary variables, characterized by a correlation kernel matrix. This paper proposes a closed form estimator of this kernel, which is particularly easy to…

Machine Learning · Statistics 2025-05-21 Christian Gouriéroux , Yang Lu

We give a functional characterization of a class of quasi-invariant determinantal processes corresponding to projection kernels in terms of de Branges spaces of entire funcitons.

Functional Analysis · Mathematics 2024-10-08 Roman Romanov

The unusual ratio of the neutron and proton transition matrix elements, $M_n/M_p$, may indicate the exotic feature of decoupled neutron and proton density distributions. In this contribution we show that these transition matrix elements are…

Nuclear Theory · Physics 2010-08-31 Chong Qi

We introduce the mathematical theory of the particle systems that interact via permutations, where the transition rates are assigned not to the jumps from a site to a site, but to the permutations themselves. This permutation processes can…

Probability · Mathematics 2007-05-23 Yevgeniy Kovchegov

In this paper, we tackle a critical issue in nonparametric inference for systems of interacting particles on Riemannian manifolds: the identifiability of the interaction functions. Specifically, we define the function spaces on which the…

Numerical Analysis · Mathematics 2024-09-11 Sui Tang , Malik Tuerkoen , Hanming Zhou

Determinantal point processes (DPPs for short) are a class of repulsive point processes. They have found some statistical applications to model spatial point pattern datasets with repulsion between close points. In the case of DPPs on…

Statistics Theory · Mathematics 2025-07-28 Poinas Arnaud

The Gamma kernel is a projection kernel of the form (A(x)B(y)-B(x)A(y))/(x-y), where A and B are certain functions on the one-dimensional lattice expressed through Euler's Gamma function. The Gamma kernel depends on two continuous…

Probability · Mathematics 2013-03-04 Grigori Olshanski

We introduce and systematically develop two classes of discrete integrable operators: those with $2\times 2$ matrix kernels and those possessing general differential kernels, thereby generalizing the discrete analogue previously studied. A…

Exactly Solvable and Integrable Systems · Physics 2025-11-10 Huan Liu

We investigate the intertwining of Laguerre processes of parameter $\alpha$ in different dimensions. We introduce a Feller kernel that depends on $\alpha $ and intertwines the $\alpha$-Laguerre process in $N+1$ dimensions and that in $N$…

Probability · Mathematics 2024-03-19 Alexander I. Bufetov , Yosuke Kawamoto

We consider the problem of inferring the interaction kernel of stochastic interacting particle systems from observations of a single particle. We adopt a semi-parametric approach and represent the interaction kernel in terms of a…

Statistics Theory · Mathematics 2025-10-31 Grigorios A. Pavliotis , Andrea Zanoni
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