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A determinantal point process (DPP) is an ensemble of random nonnegative-integer-valued Radon measures $\Xi$ on a space $S$ with measure $\lambda$, whose correlation functions are all given by determinants specified by an integral kernel…

Probability · Mathematics 2021-09-08 Makoto Katori , Tomoyuki Shirai

In this work, we investigate Gaussian Processes indexed by multidimensional distributions. While directly constructing radial positive definite kernels based on the Wasserstein distance has been proven to be possible in the unidimensional…

Non-linear Hawkes processes with memory kernels given by the sum of Erlang kernels are considered. It is shown that their stability properties can be studied in terms of an associated class of piecewise deterministic Markov processes,…

Probability · Mathematics 2018-11-27 Aline Duarte , Eva Löcherbach , Guilherme Ost

Inspired by Okounkov's work [\emph{Selecta Mathematica}, 7(1):57--81, 2001] which relates KP hierarchy to determinant point process, we establish a relationship between BKP hierarchy and Pfaffian point process. We prove that the correlation…

Mathematical Physics · Physics 2019-02-20 Zhi-Lan Wang , Shi-Hao Li

Quantum systems with constraints are often considered in modern theoretical physcics. All realistic field models based on the idea of gauge symmetry are of this type. A partial case of constraints being linear in coordinate and momenta…

Mathematical Physics · Physics 2007-05-23 O. Yu. Shvedov

Critical exponents of the Kawasaki dynamics in the Ising chain are re-examined numerically through the spectrum gap of evolution operators constructed both in spin and domain wall representations. At low temperature regimes the latter…

Statistical Mechanics · Physics 2010-11-17 M. D. Grynberg

Motivated by practical applications, I present a novel and comprehensive framework for operator-valued positive definite kernels. This framework is applied to both operator theory and stochastic processes. The first application focuses on…

Statistics Theory · Mathematics 2025-11-04 Saeed Hashemi Sababe

In this note, we show that determinantal point processes on the real line corresponding to de Branges spaces of entire functions are rigid in the sense of Ghosh-Peres and, under certain additional assumptions, quasi-invariant under the…

Probability · Mathematics 2016-06-07 Alexander I. Bufetov , Tomoyuki Shirai

Motivated by applications to the study of stochastic processes, we introduce a new analysis of positive definite kernels $K$, their reproducing kernel Hilbert spaces (RKHS), and an associated family of feature spaces that may be chosen in…

Functional Analysis · Mathematics 2017-07-27 Palle Jorgensen , Feng Tian

The Kawasaki model is not exactly solvable as any choice of the exchange rate ($w_{jj'}$) which satisfies the detailed balance condition is highly nonlinear. In this work we address the issue of writing $w_{jj'}$ in a best possible linear…

Statistical Mechanics · Physics 2014-04-25 Shaon Sahoo , Sandeep Chatterjee

Let $\Omega$ be a bounded pseudoconvex domain in $\mathbb{C}^n$, and let $\phi$ be a strictly plurisubharmonic function on $\Omega$. For each $k\in\mathbb{N}$, we consider determinantal point process $\Lambda_k$ with kernel $K_{k\phi}$,…

Complex Variables · Mathematics 2025-05-01 Kiyoon Eum

We study positive definite kernels pulled back along a finite family of self-maps under a subinvariance inequality for the associated branching operator. Iteration produces an increasing kernel tower with defect kernels. Under diagonal…

Probability · Mathematics 2026-02-03 James Tian

We identify the linear space spanned by the real-valued excessive functions of a Markov process with the set of those functions which are quasimartingales when we compose them with the process. Applications to semi-Dirichlet forms are…

Probability · Mathematics 2017-09-07 Iulian Cîmpean , Lucian Beznea

In the context of kernel optimization, we prove a result that yields new factorizations and realizations. Our initial context is that of general positive operator-valued kernels. We further present implications for Hilbert space-valued…

Operator Algebras · Mathematics 2024-10-14 Palle E. T. Jorgensen , James Tian

We discuss symmetric quantum measurements and the associated covariant observables modelled, respectively, as instruments and positive-operator-valued measures. The emphasis of this work are the optimality properties of the measurements,…

Quantum Physics · Physics 2021-03-30 Erkka Haapasalo , Juha-Pekka Pellonpää

A process model of quantum mechanics utilizes a combinatorial game to generate a discrete and finite causal space upon which can be defined a self-consistent quantum mechanics. An emergent space-time M and continuous wave function arise…

Mathematical Physics · Physics 2015-06-19 William Sulis

Given a stationary continuous-time process $f(t)$, the Hilbert-Schmidt operator $A_{\tau}$ can be defined for every finite $\tau$\cite{Vautard1989SingularSA}. Let $\lambda_{\tau,i}$ be the eigenvalues of $A_{\tau}$ with descending order. In…

Optimization and Control · Mathematics 2026-04-20 Yicun Zhen , Bertrand Chapron , Etienne Mémin

We study the asymptotics of certain measures on partitions (the so-called z-measures and their relatives) in two different regimes: near the diagonal of the corresponding Young diagram and in the intermediate zone between the diagonal and…

Mathematical Physics · Physics 2007-05-23 Alexei Borodin , Grigori Olshanski

We present an approach to construct approximate Koopman-type decompositions for dynamical systems depending on static or time-varying parameters. Our method simultaneously constructs an invariant subspace and a parametric family of…

Optimization and Control · Mathematics 2024-11-12 Yue Guo , Milan Korda , Ioannis G. Kevrekidis , Qianxiao Li

In this paper we elaborate on the interplay between energy optimization, positive definiteness, and discrepancy. In particular, assuming the existence of a $K$-invariant measure $\mu$ with full support, we show that conditional positive…

Classical Analysis and ODEs · Mathematics 2021-10-11 Dmitriy Bilyk , Ryan Matzke , Oleksandr Vlasiuk