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This study shows how Aronszajn's theory of reproducing kernels can be of use for the construction the Hilbert spaces of quantum theory. We show that the Feynman propagator is an example of a reproducing kernel under a boundedness condition.…

Mathematical Physics · Physics 2020-10-26 Pierre-Cyril Aubin-Frankowski

The standard Sobolev space $W^s_2(\mathbb{R}^d)$, with arbitrary positive integers $s$ and $d$ for which $s>d/2$, has the reproducing kernel $$ K_{d,s}(x,t)=\int_{\mathbb{R}^d}\frac{\prod_{j=1}^d\cos\left(2\pi\,(x_j-t_j)u_j\right)}…

Numerical Analysis · Mathematics 2018-07-17 Erich Novak , Mario Ullrich , Henryk Woźniakowski , Shun Zhang

The eigenfunctions of the Dirac operator on spheres and real hyperbolic spaces of arbitrary dimension are computed by separating variables in geodesic polar coordinates. These eigenfunctions are used to derive the heat kernel of the…

General Relativity and Quantum Cosmology · Physics 2009-10-28 R. Camporesi , A. Higuchi

A finite dimensional system with a quadratic Hamiltonian constraint is Dirac quantized in holomorphic, antiholomorphic and mixed representations. A unique inner product is found by imposing Hermitian conjugacy relations on an operator…

General Relativity and Quantum Cosmology · Physics 2010-11-01 Jorma Louko

We present decompositions of various positive kernels as integrals or sums of positive kernels. Within this framework we study the reproducing kernel Hilbert spaces associated with the fractional and bi-fractional Brownian motions. As a…

Probability · Mathematics 2007-05-23 Daniel Alpay , David Levanony

We propose to investigate test statistics for testing homogeneity in reproducing kernel Hilbert spaces. Asymptotic null distributions under null hypothesis are derived, and consistency against fixed and local alternatives is assessed.…

Machine Learning · Statistics 2008-12-18 Zaid Harchaoui , Francis Bach , Eric Moulines

The aim of this study is to present a good modernistic strategy for solving some well-known classes of Lane-Emden type singular differential equations. The proposed approach is based on the reproducing kernel Hilbert space (RKHS) and…

In this paper we solve support vector machines in reproducing kernel Banach spaces with reproducing kernels defined on nonsymmetric domains instead of the traditional methods in reproducing kernel Hilbert spaces. Using the orthogonality of…

Machine Learning · Statistics 2015-01-16 Gregory E. Fasshauer , Fred J. Hickernell , Qi Ye

We study the representation ${\cal D}$ of a simple compact Lie algebra $\g$ of rank l constructed with the aid of the hermitian Dirac matrices of a (${\rm dim} \g$)-dimensional euclidean space. The irreducible representations of $\g$…

High Energy Physics - Theory · Physics 2009-10-31 J. A. de Azcárraga , A. J. Macfarlane

The paper investigates the properties of certain biorthogonal polynomials appearing in a specific simultaneous Hermite-Pade' approximation scheme. Associated to any totally positive kernel and a pair of positive measures on the positive…

Mathematical Physics · Physics 2009-04-20 M. Bertola , M. Gekhtman , J. Szmigielski

A linear operator in a Hilbert space defined through the form of Riesz representation naturally introduces a reproducing kernel Hilbert space structure over the range space. Such formulation, called H-HK formulation in this paper, possesses…

Analysis of PDEs · Mathematics 2021-10-27 Tao Qian

Starting from a purely algebraic procedure based on the commutant of a subalgebra in the universal enveloping algebra of a given Lie algebra, the notion of algebraic Hamiltonians and the constants of the motion generating a polynomial…

Mathematical Physics · Physics 2023-07-20 Rutwig Campoamor-Stursberg , Danilo Latini , Ian Marquette , Yao-Zhong Zhang

There are two frameworks for mating Kleinian groups with rational maps on the Riemann sphere: the algebraic correspondence framework due to Bullett-Penrose-Lomonaco \cite{BP94,BL20} and the simultaneous uniformization mating framework of…

Dynamical Systems · Mathematics 2025-09-22 Mahan Mj , Sabyasachi Mukherjee

We study kernel functions, and associated reproducing kernel Hilbert spaces $\mathscr{H}$ over infinite, discrete and countable sets $V$. Numerical analysis builds discrete models (e.g., finite element) for the purpose of finding…

Functional Analysis · Mathematics 2015-08-17 Palle Jorgensen , Feng Tian

Various convergence results for the Bergman kernel of the Hilbert space of all polynomials in \C^{n} of total degree at most k, equipped with a weighted norm, are obtained. The weight function is assumed to be C^{1,1}, i.e. it is…

Complex Variables · Mathematics 2008-04-21 Robert Berman

The aim of the paper is to create a link between the theory of reproducing kernel Hilbert spaces (RKHS) and the notion of a unitary representation of a group or of a groupoid. More specifically, it is demonstrated on one hand, how to…

Functional Analysis · Mathematics 2021-02-22 Monika Drewnik , Tomasz Miller , Zbigniew Pasternak-Winiarski

We examine how the square-integrable function subspaces are transformed using the holomorphic Fourier transform. On account of this, the extended Paley-Wiener theorem over the Hardy-Sobolev spaces is produced. The theorem also asserts that…

Functional Analysis · Mathematics 2024-03-19 Detian Liu , Haichou Li , Kit Ian Kou

In this work, we consider "finite bandwidth" reproducing kernel Hilbert spaces which have orthonormal bases of the form $f_n(z)=z^n \prod_{j=1}^J \left( 1 - a_{n}w_j z \right)$, where $w_1 ,w_2, \ldots w_J $ are distinct points on the…

Functional Analysis · Mathematics 2023-10-18 Gregory T. Adams , Nathan A. Wagner

In this work, the concept of quasi-type Kernel polynomials with respect to a moment functional is introduced. Difference equation satisfied by these polynomials along with the criterion for orthogonality conditions are discussed. The…

Spectral Theory · Mathematics 2023-01-31 Vikash Kumar , A. Swaminathan

Learning the kernel functions used in kernel methods has been a vastly explored area in machine learning. It is now widely accepted that to obtain 'good' performance, learning a kernel function is the key challenge. In this work we focus on…

Machine Learning · Computer Science 2016-01-08 Chetan Tonde , Ahmed Elgammal