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Related papers: Fourier-Bessel heat kernel estimates

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The Heat Kernel Method is applied to the constituent quark model. We calculate the effect of thermal quark fluctuations on the meson action and the resulting quark condensate and pi pi-scattering amplitude at finite temperature. The quarks…

High Energy Physics - Phenomenology · Physics 2009-10-30 B. -J. Schaefer , H. -J. Pirner

We study the occurrence of a Bose-Einstein transition in a dilute gas with repulsive interactions, starting from temperatures above the transition temperature. The formalism, based on the use of Ursell operators, allows us to evaluate the…

Statistical Mechanics · Physics 2007-05-23 M. Holzmann , P. Gruter , F. Laloe

We study the Sine$_\beta$ process introduced in [B. Valk\'o and B. Vir\'ag. Invent. math. (2009)] when the inverse temperature $\beta$ tends to 0. This point process has been shown to be the scaling limit of the eigenvalues point process in…

Probability · Mathematics 2014-12-16 Romain Allez , Laure Dumaz

We are studying the problem of estimating density in a wide range of metric spaces, including the Euclidean space, the sphere, the ball, and various Riemannian manifolds. Our framework involves a metric space with a doubling measure and a…

Statistics Theory · Mathematics 2023-04-04 Galatia Cleanthous , Athanasios G. Georgiadis , Philip A. White

In this paper, we transform a formula for the $A_2$ Dunkl kernel by B\'echir Amri. The resulting formula expresses the $A_2$ Dunkl kernel in terms of the $A_1$ Dunkl kernel involving only positive terms. This result allows us to derive…

Classical Analysis and ODEs · Mathematics 2023-08-04 P. Graczyk , P. Sawyer

On a complete non-compact Riemannian manifold satisfying the volume doubling property, we give conditions on the negative part of the Ricci curvature that ensure that, unless there are harmonic one-forms, the Gaussian heat kernel upper…

Analysis of PDEs · Mathematics 2016-06-09 Thierry Coulhon , Baptiste Devyver , Adam Sikora

This paper studies the asymptotic behavior of the integral kernel of the Dunkl transform, the so-called Dunkl kernel, when one of its arguments is fixed and the other tends to infinity either within a Weyl chamber of the associated…

Classical Analysis and ODEs · Mathematics 2023-05-31 Margit Rösler , Marcel de Jeu

We propose a test for model specification of a parametric diffusion process based on a kernel estimation of the transitional density of the process. The empirical likelihood is used to formulate a statistic, for each kernel smoothing…

Statistics Theory · Mathematics 2009-09-29 Song Xi Chen , Jiti Gao , Cheng Yong Tang

We study the kernel estimator of the transition density of bifurcating Markov chains. Under some ergodic and regularity properties, we prove that this estimator is consistent and asymptotically normal. Next, in the numerical studies, we…

Statistics Theory · Mathematics 2023-03-28 S. Valère Bitseki Penda

Theoretical predictions for the BCS-BEC crossover of trapped Fermi atoms are compared with recent experimental results for the density profiles of $^6$Li. The calculations rest on a single theoretical approach that includes pairing…

Superconductivity · Physics 2009-02-20 A. Perali , P. Pieri , G. C. Strinati

We obtain matching two sided estimates of the heat kernel on a connected sum of parabolic manifolds, each of them satisfying the Li-Yau estimate. The key result is the on-diagonal upper bound of the heat kernel at a central point. Contrary…

Probability · Mathematics 2016-08-05 Alexander Grigor'yan , Satoshi Ishiwata , Laurent Saloff-Coste

In this paper, we are interested in the estimates of the Dunkl Kernel on some special sets, following the work of M.F.E. de Jeu and M. R\"{o}sler in \cite{R3}.

Classical Analysis and ODEs · Mathematics 2018-10-08 Béchir Amri , Abdessalem Gasmi

In this paper, we present sharp estimates for the covering numbers of the embedding of the reproducing kernel Hilbert space (RKHS) associated with the Weierstrass fractal kernel into the space of continuous functions. The method we apply is…

Functional Analysis · Mathematics 2023-04-28 K. Gonzalez , D. Azevedo , T. Jordão

We prove sharp two-sided bounds of the fundamental solution for an integro-differential operator of order $\alpha \in (0,2)$ that generates a $d$-dimensional Markov process. The corresponding Dirichlet form is comparable to that of $d$…

Analysis of PDEs · Mathematics 2021-09-21 Moritz Kassmann , Kyung-Youn Kim , Takashi Kumagai

Random features have been introduced to scale up kernel methods via randomization techniques. In particular, random Fourier features and orthogonal random features were used to approximate the popular Gaussian kernel. Random Fourier…

Machine Learning · Computer Science 2024-10-22 Nizar Demni , Hachem Kadri

In this paper we construct the fundamental solution to some integro-differential equation, as well as the intrinsic upper and lower estimates for this solution. As an application of constructed estimates we state a criterion when a given…

Probability · Mathematics 2016-02-16 Victoria P. Knopova , Alexei M. Kulik

Simulating a Gaussian process requires sampling from a high-dimensional Gaussian distribution, which scales cubically with the number of sample locations. Spectral methods address this challenge by exploiting the Fourier representation,…

Machine Learning · Statistics 2026-02-27 Arsalan Jawaid , Abdullah Karatas , Jörg Seewig

Usually such area of mathematics as differential equations acts as a consumer of results given by functional analysis. This article will give an example of the reverse interaction of these two fields of knowledge. Namely, the derivation and…

Classical Analysis and ODEs · Mathematics 2026-05-14 Alexey Gorshkov

We obtain two-sided estimates for the heat kernel (or the fundamental function) associated with the following fractional Schr\"odinger operator with negative Hardy potential $$\Delta^{\alpha/2} -\lambda |x|^{-\alpha}$$ on $\RR^d$, where…

Probability · Mathematics 2018-09-18 Tomasz Jakubowski , Jian Wang

This study proposes a data condensation method for multivariate kernel density estimation by genetic algorithm. First, our proposed algorithm generates multiple subsamples of a given size with replacement from the original sample. The…

Methodology · Statistics 2022-03-04 Kiheiji Nishida