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Related papers: On Local Heat Kernel

200 papers

A Riemannian orbifold is a mildly singular generalization of a Riemannian manifold which is locally modeled on the quotient of a connected, open manifold under a finite group of isometries. If all of the isometries used to define the local…

Differential Geometry · Mathematics 2019-10-09 Sean Richardson , Elizabeth Stanhope

The paper deals with point-wise estimates for the heat kernel of a nonlocal convolution type operator with a kernel that decays at least exponentially at infinity. It is shown that the large time behaviour of the heat kernel depends…

Functional Analysis · Mathematics 2018-04-25 Alexander Grigoryan , Yury Kondratiev , Andrey Piatnitski , Elena Zhizhina

The asymptotic expansion of the heat kernel associated with Laplace operators is considered for general irreducible rank one locally symmetric spaces. Invariants of the Chern-Simons theory of irreducible U(n)- flat connections on real…

High Energy Physics - Theory · Physics 2009-11-07 A. A. Bytsenko

We present a brief overview of several approaches for calculating the local asymptotic expansion of the heat kernel for Laplace-type operators. The different methods developed in the papers of both authors some time ago are described in…

High Energy Physics - Theory · Physics 2007-05-23 Ivan G. Avramidi , Rainer Schimming

Recently proposed nonlocal and nonperturbative late time behavior of the heat kernel is generalized to curved spacetimes. Heat kernel trace asymptotics is dominated by two terms one of which represents a trivial covariantization of the…

High Energy Physics - Theory · Physics 2009-11-10 A. O. Barvinsky , Yu. V. Gusev , V. F. Mukhanov , D. V. Nesterov

We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression…

Computer Vision and Pattern Recognition · Computer Science 2016-06-30 Moo K. Chung , Anqi Qiu , Seongho Seo , Houri K. Vorperian

We explicitly construct a heat kernel as a Neumann series for certain function spaces, such as $L^{1}$, $L^{2}$, and Hilbert spaces, associated to a locally compact Hausdorff space $\mathfrak{X}$ with Borel $\sigma$-algebra $\mathcal{B}$,…

Classical Analysis and ODEs · Mathematics 2026-01-01 Palle Jorgensen , Jay Jorgenson , Lejla Smajlovic

In this paper, we firstly establish weighted heat kernel comparison theorems for the weighted heat equation on complete manifolds with radial curvatures bounded, and then by mainly using this conclusion, we can obtain two eigenvalue…

Differential Geometry · Mathematics 2026-03-19 Jing Mao

Asymptotic expansions of heat kernels and heat traces of Schr\"odinger operators on non-compact spaces are rarely explored, and even for cases as simple as $\mathbb{C}^n$ with (quasi-homogeneous) polynomials potentials, it's already very…

Differential Geometry · Mathematics 2020-11-12 Xianzhe Dai , Junrong Yan

We prove the existence and uniqueness of the Robin heat kernel on compact Riemannian manifolds with smooth boundary for Robin parameter $\alpha\in\mathbb{R}$, expressed as a spectral expansion in terms of Robin eigenvalues and…

Analysis of PDEs · Mathematics 2025-06-19 Yifeng Meng , Kui Wang

We study the existence and uniqueness of the heat kernel on infinite, locally finite, connected graphs. For general graphs, a uniqueness criterion, shown to be optimal, is given in terms of the maximal valence on spheres about a fixed…

Spectral Theory · Mathematics 2008-04-24 Radoslaw K. Wojciechowski

We establish an estimate for the fundamental solution of the heat equation on a closed Riemannian manifold $M$ of dimension at least 3, evolving under the Ricci flow. The estimate depends on some constants arising from a Sobolev imbedding…

Differential Geometry · Mathematics 2016-08-10 Mihai Bailesteanu

We prove heat kernel estimates for the $\bar\partial$-Neumann Laplacian acting in spaces of differential forms over noncompact, strongly pseudoconvex complex manifolds with a Lie group symmetry and compact quotient. We also relate our…

Spectral Theory · Mathematics 2012-05-29 Joe J. Perez , Peter Stollmann

The formulation of gauge theories on compact Riemannian manifolds with boundary leads to partial differential operators with Gilkey--Smith boundary conditions, whose peculiar property is the occurrence of both normal and tangential…

Mathematical Physics · Physics 2011-04-15 Ivan G. Avramidi , Giampiero Esposito

In this paper, we study the heat kernel associated to the intrinsic sublaplacian on a quaternionic contact manifold considered as a subriemannian manifold. More precisely, we explicitly compute the first two coefficients $c_0$ and $c_1$…

Differential Geometry · Mathematics 2021-03-02 Abdellah Laaroussi

We consider the asymptotic expansion of the heat kernel of a generalized Laplacian for $t\to 0^+$ and characterize the coefficients $a_k$ of this expansion by a natural intertwining property. In particular we will give a closed formula for…

Differential Geometry · Mathematics 2007-05-23 Gregor Weingart

The contributions to the heat kernel coefficients generated by the corners of the boundary are studied. For this purpose the internal and external sectors of a wedge and a cone are considered. These sectors are obtained by introducing,…

High Energy Physics - Theory · Physics 2017-08-23 V. V. Nesterenko , I. G. Pirozhenko , J. Dittrich

We derive a local Gaussian upper bound for the $f$-heat kernel on complete smooth metric measure space $(M,g,e^{-f}dv)$ with nonnegative Bakry-\'{E}mery Ricci curvature, which generalizes the classic Li-Yau estimate. As applications, we…

Differential Geometry · Mathematics 2015-09-08 Jia-Yong Wu , Peng Wu

We investigate heat kernel estimates of the form $p_{t}(x, x)\geq c_{x}t^{-\alpha},$ for large enough $t,$ where $\alpha$ and $c_{x}$ are positive reals and $c_{x}$ may depend on $x,$ on manifolds having at least one end.

Differential Geometry · Mathematics 2022-01-19 Alexander Grigor'yan , Philipp Sürig

Manifold learning is a fundamental problem in machine learning with numerous applications. Most of the existing methods directly learn the low-dimensional embedding of the data in some high-dimensional space, and usually lack the…

Machine Learning · Computer Science 2021-03-16 Yufan Zhou , Changyou Chen , Jinhui Xu