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In this paper we continue the analysis of spectral problems in the setting of complete manifolds with fibred boundary metrics, also referred to as $\phi$-metrics, as initiated in our previous work. We consider the Hodge Laplacian for a…

Differential Geometry · Mathematics 2021-11-05 Mohammad Talebi , Boris Vertman

We obtain Gaussian upper bounds for heat kernels of higher order differential operators with Dirichlet boundary conditions on bounded domains in $\R^N$. The bounds exhibit explicitly the nature of the spatial decay of the heat kernel close…

Analysis of PDEs · Mathematics 2012-08-01 Narinder Claire

We study the boundary trace processes of reflected diffusions on uniform domains. We obtain stable-like heat kernel estimates for such a boundary trace process when the diffusion on the underlying ambient space satisfies sub-Gaussian heat…

Probability · Mathematics 2025-02-24 Naotaka Kajino , Mathav Murugan

We present new gradient estimates and Harnack inequalities for positive solutions to nonlinear slow diffusion equations. The framework is that of a smooth metric measure space $(\mathscr M,g,d\mu)$ with invariant weighted measure…

Analysis of PDEs · Mathematics 2025-05-21 Ali Taheri , Vahideh Vahidifar

Working within the framework of the covariant perturbation theory, we obtain the coincidence limit of the heat kernel of an elliptic second order differential operator that is applicable to a large class of quantum field theories. The basis…

High Energy Physics - Theory · Physics 2008-12-18 Yuri V. Gusev

We prove heat kernel bounds for the operator (1 + |x|^{\alpha})\Delta in R^N, through Nash inequalities and weighted Hardy inequalities.

Analysis of PDEs · Mathematics 2011-01-21 Giorgio Metafune , Chiara Spina

A new algebraic approach for calculating the heat kernel for the Laplace operator on any Riemannian manifold with covariantly constant curvature is proposed. It is shown that the heat kernel operator can be obtained by an averaging over the…

High Energy Physics - Theory · Physics 2008-11-26 Ivan G. Avramidi

We construct the fundamental solution (the heat kernel) $p^{\kappa}$ to the equation $\partial_t=\mathcal{L}^{\kappa}$, where under certain assumptions the operator $\mathcal{L}^{\kappa}$ takes one of the following forms, \begin{align*}…

Analysis of PDEs · Mathematics 2018-04-05 Tomasz Grzywny , Karol Szczypkowski

We prove a variant of the Davies-Gaffney-Grigor'yan Lemma for the continuous time heat kernel on graphs. We use it together with the Li-Yau inequality to obtain strong heat kernel estimates for graphs satisfying the exponential curvature…

Differential Geometry · Mathematics 2015-11-30 Frank Bauer , Bobo Hua , Shing-Tung Yau

Being motivated by physical applications (as the phi^4 model) we calculate the heat kernel coefficients for generalised Laplacians on the Moyal plane containing both left and right multiplications. We found both star-local and star-nonlocal…

High Energy Physics - Theory · Physics 2009-11-11 Dmitri V. Vassilevich

Let $S$ be a compact hyperbolic surface of genus $g\geq 2$ and let $I(S) = \frac{1}{\mathrm{Vol}(S)}\int_{S} \frac{1}{\mathrm{Inj}(x)^2 \wedge 1} dx$, where $\mathrm{Inj}(x)$ is the injectivity radius at $x$. We prove that for any $k\in…

Spectral Theory · Mathematics 2025-04-30 Renan Gross , Guy Lachman , Asaf Nachmias

Let $\displaystyle L = -\frac{1}{w} \, \mathrm{div}(A \, \nabla u) + \mu$ be the generalized degenerate Schr\"odinger operator in $L^2_w(\mathbb{R}^d)$ with $d\ge 3$ with suitable weight $w$ and measure $\mu$. The main aim of this paper is…

Functional Analysis · Mathematics 2020-09-08 The Anh Bui , Tan Duc Do , Nguyen Ngoc Trong

Results regarding off-diagonal Gaussian upper heat kernel bounds on discrete weighted graphs with possibly unbounded geometry are summarized and related. After reviewing uniform upper heat kernel bounds obtained by Carlen, Kusuoka, and…

Analysis of PDEs · Mathematics 2025-02-28 Christian Rose

We consider a self-adjoint non-negative operator $H$ in a Hilbert space $\mathsf{L}^2(X,{\rm d}\mu)$. We assume that the semigroup $(\mathrm{e}^{-t H})_{t>0}$ is defined by an integral kernel, $p$, which allows an estimate of the form…

Spectral Theory · Mathematics 2016-06-03 Jochen Brüning , Batu Güneysu

In this work, we establish a new characterization of sub-Gaussian heat kernel estimates for strongly local regular Dirichlet forms on metric measure spaces. Our formulation is based on the newly introduced cutoff energy condition, which…

Probability · Mathematics 2025-10-08 Riku Anttila

We consider a complete noncompact smooth Riemannian manifold $M$ with a weighted measure and the associated drifting Laplacian. We demonstrate that whenever the $q$-Bakry-\'Emery Ricci tensor on $M$ is bounded below, then we can obtain an…

Differential Geometry · Mathematics 2013-04-18 Nelia Charalambous , Zhiqin Lu

We prove the Li-Yau gradient estimate for the heat kernel on graphs. The only assumption is a variant of the curvature-dimension inequality, which is purely local, and can be considered as a new notion of curvature for graphs. We compute…

Analysis of PDEs · Mathematics 2015-12-02 Frank Bauer , Paul Horn , Yong Lin , Gabor Lippner , Dan Mangoubi , Shing-Tung Yau

Let $(X,d,\mu)$ be a doubling metric measure space endowed with a Dirichlet form $\E$ deriving from a "carr\'e du champ". Assume that $(X,d,\mu,\E)$ supports a scale-invariant $L^2$-Poincar\'e inequality. In this article, we study the…

Metric Geometry · Mathematics 2017-10-03 Thierry Coulhon , Renjin Jiang , Pekka Koskela , Adam Sikora

We study the low-energy approximation for calculation of the heat kernel which is determined by the strong slowly varying background fields in strongly curved quasi-homogeneous manifolds. A new covariant algebraic approach, based on taking…

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

Many contemporary statistical learning methods assume a Euclidean feature space. This paper presents a method for defining similarity based on hyperspherical geometry and shows that it often improves the performance of support vector…

Machine Learning · Statistics 2018-08-07 Chenchao Zhao , Jun S. Song
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