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We establish heat kernel upper bounds for a continuous-time random walk under unbounded conductances satisfying an integrability assumption, where we correct and extend recent results by the authors to a general class of speed measures. The…

Probability · Mathematics 2019-01-17 Sebastian Andres , Jean-Dominique Deuschel , Martin Slowik

In this paper we study the transition densities for a large class of non-symmetric Markov processes whose jumping kernels decay exponentially or subexponentially. We obtain their upper bounds which also decay at the same rate as their…

Probability · Mathematics 2018-01-03 Panki Kim , Jaehun Lee

Field-scale properties of fractured rocks play crucial role in many subsurface applications, yet methodologies for identification of the statistical parameters of a discrete fracture network (DFN) are scarce. We present an inversion…

Geophysics · Physics 2022-01-05 Zitong Zhou , Delphine Roubinet , Daniel M. Tartakovsky

We consider the formal SDE dX t = b(t, X t)dt + dZ t , X 0 = x $\in$ R d , (E) where b $\in$ L r ([0, T ], B $\beta$ p,q (R d , R d)) is a time-inhomogeneous Besov drift and Z t is a symmetric d-dimensional $\alpha$-stable process, $\alpha$…

Probability · Mathematics 2024-10-14 Mathis Fitoussi

We show that for a strongly local, regular symmetric Dirichlet form over a complete, locally compact geodesic metric space, full off-diagonal heat kernel estimates with walk dimension strictly larger than two (\emph{sub-Gaussian} estimates)…

Probability · Mathematics 2020-09-11 Naotaka Kajino , Mathav Murugan

We consider heat kernels on Weyl chambers corresponding to Laplacians subject to mixed Dirichlet-Neumann boundary conditions imposed on the boundary. Using purely analytic tools we prove genuinely sharp two-sided global estimates in the…

Analysis of PDEs · Mathematics 2024-08-08 Krzysztof Stempak

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 obtain heat kernel estimates for a class of fourth order non-uniformly elliptic operators in two dimensions. Contrary to existing results, the operators considered have symbols that are not strongly convex. This rises certain…

Analysis of PDEs · Mathematics 2022-11-22 Gerassimos Barbatis , Panagiotis Branikas

We give a direct proof of the sharp two-sided estimates, recently established in [4,9], for the Dirichlet heat kernel of the fractional Laplacian with gradient perturbation in $C^{1, 1}$ open sets by using Duhamel formula. We also obtain a…

Probability · Mathematics 2017-12-12 Peng Chen , Renming Song , Longjie Xie , Yingchao Xie

We introduce diffusion means as location statistics on manifold data spaces. A diffusion mean is defined as the starting point of an isotropic diffusion with a given diffusivity. They can therefore be defined on all spaces on which a…

Methodology · Statistics 2021-03-02 Pernille Hansen , Benjamin Eltzner , Stefan Sommer

This paper studies the empirical measures of eigenvalues and singular values for random matrices drawn from the heat kernel measures on the unitary groups $\mathbb{U}_N$ and the general linear groups $\mathbb{GL}_N$, for $N\in\mathbb{N}$.…

Probability · Mathematics 2013-06-11 Todd Kemp

We obtain sharp two-sided heat kernel estimates on spaces with varying dimension, in which two spaces of general dimension are connected at one point. On these spaces, if the dimensions of the two constituent parts are different, the volume…

Probability · Mathematics 2020-07-14 Takumu Ooi

We consider random walks in a balanced i.i.d. random environment in $Z^d$ for $d\ge2$ and the corresponding discrete non-divergence form difference operators. We first obtain an exponential integrability of the heat kernel bounds. We then…

Probability · Mathematics 2022-09-29 Xiaoqin Guo , Hung V. Tran

We present on-diagonal heat kernel estimates and quantitative homogenization statements for the one-dimensional Bouchaud trap model. The heat kernel estimates are obtained using standard techniques, with key inputs coming from a careful…

Probability · Mathematics 2024-03-11 Sebastian Andres , David A. Croydon , Takashi Kumagai

We consider a class of constant-coefficient partial differential operators on a finite-dimensional real vector space which exhibit a natural dilation invariance. Typically, these operators are anisotropic, allowing for different degrees in…

Analysis of PDEs · Mathematics 2020-01-22 Evan Randles , Laurent Saloff-Coste

This paper introduces a novel, non-deterministic method for embedding data in low-dimensional Euclidean space based on computing realizations of a Gaussian process depending on the geometry of the data. This type of embedding first appeared…

Machine Learning · Computer Science 2024-03-14 Anna C. Gilbert , Kevin O'Neill

The trace of the heat kernel in a (D+1)-dimensional Euclidean spacetime (integer D > 1) is used to derive the free energy in finite temperature field theory. The spacetime presents a D-dimensional compact space (domain) with a…

High Energy Physics - Theory · Physics 2016-12-12 Yuri V. Gusev

We study heat kernel estimates for symmetric pure jump processes on general metric measure spaces. Building on recent progress in the local setting due to S.~Eriksson-Bique, we develop a non-local version of the Whitney blending technique…

Probability · Mathematics 2026-02-09 Mathav Murugan

Permutation invariance is fundamental in molecular point-cloud generation, yet most diffusion models enforce it indirectly via permutation-equivariant networks on an ordered space. We propose to model diffusion directly on the quotient…

Machine Learning · Computer Science 2026-03-25 Gyeonghoon Ko , Juho Lee

In this article, we consider flat and curved Riemannian symmetric spaces in the complex case and we study their basic integral kernels, in potential and spherical analysis: heat, Newton, Poisson kernels and spherical functions, i.e. the…

Probability · Mathematics 2020-12-22 P. Graczyk , P. Sawyer
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