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Related papers: Heat kernel coefficients for compact fuzzy spaces

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Classical and non classical Besov and Triebel-Lizorkin spaces with complete range of indices are developed in the general setting of Dirichlet space with a doubling measure and local scale-invariant Poincar\'e inequality. This leads to Heat…

Functional Analysis · Mathematics 2014-06-10 Gerard Kerkyacharian , Pencho Petrushev

We review the status of covariant methods in quantum field theory and quantum gravity, in particular, some recent progress in the calculation of the effective action via the heat kernel method. We study the heat kernel associated with an…

High Energy Physics - Theory · Physics 2014-06-06 Ivan G. Avramidi

Let $G$ be a simple, finite graph and let $p_t(x,y)$ denote the heat kernel on $G$. The purpose of this short note is to show that for $t \rightarrow 0^+$ $$ p_t(x,y) = \# \left\{\mbox{paths of…

Analysis of PDEs · Mathematics 2019-05-21 Stefan Steinerberger

We analyze gauge theories based on abelian $p-$forms in real compact hyperbolic manifolds. The explicit thermodynamic functions associated with skew--symmetric tensor fields are obtained via zeta--function regularization and the trace…

High Energy Physics - Theory · Physics 2007-05-23 A. A. Bytsenko , V. S. Mendes , A. C. Tort

Using index-free notation, we present the diagonal values of the first five heat kernel coefficients associated with a general Laplace-type operator on a compact Riemannian space without boundary. The fifth coefficient appears here for the…

High Energy Physics - Theory · Physics 2014-11-18 Anton E. M. van de Ven

Using our recently proposed covariant algebraic approach the heat kernel for a Laplace-like differential operator in low-energy approximation is studied. Neglecting all the covariant derivatives of the gauge field strength (Yang-Mills…

High Energy Physics - Theory · Physics 2009-10-28 I. G. Avramidi

An overview about recent progress in the calculation of the heat kernel and the one-loop effective action in quantum gravity and gauge theories is given. We analyse the general structure of the standard Schwinger-De Witt asymptotic…

General Relativity and Quantum Cosmology · Physics 2007-05-23 I. G. Avramidi

The heat kernel on the symmetric space of positive definite Hermitian matrices is used to endow the spaces of Bergman metrics of degree k on a Riemann surface M with a family of probability measures depending on a choice of the background…

Probability · Mathematics 2016-08-10 Semyon Klevtsov , Steve Zelditch

In this paper, we show that efficient separated sum-of-exponentials approximations can be constructed for the heat kernel in any dimension. In one space dimension, the heat kernel admits an approximation involving a number of terms that is…

Numerical Analysis · Mathematics 2013-08-20 Shidong Jiang , Leslie Greengard , Shaobo Wang

Let $X$ be an abstract orientable not necessarily compact CR manifold of dimension $2n+1$, $n\geq1$, and let $L^k$ be the $k$-th tensor power of a CR complex line bundle $L$ over $X$. Suppose that condition $Y(q)$ holds at each point of…

Complex Variables · Mathematics 2021-08-04 Chin-Yu Hsiao , Weixia Zhu

We compute the coefficients in asymptotics of regularized traces and associated trace (spectral) distributions for Schrodinger operators, with short and long range potentials. A kernel expansion for the Schrodinger semigroup is derived, and…

Spectral Theory · Mathematics 2007-05-23 Michael Hitrik , Iosif Polterovich

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

In this paper, we establish existence and uniqueness of weak solutions to general time fractional equations and give their probabilistic representations. We then derive sharp two-sided estimates for fundamental solutions of a family of time…

Probability · Mathematics 2017-09-12 Zhen-Qing Chen , Panki Kim , Takashi Kumagai , Jian Wang

By using ideas and strong results borrowed from the classical moment problem, we show how -under very general conditions- a discrete number of values of the spectral zeta function (associated generically with a non-decreasing sequence of…

Mathematical Physics · Physics 2007-05-23 M. Tierz , E. Elizalde

We build a systematic calculational method for the covariant expansion of the two-point heat kernel $\hat K(\tau|x,x')$ for generic minimal and non-minimal differential operators of any order. This is the expansion in powers of dimensional…

High Energy Physics - Theory · Physics 2022-03-31 Andrei O. Barvinsky , Wladyslaw Wachowski

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

Standard thermodynamic treatments of quantum field theory in the presence of black-hole backgrounds reproduce the black hole entropy by usually specializing to the leading order of the heat-kernel or the high-temperature expansion. By…

High Energy Physics - Theory · Physics 2009-06-19 Horacio E. Camblong , Carlos R. Ordonez

The heat kernel in the setting of classical Fourier-Bessel expansions is defined by an oscillatory series which cannot be computed explicitly. We prove qualitatively sharp estimates of this kernel. Our method relies on establishing a…

Classical Analysis and ODEs · Mathematics 2014-02-12 Adam Nowak , Luz Roncal

We consider the asymptotics of the discrete heat kernel on isoradial graphs for the case where the time and the edge lengths tend to zero simultaneously. Depending on the asymptotic ratio between time and edge lengths, we show that two…

Probability · Mathematics 2024-01-24 Simon Schwarz , Anja Sturm , Max Wardetzky

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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