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Related papers: Green's kernels for transmission problems in bodie…

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We construct an asymptotic approximation to the solution of a transmission problem for a body containing a region occupied by many small inclusions. The cluster of inclusions is characterised by two small parameters that determine the…

Analysis of PDEs · Mathematics 2016-07-22 Michael Nieves

Given a sequence of regular planar domains converging in the sense of kernel, we prove that the corresponding Green's functions converge uniformly on the complex sphere, provided the limit domain is also regular, and the connectivity is…

Complex Variables · Mathematics 2019-02-19 Sergei Kalmykov , Leonid V. Kovalev

Asymptotic formulae for Green's kernels $G_\epsilon({\bf x}, {\bf y})$ of various boundary value problems for the Laplace operator are obtained in regularly perturbed domains and certain domains with small singular perturbations of the…

Analysis of PDEs · Mathematics 2007-05-23 Vladimir Maz'ya , Alexander B. Movchan

A kernel based procedure for correcting experimental data for distortions due to the finite resolution and limited detector acceptance is presented. The unfolding problem is known to be an ill-posed problem that can not be solved without…

Data Analysis, Statistics and Probability · Physics 2012-09-19 N. D. Gagunashvili , M. Schmelling

We propose a highly efficient numerical method to describe inhomogeneous superconductivity by using the kernel polynomial method in order to calculate the Green's functions of a superconductor. Broken translational invariance of any type…

Superconductivity · Physics 2010-10-13 L. Covaci , F. M. Peeters , M. Berciu

Selecting optimal kernels for regression in physical systems remains a challenge, often relying on trial-and-error with standard functions. In this work, we establish a mathematical correspondence between support vector machine kernels and…

Quantum Physics · Physics 2026-01-05 Nan-Hong Kuo , Renata Wong

This note proposes rapidly convergent computational formulae for evaluating scattering kernels from radiative transfer theory. The approach used here does not rely on Legendre expansions, but rather uses exponentially convergent numerical…

Numerical Analysis · Mathematics 2015-12-09 Hans Engler

Representing spectral densities, real-frequency, and real-time Green's functions of continuous systems by a small discrete set of complex poles is an ubiquitous problem in condensed matter physics, with applications ranging from quantum…

Strongly Correlated Electrons · Physics 2025-06-04 Lei Zhang , André Erpenbeck , Yang Yu , Emanuel Gull

Asymptotic expansions of Green functions and spectral densities associated with partial differential operators are widely applied in quantum field theory and elsewhere. The mathematical properties of these expansions can be clarified and…

funct-an · Mathematics 2007-05-23 R. Estrada , S. A. Fulling

We consider a two-dimensional diffusion process in a two-layered plane, governed by distinct covariance matrices in the upper and lower half-planes and by two drift vectors pointed away from the $x$-axis. We first analyze the case where the…

Probability · Mathematics 2025-12-11 Sandro Franceschi , Irina Kourkova , Maxence Petit

Machine learning methods are applied to finding the Green's function of the Anderson impurity model, a basic model system of quantum many-body condensed-matter physics. Different methods of parametrizing the Green's function are…

Strongly Correlated Electrons · Physics 2015-06-22 Louis-François Arsenault , Alejandro Lopez-Bezanilla , O. Anatole von Lilienfeld , Andrew J. Millis

As a main result of the paper, we construct and justify an asymptotic approximation of Green's function in a domain with many small inclusions. Periodicity of the array of inclusions is not required. We start with an analysis of the…

Analysis of PDEs · Mathematics 2009-04-14 V. Maz'ya , A. Movchan

Kernel means are frequently used to represent probability distributions in machine learning problems. In particular, the well known kernel density estimator and the kernel mean embedding both have the form of a kernel mean. Unfortunately,…

Machine Learning · Statistics 2015-03-03 E. Cruz Cortés , C. Scott

We present a general representation for solving problems in many-body perturbation theory. By projecting the single-particle Green's function to an auxiliary space we show how one can convert an arbitrary Feynman graph to a universal kernel…

Strongly Correlated Electrons · Physics 2025-11-05 Daria Gazizova , Rayan Farid , B. D. E. McNiven , I. Assi , Ethan G. Armstrong , J. P. F. LeBlanc

We describe a method to prove new integral inequalities for stable minimal hypersurfaces in Euclidean space. As an application, we give a simple proof that complete, two sided, stable minimal hypersurfaces in $\mathbb{R}^4$ are hyperplanes.…

Differential Geometry · Mathematics 2026-04-17 Xavier Cabre , Giovanni Catino , Luciano Mari , Paolo Mastrolia , Alberto Roncoroni

Inspired by the recent proposed Legendre orthogonal polynomial representation of imaginary-time Green's functions, we develop an alternate representation for the Green's functions of quantum impurity models and combine it with the…

Strongly Correlated Electrons · Physics 2016-12-08 Li Huang , Liang Du

An integral formulation for acoustic radiation in moving flows is presented. It is based on a potential formulation for acoustic radiation on weakly non-uniform subsonic mean flows. This work is motivated by the absence of suitable kernels…

Fluid Dynamics · Physics 2016-09-13 Simone Mancini , R. Jeremy Astley , Samuel Sinayoko , Gwenael Gabard , Michel Tournour

A domain integral method employing a specific Green's function (i.e., incorporating some features of the global problem of wave propagation in an inhomogeneous medium) is developed for solving direct and inverse scattering problems relative…

Crosscorrelation structures in the Green function retrieval by crosscorrelating wavefields are revealed using rigorous mathematical theory on integral equations. The previous practice on extracting the Green function by crosscorrelating the…

Classical Physics · Physics 2009-10-07 Yingcai Zheng

We propose non-stationary spectral kernels for Gaussian process regression. We propose to model the spectral density of a non-stationary kernel function as a mixture of input-dependent Gaussian process frequency density surfaces. We solve…

Machine Learning · Statistics 2019-09-25 Sami Remes , Markus Heinonen , Samuel Kaski
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