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We propose two easy-to-implement fast algorithms based on moment-matching to compute the nonlocal potential $\varphi(\textbf{x})=(U\ast \rho)(\textbf{x})$ on bounded domain, where the kernel $U$ is singular at the origin and the density…

Numerical Analysis · Mathematics 2026-02-16 Xin Liu , Qinglin Tang , Yong Zhang

We present a spectrally accurate, efficient FFT-based method for the three-dimensional free-space Poisson equation with smooth, compactly supported sources. The method adopts a super-potential formulation: we first compute the convolution…

Computational Physics · Physics 2025-09-22 Lukas Exl , Sebastian Schaffer

The convolution potential arises in a wide variety of application areas, and its efficient and accurate evaluation encounters three challenges: singularity, nonlocality and anisotropy. We introduce a fast algorithm based on a far-field…

Numerical Analysis · Mathematics 2025-04-29 Xin Liu , Yong Zhang

In this article, we present an $O(N \log N)$ rapidly convergent algorithm for the numerical approximation of the convolution integral with radially symmetric weakly singular kernels and compactly supported densities. To achieve the reduced…

Numerical Analysis · Mathematics 2021-07-09 Awanish Kumar Tiwari , Ambuj Pandey , Jagabandhu Paul , Akash Anand

We provide faster algorithms for the problem of Gaussian summation, which occurs in many machine learning methods. We develop two new extensions - an O(Dp) Taylor expansion for the Gaussian kernel with rigorous error bounds and a new error…

Machine Learning · Computer Science 2012-07-02 Dongryeol Lee , Alexander G. Gray

The quasi-2D electrostatic systems, characterized by periodicity in two dimensions with a free third dimension, have garnered significant interest in many fields. We apply the sum-of-Gaussians (SOG) approximation to the Laplace kernel,…

Numerical Analysis · Mathematics 2024-12-09 Xuanzhao Gao , Shidong Jiang , Jiuyang Liang , Zhenli Xu , Qi Zhou

We investigate training and using Gaussian kernel SVMs by approximating the kernel with an explicit finite- dimensional polynomial feature representation based on the Taylor expansion of the exponential. Although not as efficient as the…

Artificial Intelligence · Computer Science 2011-09-22 Andrew Cotter , Joseph Keshet , Nathan Srebro

It was demonstrated in earlier work that, by approximating its range kernel using shiftable functions, the non-linear bilateral filter can be computed using a series of fast convolutions. Previous approaches based on shiftable approximation…

Computer Vision and Pattern Recognition · Computer Science 2016-04-20 Sanjay Ghosh , Kunal N. Chaudhury

Over the last two decades, several fast, robust, and high-order accurate methods have been developed for solving the Poisson equation in complicated geometry using potential theory. In this approach, rather than discretizing the partial…

Numerical Analysis · Mathematics 2024-09-19 Fredrik Fryklund , Leslie Greengard , Shidong Jiang , Samuel Potter

Exploratory variational pseudopotential density functional calculations are performed for the electronic properties of many-electron systems in the 3D cartesian coordinate grid (CCG). The atom-centered localized gaussian basis set,…

Chemical Physics · Physics 2015-05-18 Amlan K Roy

We present a fast and accurate algorithm for the evaluation of nonlocal (long-range) Coulomb and dipole-dipole interactions in free space. The governing potential is simply the convolution of an interaction kernel $U(\bx)$ and a density…

Numerical Analysis · Mathematics 2014-10-07 Shidong Jiang , Leslie Greengard , Weizhu Bao

This paper presents a simple and efficient method to convolve an image with a Gaussian kernel. The computation is performed in a constant number of operations per pixel using running sums along the image rows and columns. We investigate the…

Computer Vision and Pattern Recognition · Computer Science 2011-07-26 Elhanan Elboher , Michael Werman

We present an approximate calculation of the full Bayesian posterior probability distribution for the local non-Gaussianity parameter $f_{\text{nl}}$ from observations of cosmic microwave background anisotropies within the framework of…

Cosmology and Nongalactic Astrophysics · Physics 2013-11-14 Sebastian Dorn , Niels Oppermann , Rishi Khatri , Marco Selig , Torsten A. Enßlin

Simulating a Gaussian process requires sampling from a high-dimensional Gaussian distribution, which scales cubically with the number of sample locations. Spectral methods address this challenge by exploiting the Fourier representation,…

Machine Learning · Statistics 2026-02-27 Arsalan Jawaid , Abdullah Karatas , Jörg Seewig

In this paper, we propose a method to approximate the Gaussian function on ${\mathbb R}$ by a short cosine sum. We generalise and extend the differential approximation method proposed in [4, 40] to approximate $\mathrm{e}^{-t^{2}/2\sigma}$…

Numerical Analysis · Mathematics 2025-05-23 Nadiia Derevianko , Gerlind Plonka

It is well-known that non-linear approximation has an advantage over linear schemes in the sense that it provides comparable approximation rates to those of the linear schemes, but to a larger class of approximands. This was established for…

Classical Analysis and ODEs · Mathematics 2010-04-28 Thomas Hangelbroek , Amos Ron

We present an efficient algorithm for the all-electron periodic Coulomb matrix based on the Ewald summation combined with the Fourier-transformed Coulomb method. The short-range contributions involving compact densities are evaluated in…

Chemical Physics · Physics 2025-09-23 Hieu Q. Dinh , Adam Rettig , Xintian Feng , Joonho Lee

We implement an efficient method of computation of two dimensional Fourier-type integrals based on approximation of the integrand by Gaussian radial basis functions, which constitute a standard tool in approximation theory. As a result, we…

Numerical Analysis · Mathematics 2022-02-07 A. Martinez-Finkelshtein , D. Ramos-Lopez , D. R. Iskander

The kernel truncation method (KTM) is a commonly-used algorithm to compute the convolution-type nonlocal potential $\Phi(x)=(U\ast \rho)(x), ~x \in {\mathbb R^d}$, where the convolution kernel $U(x)$ might be singular at the origin and/or…

Numerical Analysis · Mathematics 2022-09-27 Xin Liu , Qinglin Tang , Shaobo Zhang , Yong Zhang

An efficient solver for the three dimensional free-space Poisson equation is presented. The underlying numerical method is based on finite Fourier series approximation. While the error of all involved approximations can be fully controlled,…

Computational Physics · Physics 2017-10-18 Lukas Exl
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