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We present an accurate and efficient method to calculate the effect of random fluctuations of the local field at the muon, for instance in the case muon diffusion, within the framework of the strong collision approximation. The method is…

Other Condensed Matter · Physics 2015-06-19 Giuseppe Allodi , Roberto De Renzi

The imaging sharpness of an X-ray telescope is chiefly determined by the optical quality of its focusing optics, which in turn mostly depends on the shape accuracy and the surface finishing of the grazing-incidence X-ray mirrors that…

Instrumentation and Methods for Astrophysics · Physics 2014-12-10 Lorenzo Raimondi , Daniele Spiga

In this paper we present a simple and effective method, based on appropriate superpositions of Bessel-Gauss beams, which in the Fresnel regime is able to describe in analytic form the 3D evolution of important waves as Bessel beams, plane…

Optics · Physics 2012-06-26 Michel Zamboni-Rached , Erasmo Recami , Massimo Balma

The image degradation produced by atmospheric turbulence and optical aberrations is usually alleviated using post-facto image reconstruction techniques, even when observing with adaptive optics systems. These techniques rely on the…

Instrumentation and Methods for Astrophysics · Physics 2015-05-18 A. Asensio Ramos , A. Lopez Ariste

Fourier series multiscale method, a concise and efficient analytical approach for multiscale computation, will be developed out of this series of papers. In the sixth paper, exact analysis of the wave propagation in a beam with rectangular…

Numerical Analysis · Mathematics 2022-08-30 Weiming Sun , Zimao Zhang

Computationally efficient numerical methods for high-order approximations of convolution integrals involving weakly singular kernels find many practical applications including those in the development of fast quadrature methods for…

Numerical Analysis · Mathematics 2018-10-10 Akash Anand , Awanish Kumar Tiwari

We consider a large class of physical fields $u$ written as double inverse Fourier transforms of some functions $F$ of two complex variables. Such integrals occur very often in practice, especially in diffraction theory. Our aim is to…

Analysis of PDEs · Mathematics 2022-10-18 Raphaël C. Assier , Andrey V. Shanin , Andrey I. Korolkov

In this work, we develop a method for rational approximation of the Fourier transform (FT) based on the real and imaginary parts of the complex error function \[ w(z) = e^{-z^2}(1 - {\rm{erf}}(-iz)) = K(x,y) + iL(x,y), \qquad z = x + iy, \]…

General Mathematics · Mathematics 2025-06-25 Sanjar M. Abrarov , Rehan Siddiqui , Rajinder K. Jagpal , Brendan M. Quine

Galaxy profile fitting is a ubiquitous technique that provides the backbone for photometric and morphological measurements in modern extragalactic surveys. A recent innovation in profile fitting algorithms is to render, or create, the model…

Instrumentation and Methods for Astrophysics · Physics 2026-04-17 Tim B. Miller , Imad Pasha

This work presents a method of computing Voigt functions and their derivatives, to high accuracy, on a uniform grid. It is based on an adaptation of Fourier-transform based convolution. The relative error of the result decreases as the…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Marcus H. Mendenhall

Paraxial diffraction modeling based on the Fourier transform has seen widespread implementation for simulating the response of a diffraction-limited optical system. For systems where the paraxial assumption is not sufficient, a class of…

In this paper, we consider a method for fast numerical computation of the Fourier transform of a slowly decaying function with given accuracy in given ranges of the frequency. In these decades, some useful formulas for the Fourier transform…

Numerical Analysis · Mathematics 2015-07-28 Ken'ichiro Tanaka

Scene reconstruction has emerged as a central challenge in computer vision, with approaches such as Neural Radiance Fields (NeRF) and Gaussian Splatting achieving remarkable progress. While Gaussian Splatting demonstrates strong performance…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Alexander Valverde , Brian Xu , Yuyin Zhou , Meng Xu , Hongyun Wang

This paper presents a family of Fourier eigenfunctions indexed by the space dimension d. These eigenfunctions are radial and built upon some generalized exponential integral function. For d=1,2,3, they are integrable or square integrable…

Classical Analysis and ODEs · Mathematics 2024-11-28 Rodolphe Garbit , Julien-Bilal Zinoune

2-D complex Gabor filtering has found numerous applications in the fields of computer vision and image processing. Especially, in some applications, it is often needed to compute 2-D complex Gabor filter bank consisting of the 2-D complex…

Computer Vision and Pattern Recognition · Computer Science 2017-04-19 Suhyuk Um , Jaeyoon Kim , Dongbo Min

We describe a method for calculating the roots of special functions satisfying second order linear ordinary differential equations. It exploits the recent observation that the solutions of a large class of such equations can be represented…

Numerical Analysis · Mathematics 2016-08-05 James Bremer

We present a numerical algorithm for evaluating the Boltzmann collision operator with $O(N^2)$ operations based on high order discontinuous Galerkin discretizations in the velocity variable. To formulate the approach, Galerkin projection of…

Numerical Analysis · Mathematics 2018-01-19 Alexander Alekseenko , Jeffrey Limbacher

This paper presents a 3D Gaussian Inverse Rendering (GIR) method, employing 3D Gaussian representations to effectively factorize the scene into material properties, light, and geometry. The key contributions lie in three-fold. We compute…

Computer Vision and Pattern Recognition · Computer Science 2024-08-16 Yahao Shi , Yanmin Wu , Chenming Wu , Xing Liu , Chen Zhao , Haocheng Feng , Jian Zhang , Bin Zhou , Errui Ding , Jingdong Wang

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

We introduce a class of algorithms for constructing Fourier representations of Gaussian processes in $1$ dimension that are valid over ranges of hyperparameter values. The scaling and frequencies of the Fourier basis functions are evaluated…

Computation · Statistics 2024-06-05 Philip Greengard
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