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We find asymptotic equalities for exact upper bounds of approximations by Fourier sums in uniform metric on classes of $2\pi$-periodic functions, representable in the form of convolutions of functions $\varphi$, which belong to unit balls…

Classical Analysis and ODEs · Mathematics 2016-03-08 A. S. Serdyuk , T. A. Stepaniuk

We propose and study a new quasi-interpolation method on spheres featuring the following two-phase construction and analysis. In Phase I, we analyze and characterize a large family of zonal kernels (e.g., the spherical version of Poisson…

Numerical Analysis · Mathematics 2025-08-27 Zhengjie Sun , Wenwu Gao , Xingping Sun

We present a super-high-efficiency approximate computing scheme for series sum and discrete Fourier transform. The summation of a series sum or a discrete Fourier transform is approximated by summing over part of the terms multiplied by…

Numerical Analysis · Mathematics 2013-12-09 Xin-Zhong Yan

We discuss efficient algorithms for the accurate forward and reverse evaluation of the discrete Fourier-Bessel transform (dFBT) as numerical tools to assist in the 2D polar convolution of two radially symmetric functions, relevant, e.g., to…

Computational Physics · Physics 2016-11-08 O. Melchert , M. Wollweber , B. Roth

We consider a polynomial reconstruction of smooth functions from their noisy values at discrete nodes on the unit sphere by a variant of the regularized least-squares method of An et al., SIAM J. Numer. Anal. 50 (2012), 1513--1534. As nodes…

Numerical Analysis · Mathematics 2015-01-12 Sergei. V. Pereverzyev , Ian. H. Sloan , Pavlo Tkachenko

Probabilistic graphical models have emerged as a powerful modeling tool for several real-world scenarios where one needs to reason under uncertainty. A graphical model's partition function is a central quantity of interest, and its…

Artificial Intelligence · Computer Science 2021-05-25 Durgesh Agrawal , Yash Pote , Kuldeep S Meel

For many fundamental problems in computational topology, such as unknot recognition and $3$-sphere recognition, the existence of a polynomial-time solution remains unknown. A major algorithmic tool behind some of the best known algorithms…

Computational Geometry · Computer Science 2024-03-08 Benjamin A. Burton , Alexander He

We present in this paper algorithms for solving stiff PDEs on the unit sphere with spectral accuracy in space and fourth-order accuracy in time. These are based on a variant of the double Fourier sphere method in coefficient space with…

Numerical Analysis · Mathematics 2017-12-27 Hadrien Montanelli , Yuji Nakatsukasa

Solving a Poisson equation is generally reduced to solving a linear system with a coefficient matrix $A$ of entries $a_{ij}$, $i,j=1,2,...,n$, from the discretized Poisson equation. Although the variational quantum algorithms are promising…

Quantum Physics · Physics 2023-09-25 Hui-Min Li , Zhi-Xi Wang , Shao-Ming Fei

In this paper a local approximation method on the sphere is presented. As interpolation scheme we consider a partition of unity method, such as the modified spherical Shepard's method, which uses zonal basis functions (ZBFs) plus spherical…

Numerical Analysis · Mathematics 2014-04-08 Alessandra De Rossi

We present a general method for accelerating by more than an order of magnitude the convolution of pixelated function on the sphere with a radially-symmetric kernel. Our method splits the kernel into a compact real-space, and a compact…

Instrumentation and Methods for Astrophysics · Physics 2012-11-16 P. M. Sutter , Benjamin D. Wandelt , Franz Elsner

A common strategy in the numerical solution of partial differential equations is to define a uniform discretization of a tensor-product multi-dimensional logical domain, which is mapped to a physical domain through a given coordinate…

Computational Physics · Physics 2019-09-13 Edoardo Zoni , Yaman Güçlü

Acceleration of algorithms is becoming a crucial problem, if larger data sets are to be processed. Evaluation of algorithms is mostly done by using computational geometry approach and evaluation of computational complexity. However in…

Computational Geometry · Computer Science 2022-08-29 Vaclav Skala

This article introduces a functional method for lower-dimensional smooth representations in terms of time-varying dissimilarities. The method incorporates dissimilarity representation in multidimensional scaling and smoothness approach of…

Methodology · Statistics 2025-05-02 Liting Li

We provide an explicit geometric algorithm involving only ruler and compass constructions in order to specify the specular reflection point on the surface of a reflecting sphere of radius $r$ given two focal points $A$ and $B$ lying outside…

History and Overview · Mathematics 2017-03-21 Nikolaos K. Kollas

We introduce a fast algorithm for computing sparse Fourier transforms supported on smooth curves or surfaces. This problem appear naturally in several important problems in wave scattering and reflection seismology. The main observation is…

Numerical Analysis · Mathematics 2008-01-11 Lexing Ying

We review existing methods for implementing smooth functions f(A) of a sparse Hermitian matrix A on a quantum computer, and analyse a further combination of these techniques which has some advantages of simplicity and resource consumption…

Quantum Physics · Physics 2019-08-23 Sathyawageeswar Subramanian , Steve Brierley , Richard Jozsa

This work provides a computationally efficient and statistically consistent moment-based estimator for mixtures of spherical Gaussians. Under the condition that component means are in general position, a simple spectral decomposition…

Machine Learning · Computer Science 2012-10-30 Daniel Hsu , Sham M. Kakade

The pseudospherical functions on one-sheet, two-dimensional hyperboloid are discussed. The simplest method of construction of these functions is introduced using the Fock space structure of the representation space of the su(1,1) algebra.…

Mathematical Physics · Physics 2015-05-27 K. Kowalski , J. Rembielinski , A. Szczesniak

Gaussian processes are popular and flexible models for spatial, temporal, and functional data, but they are computationally infeasible for large datasets. We discuss Gaussian-process approximations that use basis functions at multiple…

Methodology · Statistics 2020-12-22 Matthias Katzfuss , Wenlong Gong
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