Fast algorithms using orthogonal polynomials

IF 16.3 1区 数学 Q1 MATHEMATICS Acta Numerica Pub Date : 2020-05-01 DOI:10.1017/S0962492920000045
S. Olver, R. Slevinsky, Alex Townsend
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引用次数: 29

Abstract

We review recent advances in algorithms for quadrature, transforms, differential equations and singular integral equations using orthogonal polynomials. Quadrature based on asymptotics has facilitated optimal complexity quadrature rules, allowing for efficient computation of quadrature rules with millions of nodes. Transforms based on rank structures in change-of-basis operators allow for quasi-optimal complexity, including in multivariate settings such as on triangles and for spherical harmonics. Ordinary and partial differential equations can be solved via sparse linear algebra when set up using orthogonal polynomials as a basis, provided that care is taken with the weights of orthogonality. A similar idea, together with low-rank approximation, gives an efficient method for solving singular integral equations. These techniques can be combined to produce high-performance codes for a wide range of problems that appear in applications.
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使用正交多项式的快速算法
我们回顾了正交多项式在求积、变换、微分方程和奇异积分方程算法方面的最新进展。基于渐近线的求积促进了最优复杂度求积规则,允许使用数百万节点高效计算求积规则。基于变基算子中的秩结构的变换允许准最优复杂度,包括在多变量设置中,如三角形和球面谐波。当使用正交多项式作为基础建立常微分方程和偏微分方程时,只要注意正交性的权重,就可以通过稀疏线性代数来求解。类似的思想,结合低阶近似,给出了一种求解奇异积分方程的有效方法。这些技术可以结合起来,为应用程序中出现的各种问题生成高性能代码。
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来源期刊
Acta Numerica
Acta Numerica MATHEMATICS-
CiteScore
26.00
自引率
0.70%
发文量
7
期刊介绍: Acta Numerica stands as the preeminent mathematics journal, ranking highest in both Impact Factor and MCQ metrics. This annual journal features a collection of review articles that showcase survey papers authored by prominent researchers in numerical analysis, scientific computing, and computational mathematics. These papers deliver comprehensive overviews of recent advances, offering state-of-the-art techniques and analyses. Encompassing the entirety of numerical analysis, the articles are crafted in an accessible style, catering to researchers at all levels and serving as valuable teaching aids for advanced instruction. The broad subject areas covered include computational methods in linear algebra, optimization, ordinary and partial differential equations, approximation theory, stochastic analysis, nonlinear dynamical systems, as well as the application of computational techniques in science and engineering. Acta Numerica also delves into the mathematical theory underpinning numerical methods, making it a versatile and authoritative resource in the field of mathematics.
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