计算高振荡积分的加速Levin-Clenshaw-Curtis方法。

IF 1.7 3区 数学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
BIT Numerical Mathematics Pub Date : 2025-01-01 Epub Date: 2025-08-11 DOI:10.1007/s10543-025-01079-4
Arieh Iserles, Georg Maierhofer
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引用次数: 0

摘要

高振荡积分的有效逼近在广泛的应用中起着重要的作用。虽然传统的正交法在高频区域变得非常昂贵,但Levin方法提供了一种在许多情况下以均匀成本近似这些积分的方法。在这项工作中,我们提出了Levin方法的加速版本,该方法可以应用于广泛的物理上重要的振荡积分,通过利用切比雪夫多项式基础上某些微分算子的带状作用。我们提出的Levin方法的版本基本上可以用与在正交点上进行快速傅立叶变换相同的成本来计算,并且在手稿中明确说明了成本对许多附加参数的依赖。这比目前先进的莱文方法的直接计算速度有了显著的提高。我们概述了这种加速方法对相当广泛的一类积分的构造,并用一些说明性的数值例子来支持我们的理论描述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An accelerated Levin-Clenshaw-Curtis method for the evaluation of highly oscillatory integrals.

The efficient approximation of highly oscillatory integrals plays an important role in a wide range of applications. Whilst traditional quadrature becomes prohibitively expensive in the high-frequency regime, Levin methods provide a way to approximate these integrals in many settings at uniform cost. In this work, we present an accelerated version of Levin methods that can be applied to a wide range of physically important oscillatory integrals, by exploiting the banded action of certain differential operators on a Chebyshev polynomial basis. Our proposed version of the Levin method can be computed essentially in the same cost as a Fast Fourier Transform in the quadrature points and the dependence of the cost on a number of additional parameters is made explicit in the manuscript. This presents a significant speed-up over the direct computation of the Levin method in current state-of-the-art. We outline the construction of this accelerated method for a fairly broad class of integrals and support our theoretical description with a number of illustrative numerical examples.

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来源期刊
BIT Numerical Mathematics
BIT Numerical Mathematics 数学-计算机:软件工程
CiteScore
2.90
自引率
0.00%
发文量
38
审稿时长
6 months
期刊介绍: The journal BIT has been published since 1961. BIT publishes original research papers in the rapidly developing field of numerical analysis. The essential areas covered by BIT are development and analysis of numerical methods as well as the design and use of algorithms for scientific computing. Topics emphasized by BIT include numerical methods in approximation, linear algebra, and ordinary and partial differential equations.
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