Splitting methods for differential equations

IF 16.3 1区 数学 Q1 MATHEMATICS Acta Numerica Pub Date : 2024-09-04 DOI:10.1017/s0962492923000077
Sergio Blanes, Fernando Casas, Ander Murua
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Abstract

This overview is devoted to splitting methods, a class of numerical integrators intended for differential equations that can be subdivided into different problems easier to solve than the original system. Closely connected with this class of integrators are composition methods, in which one or several low-order schemes are composed to construct higher-order numerical approximations to the exact solution. We analyse in detail the order conditions that have to be satisfied by these classes of methods to achieve a given order, and provide some insight about their qualitative properties in connection with geometric numerical integration and the treatment of highly oscillatory problems. Since splitting methods have received considerable attention in the realm of partial differential equations, we also cover this subject in the present survey, with special attention to parabolic equations and their problems. An exhaustive list of methods of different orders is collected and tested on simple examples. Finally, some applications of splitting methods in different areas, ranging from celestial mechanics to statistics, are also provided.

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微分方程的分割方法
本综述主要介绍拆分方法,这是一类数值积分方法,适用于可细分为比原始系统更易求解的不同问题的微分方程。与这一类积分器密切相关的是组合方法,其中一个或多个低阶方案组成高阶数值近似精确解。我们详细分析了这几类方法为达到给定阶数而必须满足的阶数条件,并结合几何数值积分和高振荡问题的处理,对它们的定性特性提出了一些见解。由于分裂方法在偏微分方程领域受到了广泛关注,我们在本研究中也涉及这一主题,并特别关注抛物方程及其问题。我们收集了不同阶数的详尽方法列表,并在简单示例中进行了测试。最后,我们还介绍了分裂方法在从天体力学到统计学等不同领域的一些应用。
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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.
期刊最新文献
Splitting methods for differential equations Adaptive finite element methods The geometry of monotone operator splitting methods Numerical analysis of physics-informed neural networks and related models in physics-informed machine learning Optimal experimental design: Formulations and computations
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