针对分数拉普拉斯问题的梯度网格上的拼合方法的误差分析

IF 1.7 3区 数学 Q2 MATHEMATICS, APPLIED Advances in Computational Mathematics Pub Date : 2024-05-20 DOI:10.1007/s10444-024-10146-3
Minghua Chen, Weihua Deng, Chao Min, Jiankang Shi, Martin Stynes
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引用次数: 0

摘要

本文研究了一维分数拉普拉斯边界值问题的数值求解。虽然分数拉普拉斯算子是最重要和最突出的非局部算子之一,但其数值分析却具有挑战性,部分原因是该问题的解一般在域边界处具有弱奇异性。为了对该问题进行数值求解,我们在网格上使用了分段线性配位来处理边界奇点。通过严格的分析,我们得出了最大节点误差的界限,这表明该方法的收敛阶数如何取决于网格的分级;因此,我们可以确定最佳的网格分级。给出的数值结果证实了误差分析的精确性。
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Error analysis of a collocation method on graded meshes for a fractional Laplacian problem

The numerical solution of a 1D fractional Laplacian boundary value problem is studied. Although the fractional Laplacian is one of the most important and prominent nonlocal operators, its numerical analysis is challenging, partly because the problem’s solution has in general a weak singularity at the boundary of the domain. To solve the problem numerically, we use piecewise linear collocation on a mesh that is graded to handle the boundary singularity. A rigorous analysis yields a bound on the maximum nodal error which shows how the order of convergence of the method depends on the grading of the mesh; hence, one can determine the optimal mesh grading. Numerical results are presented that confirm the sharpness of the error analysis.

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来源期刊
CiteScore
3.00
自引率
5.90%
发文量
68
审稿时长
3 months
期刊介绍: Advances in Computational Mathematics publishes high quality, accessible and original articles at the forefront of computational and applied mathematics, with a clear potential for impact across the sciences. The journal emphasizes three core areas: approximation theory and computational geometry; numerical analysis, modelling and simulation; imaging, signal processing and data analysis. This journal welcomes papers that are accessible to a broad audience in the mathematical sciences and that show either an advance in computational methodology or a novel scientific application area, or both. Methods papers should rely on rigorous analysis and/or convincing numerical studies.
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