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An optimal ansatz space for moving least squares approximation on spheres
Advances in Computational Mathematics ( IF 1.7 ) Pub Date : 2024-10-22 , DOI: 10.1007/s10444-024-10201-z
Ralf Hielscher, Tim Pöschl

We revisit the moving least squares (MLS) approximation scheme on the sphere \(\mathbb S^{d-1} \subset {\mathbb R}^d\), where \(d>1\). It is well known that using the spherical harmonics up to degree \(L \in {\mathbb N}\) as ansatz space yields for functions in \(\mathcal {C}^{L+1}(\mathbb S^{d-1})\) the approximation order \(\mathcal {O}\left( h^{L+1} \right) \), where h denotes the fill distance of the sampling nodes. In this paper, we show that the dimension of the ansatz space can be almost halved, by including only spherical harmonics of even or odd degrees up to L, while preserving the same order of approximation. Numerical experiments indicate that using the reduced ansatz space is essential to ensure the numerical stability of the MLS approximation scheme as \(h \rightarrow 0\). Finally, we compare our approach with an MLS approximation scheme that uses polynomials on the tangent space of the sphere as ansatz space.



中文翻译:


在球体上移动最小二乘近似的最佳拟设空间



我们重新审视球体 \(\mathbb S^{d-1} \subset {\mathbb R}^d\) 上的移动最小二乘 (MLS) 近似方案,其中 \(d>1\)。众所周知,使用高达 \(L \in {\mathbb N}\) 的球谐函数作为拟设空间,可以得到 \(\mathcal {C}^{L+1}(\mathbb S^{d-1})\) 中的函数的近似阶数 \(\mathcal {O}\left( h^{L+1} \right) \),其中 h 表示采样节点的填充距离。在本文中,我们表明,通过仅包含高达 L 的偶数或奇数度的球谐,同时保持相同的近似阶数,拟设空间的维数几乎可以减半。数值实验表明,使用约化的拟设空间对于确保 MLS 近似方案的数值稳定性至关重要,如 \(h \rightarrow 0\)。最后,我们将我们的方法与 MLS 近似方案进行了比较,后者使用球体切线上的多项式作为拟设空间。

更新日期:2024-10-22
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