The discretization of surface intrinsic PDEs has challenges that one might not face in the flat space. The closest point method (CPM) is an embedding method that represents surfaces using a function that maps points in the flat space to their closest points on the surface. This mapping brings intrinsic data onto the embedding space, allowing us to numerically approximate PDEs by the standard methods in the tubular neighborhood of the surface. Here, we solve the surface intrinsic positive Helmholtz equation by the CPM paired with finite differences which usually yields a large, sparse, and non-symmetric system. Domain decomposition methods, especially Schwarz methods, are robust algorithms to solve these linear systems. While there have been substantial works on Schwarz methods, Schwarz methods for solving surface differential equations have not been widely analyzed. In this work, we investigate the convergence of the CPM coupled with Schwarz method on 1-manifolds in d-dimensional space of real numbers.
翻译:表面内在的 PDE 的离散性存在挑战。 最接近点法( CPM) 是一种嵌入方法, 代表表面, 其功能是绘制平面上的点, 绘制在表面最接近点。 此映射将内在数据引入嵌入空间, 使我们能够用地表管周围的标准方法从数字上接近 PDE 。 在这里, 我们通过 CPM 解决表面内在正 Helmholtz 方程式的表面内正 Helmholtz 方程式, 配以有限的差异, 通常产生一个大、 稀疏和非对称系统。 Domain 分解法, 特别是Schwarz 法, 是解决这些线性系统的有力算法。 虽然在Schwarz 方法上做了大量的工作, 但是Schwarz 解决表面差异方程式的方法还没有得到广泛分析 。 在这项工作中, 我们研究了 CPM 与Swarz 方法在真实数字的维度空间的一公尺上与Schwarz 方法的结合情况 。