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arXiv 2111.04431math.NAcs.NA
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求给定向量场的向量势的一种新的图形算法

Inverting the discrete curl operator: a novel graph algorithm to find a vector potential of a given vector field

Silvano Pitassi, Riccardo Ghiloni, Ruben Specogna

摘要:

我们提供了一个新的框架来计算任意多面体网格上给定离散向量场的离散向量势。该框架利用了非循环匹配的概念,离散莫尔斯理论的核心组合工具。我们引入了完全非循环匹配的新概念,并证明了它们给出了相同的高斯消去法的最终结果。基本上,而不是做昂贵的行和列操作的稀疏矩阵,我们计算等价的廉价组合操作,保持底层的稀疏结构。目前,文献中提出的最有效的算法来寻找离散向量势利用树-余树技术。我们表明,他们计算一种特殊类型的完全无环匹配。此外,我们证明了计算它们的问题等价于决定给定网格是否具有拓扑性质的问题。这一事实给出了一个拓扑表征著名的终止问题的树cotree技术。我们提出了一种新的递归算法来计算离散矢量势。它通过对$1$ -链和$2$ -链进行与非循环匹配相关的基本高斯运算,直接作用于它们的基元素。然而,主要的新颖之处在于它可以递归地应用。事实上,递归过程允许我们转移标准树-余树技术的终止问题。我们测试了算法与已知的拓扑障碍病理三角剖分。在所有测试的问题中,我们观察到线性计算复杂性作为网格步长的函数。此外,该算法是纯粹基于图的,因此它是直接实现的,不需要专门的外部过程。我们相信,我们的框架可以提供新的视角,稀疏矩阵计算。

英文摘要:

We provide a novel framework to compute a discrete vector potential of a given discrete vector field on arbitrary polyhedral meshes. The framework exploits the concept of acyclic matching, a combinatorial tool at the core of discrete Morse theory. We introduce the new concept of complete acyclic matchings and we show that they give the same end result of Gaussian elimination. Basically, instead of doing costly row and column operations on a sparse matrix, we compute equivalent cheap combinatorial operations that preserve the underlying sparsity structure. Currently, the most efficient algorithms proposed in literature to find discrete vector potentials make use of tree-cotree techniques. We show that they compute a special type of complete acyclic matchings. Moreover, we show that the problem of computing them is equivalent to the problem of deciding whether a given mesh has a topological property called collapsibility. This fact gives a topological characterization of well-known termination problems of tree-cotree techniques. We propose a new recursive algorithm to compute discrete vector potentials. It works directly on basis elements of $1$- and $2$-chains by performing elementary Gaussian operations on them associated with acyclic matchings. However, the main novelty is that it can be applied recursively. Indeed, the recursion process allows us to sidetrack termination problems of the standard tree-cotree techniques. We tested the algorithm on pathological triangulations with known topological obstructions. In all tested problems we observe linear computational complexity as a function of mesh size. Moreover, the algorithm is purely graph-based so it is straightforward to implement and does not require specialized external procedures. We believe that our framework could offer new perspectives to sparse matrix computations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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