We present a computational scheme that derives a global polynomial level set parametrisation for smooth closed surfaces from a regular surface-point set and prove its uniqueness. This enables us to approximate a broad class of smooth surfaces by affine algebraic varieties. From such a global polynomial level set parametrisation, differential-geometric quantities like mean and Gauss curvature can be efficiently and accurately computed. Even 4$^{\text{th}}$-order terms such as the Laplacian of mean curvature are approximates with high precision. The accuracy performance results in a gain of computational efficiency, significantly reducing the number of surface points required compared to classic alternatives that rely on surface meshes or embedding grids. We mathematically derive and empirically demonstrate the strengths and the limitations of the present approach, suggesting it to be applicable to a large number of computational tasks in numerical differential geometry.
翻译:我们提出了一个计算方案,从正常的表面定置中得出全球多元水平,用于平滑封闭表面的设定参数,并证明其独特性。这使我们能够通过等离子代数品种,大致使用广泛的平滑表面类别。从这样一个全球多元水平定置对称中和高斯曲线等差异几何数量可以高效和准确地计算。甚至4$ ⁇ text{th ⁇ $-顺序术语,如中度曲度拉平面术语,也是非常精确的近似值。精确性能导致计算效率的提高,大大降低了所需的表面点数,与依赖地表模或嵌入网格的经典替代方法相比,大大降低了所需的表面点数。我们从数学上得出并用经验展示了当前方法的长处和局限性,表明它适用于数字差异几何中的大量计算任务。