We discuss a cheap and stable approach to polynomial moment-based compression of multivariate measures by discrete signed measures. The method is based on the availability of an orthonormal basis and a low-cardinality algebraic quadrature formula for an auxiliary measure in a bounding set. Differently from other approaches, no conditioning issue arises since no matrix factorization or inversion is needed. We provide bounds for the sum of the absolute values of the signed measure weights, and we make two examples: efficient quadrature on curved planar elements with spline boundary (in view of the application to high-order FEM/VEM), and compression of QMC integration on 3D elements with complex shape.
翻译:本文探讨了一种基于多项式矩的多元测度压缩方法,通过离散有符号测度实现低成本且稳定的计算。该方法依赖于在边界集合中构造辅助测度的正交基与低基数代数求积公式。与其他方法不同,由于无需矩阵分解或求逆运算,本方法避免了条件数问题。我们给出了有符号测度权重绝对值之和的界,并提供了两个应用示例:一是针对具有样条边界的平面曲边单元的高效求积(面向高阶有限元法/虚拟元法应用),二是对复杂形状三维单元的拟蒙特卡洛积分进行压缩。