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arXiv 2108.02848math.NAcs.NAmath.OC
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可证正正合容积公式的构造及应用

Construction and application of provable positive and exact cubature formulas

Jan Glaubitz

摘要:

许多应用需要多维数值积分,通常以体积公式的形式。这些求积公式对于某些有限维函数空间(和权函数)是正的和精确的。虽然有几个有效的程序来构建许多标准情况下的积极和准确的容积公式,它仍然是一个挑战,这样做在更一般的设置。在这里,我们展示了如何最小二乘法可以用来推导出可证明的积极和确切的公式,在一般的多维设置。因此,该过程仅利用基本的线性代数运算,例如求解最小二乘问题。特别是,它被证明,所得到的最小二乘容积公式是确保积极的和准确的,如果使用足够大的数量的均匀分布的数据点。我们还讨论了应用可证正的和精确的最小二乘求积公式来构造嵌套稳定的高阶规则和正插值公式。最后,我们的研究结果揭示了一些现有的多元数值积分的方法,并在这些限制下,确保是成功的。

英文摘要:

Many applications require multi-dimensional numerical integration, often in the form of a cubature formula. These cubature formulas are desired to be positive and exact for certain finite-dimensional function spaces (and weight functions). Although there are several efficient procedures to construct positive and exact cubature formulas for many standard cases, it remains a challenge to do so in a more general setting. Here, we show how the method of least squares can be used to derive provable positive and exact formulas in a general multi-dimensional setting. Thereby, the procedure only makes use of basic linear algebra operations, such as solving a least squares problem. In particular, it is proved that the resulting least squares cubature formulas are ensured to be positive and exact if a sufficiently large number of equidistributed data points is used. We also discuss the application of provable positive and exact least squares cubature formulas to construct nested stable high-order rules and positive interpolatory formulas. Finally, our findings shed new light on some existing methods for multivariate numerical integration and under which restrictions these are ensured to be successful.

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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