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arXiv 1105.2599math.NAcs.NA
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高阶多项式格规则的最坏情况误差的高效计算与(快速)分量按分量构造

Efficient calculation of the worst-case error and (fast) component-by-component construction of higher order polynomial lattice rules

The University of Technology, Sydney(悉尼科技大学);The University of New South Wales(新南威尔士大学);Universität Linz(林茨大学);K.U.Leuven(荷语鲁汶大学)

Jan Baldeaux, Josef Dick, Gunther Leobacher, Dirk Nuyens, Friedrich Pillichshammer

AI总结:

本文提出了一种高效的分量按分量构造算法,用于生成高阶多项式格规则,该规则在单位立方体上对高维光滑函数的多变量求积达到近最优收敛阶,并通过利用循环群结构加速最坏情况误差的计算。

摘要:

我们展示了如何获得高阶多项式格规则的快速分量按分量构造算法。此类规则对于单位立方体上高维光滑函数的多变量求积非常有用,因为它们达到了近最优的收敛阶。本文解决的主要问题是找到一种高效计算最坏情况误差的方法。我们提出了一种通用算法,并给出了基为2的显式表达式。为了获得高效的分量按分量构造算法,我们利用了底层循环群的结构。我们通过计算最坏情况误差,将新的高阶多变量求积规则与基于高阶数字网的现有求积规则进行比较。这些数值结果表明,高阶多项式格规则改进了基于高阶数字网的已知拟蒙特卡洛规则构造。

英文摘要:

We show how to obtain a fast component-by-component construction algorithm for higher order polynomial lattice rules. Such rules are useful for multivariate quadrature of high-dimensional smooth functions over the unit cube as they achieve the near optimal order of convergence. The main problem addressed in this paper is to find an efficient way of computing the worst-case error. A general algorithm is presented and explicit expressions for base~2 are given. To obtain an efficient component-by-component construction algorithm we exploit the structure of the underlying cyclic group. We compare our new higher order multivariate quadrature rules to existing quadrature rules based on higher order digital nets by computing their worst-case error. These numerical results show that the higher order polynomial lattice rules improve upon the known constructions of quasi-Monte Carlo rules based on higher order digital nets.

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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