A note on the CBC-DBD construction of lattice rules with general positive weights

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
P. Kritzer
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引用次数: 1

Abstract

Lattice rules are among the most prominently studied quasi-Monte Carlo methods to approximate multivariate integrals. A rank-$1$ lattice rule to approximate an $s$-dimensional integral is fully specified by its \emph{generating vector} $\boldsymbol{z} \in \mathbb{Z}^s$ and its number of points~$N$. While there are many results on the existence of ``good'' rank-$1$ lattice rules, there are no explicit constructions of good generating vectors for dimensions $s \ge 3$. This is why one usually resorts to computer search algorithms. In a recent paper by Ebert et al. in the Journal of Complexity, we showed a component-by-component digit-by-digit (CBC-DBD) construction for good generating vectors of rank-1 lattice rules for integration of functions in weighted Korobov classes. However, the result in that paper was limited to product weights. In the present paper, we shall generalize this result to arbitrary positive weights, thereby answering an open question posed in the paper of Ebert et al. We also include a short section on how the algorithm can be implemented in the case of POD weights, by which we see that the CBC-DBD construction is competitive with the classical CBC construction.
关于一般正权格规则的CBC-DBD构造的注记
格规则是研究最突出的拟蒙特卡罗方法来近似多元积分。近似$s$维积分的秩- $1$点阵规则由其\emph{生成向量}$\boldsymbol{z} \in \mathbb{Z}^s$及其点数$N$完全指定。虽然有许多关于“好”秩- $1$格规则存在的结果,但没有关于维度$s \ge 3$的好生成向量的明确构造。这就是为什么人们通常求助于计算机搜索算法。在Ebert等人最近发表在《复杂性杂志》上的一篇论文中,我们展示了一种组件-组件-数字-数字(CBC-DBD)构造,用于加权Korobov类中函数积分的秩-1格规则的良好生成向量。然而,该论文的结果仅限于产品权重。在本文中,我们将这个结果推广到任意正权,从而回答了Ebert等人的论文中提出的一个开放性问题。我们还包括一个关于如何在POD权重的情况下实现算法的简短部分,通过该部分我们可以看到CBC- dbd结构与经典CBC结构相竞争。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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