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引用次数: 3
摘要
本文的目的是开发在d维单位立方体[0,1]d中生成均匀分布序列的贪心算法。优点数是l2差异的三种不同变体。理论和数值实验结果表明,所得序列具有良好的分布特性。我们在这里遵循的方法是由Steinerberger和Pausinger最近的工作所激发的,他们考虑了类似的贪婪算法,在这种算法中,他们最小化了可能与星点差异或点集能量相关的函数。与许多贪婪算法相比,在这些算法中,序列的结果元素只能以数字形式给出,我们将发现,在一维情况下,我们的算法产生的是可以精确描述的有理数。特别地,我们将观察到序列[0,1)中的任何初始段都可以自然地扩展为均匀分布序列,其中所有后续元素的形式为x N = 2n−1 2n,对于某些N∈{1,…, n}。我们还将研究结果序列的l2差异对维数d的依赖性。
Uniformly distributed sequences generated by a
greedy minimization of the L2 discrepancy
The aim of this paper is to develop greedy algorithms which generate uniformly distributed sequences in the d -dimensional unit cube [0 , 1] d . The figures of merit are three different variants of L 2 discrepancy. Theoretical results along with numerical experiments suggest that the resulting sequences have excellent distribution properties. The approach we follow here is motivated by recent work of Steinerberger and Pausinger who consider similar greedy algorithms, where they minimize functionals that can be related to the star discrepancy or energy of point sets. In contrast to many greedy algorithms where the resulting elements of the sequence can only be given numerically, we will find that in the one-dimensional case our algorithms yield rational numbers which we can describe precisely. In particular, we will observe that any initial segment of a sequence in [0 , 1) can be naturally extended to a uniformly distributed sequence where all subsequent elements are of the form x N = 2 n − 1 2 N for some n ∈ { 1 , . . . , N } . We will also investigate the dependence of the L 2 discrepancy of the resulting sequences on the dimension d .