arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2003.13122math.NT
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良好逼近测度族

Families of well approximable measures

Samantha Fairchild, Max Goering, Christian Weiß

摘要:

我们提供了一个算法来近似一个离散的测量$μ$的测量$ν_{N}$对应于一组$N$点,使$μ$和$ν_N$之间的总变化有一个上限。因此,如果$μ$是$[0,1]^{d}$上的(有限或无限支持的)离散概率测度,并且每个点的权重具有足够的衰减率,则$μ$可以近似为具有全变差的$ν_N$,因此星偏差由$(\log N) N^{-1}$限制。我们的结果改进了,在离散的情况下,最近的工作Aistleitner,Bilyk,和Nikolov谁表明,任何正规化Borel措施$μ$,存在有限集,其明星的差异$μ$是最多$(\log N)^{d-\frac{1}{2}} N^{-1}$。此外,我们关闭的差距在文献中的差异的情况下$d=1$表明勒贝格确实是最难的措施,以近似有限集,也没有离散组件的所有措施有相同的顺序的差异作为勒贝格测度。

英文摘要:

We provide an algorithm to approximate a finitely supported discrete measure $μ$ by a measure $ν_{N}$ corresponding to a set of $N$ points so that the total variation between $μ$ and $ν_N$ has an upper bound. As a consequence if $μ$ is a (finite or infinitely supported) discrete probability measure on $[0,1]^{d}$ with a sufficient decay rate on the weights of each point, then $μ$ can be approximated by $ν_N$ with total variation, and hence star-discrepancy, bounded above by $(\log N) N^{-1}$. Our result improves, in the discrete case, recent work by Aistleitner, Bilyk, and Nikolov who show that for any normalized Borel measure $μ$, there exist finite sets whose star-discrepancy with respect to $μ$ is at most $(\log N)^{d-\frac{1}{2}} N^{-1}$. Moreover we close a gap in the literature for discrepancy in the case $d=1$ showing both that Lebesgue is indeed the hardest measure to approximate by finite sets and also that all measures without discrete components have the same order of discrepancy as the Lebesgue measure.

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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