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arXiv 2602.18547math.MGmath.PR
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一个多面体适用于所有:通过同时内在体积近似来表征欧几里得球体

Simultaneous random polytope approximation characterizes the Euclidean ball

Steven Hoehner

AI总结:

本文通过同时内在体积近似证明欧几里得球体的唯一性,揭示了内接多面体在渐近最优条件下的刚性特性。

摘要:

我们研究了在内在体积差限制下,对$\mathbb{R}^d$中的光滑严格凸体$K$,由具有受限顶点数的内接多面体进行渐近最佳近似的特性。我们证明了在确定性和概率性设置中都存在刚性现象。在确定性内接近似模型中,我们证明如果一个单一的多面体序列在体积和均宽差方面同时渐近最优,那么$K$必须是一个欧几里得球体。特别是,欧几里得球体是唯一的$C_+^2$凸体,使得一个多面体序列可以同时以最优渐近速率近似所有内在体积。在概率性模型中,我们证明了一个更强的结论:如果一个单一的采样密度在$\partial K$上产生随机内接多面体,这些多面体在期望意义上对任何两个不同的内在体积偏差都是渐近最优的,那么$K$必须是一个欧几里得球体。此外,利用极性,我们建立了关于内接于$K$的多面体(具有受限面数)在体积和均宽情况下的刚性定理的对偶版本,同样在确定性和概率性框架中。证明使用了渐近量化理论的工具以及基于曲率的最优顶点分布。这些结果解决了Besau、Hoehner和Kur(IMRN,2021)提出的一个开放问题。

英文摘要:

In this work, we present a new geometric characterization of the Euclidean ball based on approximation by random polytopes. We investigate when a single boundary sampling density is asymptotically optimal for two random polytope approximation problems, and show that for a convex body in $\R^d$ with $C^2$ boundary and everywhere positive principal curvatures, one fixed density minimizes the leading expected errors for any two distinct intrinsic volume differences of inscribed random polytopes if and only if the body is a Euclidean ball. We show that an analogous characterization holds for the volume and mean width differences of circumscribed random polytopes, and that uniform sampling gives the converse statement in both models. We also determine the unique density minimizing the average of two normalized leading errors, and obtain an explicit positive gap for every nonball. The proofs combine classical random polytope asymptotics, Hölder's inequality, and a curvature rigidity argument based on the Hsiung--Minkowski identities and Newton--Maclaurin inequalities.

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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