博雷尔不等式和通过离散不等式求随机多面体的平均宽度

David Alonso-Gutiérrez, Luis C. García-Lirola
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引用次数: 0

摘要

博雷尔不等式指出存在一个正的绝对常数$C>0$,使得对于每一个$1\leq p\leq q$ $\left(\mathbb E|\langle X、e_n\rangle|^p\right)^\frac{1}{p}\leqleft(\mathbb E|\langle X,e_n\rangle|^q\right)^\frac{1}{q}\leq C\frac{q}{p}\left(\mathbb E|\langle X、e_n\rangle|^p\right)^\frac{1}{p}, $$ 当 $X$ 是均匀分布在任何凸体 $K\subseteq\mathbb R^n$ 中的随机向量,其内部包含原点,并且 $(e_i)_{i=1}^n$ 是 $\mathbbR^n$ 中的标准规范基础时。在本文中,我们将证明这个不等式的离散版本,只要 $X$ 是均匀分布在 $K\cap\mathbb Z^n$ 上的随机向量,对于在其内部包含原点的任何凸体 $K\subseteq\mathbb R^n$ 来说,这个不等式都将成立。我们还将利用这种离散版本来获得离散不等式,从中我们可以为任何内部包含原点的凸体 $K$ 恢复估计值 $\mathbb Ew(K_N)\sim w(Z_{\log N}(K))$ 、其中 $K_N$ 是由均匀分布在 $K$ 上的独立随机向量生成的中心对称随机多面体$K_N=\operatorname{conv}\{pm X_1,\ldots,\pm X_N/}$,$w(\cdot)$ 表示平均宽度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Borell's inequality and mean width of random polytopes via discrete inequalities
Borell's inequality states the existence of a positive absolute constant $C>0$ such that for every $1\leq p\leq q$ $$ \left(\mathbb E|\langle X, e_n\rangle|^p\right)^\frac{1}{p}\leq\left(\mathbb E|\langle X, e_n\rangle|^q\right)^\frac{1}{q}\leq C\frac{q}{p}\left(\mathbb E|\langle X, e_n\rangle|^p\right)^\frac{1}{p}, $$ whenever $X$ is a random vector uniformly distributed in any convex body $K\subseteq\mathbb R^n$ containing the origin in its interior and $(e_i)_{i=1}^n$ is the standard canonical basis in $\mathbb R^n$. In this paper, we will prove a discrete version of this inequality, which will hold whenever $X$ is a random vector uniformly distributed on $K\cap\mathbb Z^n$ for any convex body $K\subseteq\mathbb R^n$ containing the origin in its interior. We will also make use of such discrete version to obtain discrete inequalities from which we can recover the estimate $\mathbb E w(K_N)\sim w(Z_{\log N}(K))$ for any convex body $K$ containing the origin in its interior, where $K_N$ is the centrally symmetric random polytope $K_N=\operatorname{conv}\{\pm X_1,\ldots,\pm X_N\}$ generated by independent random vectors uniformly distributed on $K$ and $w(\cdot)$ denotes the mean width.
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