arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2201.05204math.PRcs.ITmath.IT
收藏

随机超平面镶嵌的精确估计

Sharp estimates on random hyperplane tessellations

Sjoerd Dirksen, Shahar Mendelson, Alexander Stollenwerk

摘要:

我们研究的问题,生成一个超平面细分的任意设置$T$在$\mathbb{R}^n$,确保任何两个点之间的欧几里得距离对应的分数的超平面分离他们到一个预先指定的错误$δ$。我们专注于随机高斯镶嵌均匀分布的移位,并推导出所需的超平面$m$的数量上的尖锐的界限。令人惊讶的是,我们较低的估计值证伪了$m\sim \ell_*^2(T)/δ^2$是最优的猜想,其中$\ell_*^2(T)$是$T$的高斯宽度。

英文摘要:

We study the problem of generating a hyperplane tessellation of an arbitrary set $T$ in $\mathbb{R}^n$, ensuring that the Euclidean distance between any two points corresponds to the fraction of hyperplanes separating them up to a pre-specified error $δ$. We focus on random gaussian tessellations with uniformly distributed shifts and derive sharp bounds on the number of hyperplanes $m$ that are required. Surprisingly, our lower estimates falsify the conjecture that $m\sim \ell_*^2(T)/δ^2$, where $\ell_*^2(T)$ is the gaussian width of $T$, is optimal.

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。

↑