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arXiv 1902.09138math.AT
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$A_\infty$持久同源性可根据点云数据集估计拓扑

$A_\infty$ persistent homology estimates the topology from pointcloud datasets

Francisco Belchí, Anastasios Stefanou

摘要:

设$X$是度量空间$M$的闭子空间。在温和的假设下,可以从逼近$X$的点的有限集合$P \subset M$估计$X$的Betti数。在本文中,我们表明,人们也可以使用$P$估计更详细的拓扑性质的$X$。这些性质是通过$A_\infty$ -结构计算的,因此与$X$的杯积和梅西积、它的循环空间$ΩX$、它的形式、连接数等有关。此外,我们还研究了以下设置:给定拓扑空间$Y$上的连续函数$f \colon Y \longrightarrow \mathbb R$,$A_\infty$持久同源性构建了一个条形码家族,对$Y$的一些几何和拓扑性质进行了高度详细的描述。我们在这里证明,在温和的假设下,这些条形码是稳定的:函数$f$中的小扰动意味着条形码中的最多小扰动。

英文摘要:

Let $X$ be a closed subspace of a metric space $M$. Under mild hypotheses, one can estimate the Betti numbers of $X$ from a finite set $P \subset M$ of points approximating $X$. In this paper, we show that one can also use $P$ to estimate much more detailed topological properties of $X$. These properties are computed via $A_\infty$-structures, and are therefore related to the cup and Massey products of $X$, its loop space $ΩX$, its formality, linking numbers, etc. Additionally, we study the following setting: given a continuous function $f \colon Y \longrightarrow \mathbb R$ on a topological space $Y$, $A_\infty$ persistent homology builds a family of barcodes presenting a highly detailed description of some geometric and topological properties of $Y$. We prove here that under mild assumptions, these barcodes are stable: small perturbations in the function $f$ imply at most small perturbations in the barcodes.

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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