论文标题
数据集的景观和持续同源性的功能
Landscapes of data sets and functoriality of persistent homology
论文作者
论文摘要
本文的目的是描述有关持续同源性功能的新观点,并解释其固有的对称性,经常被忽略。我们的数据集是具有有限域的有限函数集合,称为测量值。这样的数据集可能包含内部对称性,这些对称是由一组域内态性的作用有效捕获的。一组内态性的不同选择编码数据集的不同对称性。我们在此类丰富的数据集上描述了各种类别结构,并证明了它们的某些特性,例如分解和形态形成。我们还根据彩色有向图描述了一个数据结构,该图很方便地编码上述富集。我们表明,持续的同源性仅保留了这些丰富数据集的这些景观的某些方面。换句话说,持续的同源性不是整个富集数据集的函数。尽管如此,我们表明持续的同源性在本地起作用。我们使用模棱两可的操作员的概念来捕获持续的同源性错过的一些信息。
The aim of this article is to describe a new perspective on functoriality of persistent homology and explain its intrinsic symmetry that is often overlooked. A data set for us is a finite collection of functions, called measurements, with a finite domain. Such a data set might contain internal symmetries which are effectively captured by the action of a set of the domain endomorphisms. Different choices of the set of endomorphisms encode different symmetries of the data set. We describe various category structures on such enriched data sets and prove some of their properties such as decompositions and morphism formations. We also describe a data structure, based on coloured directed graphs, which is convenient to encode the mentioned enrichment. We show that persistent homology preserves only some aspects of these landscapes of enriched data sets however not all. In other words persistent homology is not a functor on the entire category of enriched data sets. Nevertheless we show that persistent homology is functorial locally. We use the concept of equivariant operators to capture some of the information missed by persistent homology.