{"title":"The Dual Degree Cech Bifiltration","authors":"Morten Brun","doi":"arxiv-2407.00477","DOIUrl":null,"url":null,"abstract":"In topological data analysis (TDA), a longstanding challenge is to recognize\nunderlying geometric structures in noisy data. One motivating examples is the\nshape of a point cloud in Euclidean space given by image. Carlsson et al.\nproposed a method to detect topological features in point clouds by first\nfiltering by density and then applying persistent homology. Later more refined\nmethods have been developed, such as the degree Rips complex of Lesnick and\nWright and the multicover bifiltration. In this paper we introduce the dual\nDegree Cech bifiltration, a Prohorov stable bicomplex of a point cloud in a\nmetric space with the point cloud itself as vertex set. It is of the same\nhomotopy type as the Measure Dowker bifiltration of Hellmer and Spali\\'nski but\nit has a different vertex set. The dual Degree Cech bifiltration can be constructed both in an ambient and\nan intrinsic way. The intrinsic dual Degree Cech bifiltration is a\n$(1,2)$-intereaved with the ambent dual Degree Cech bifiltration in the\ndistance parameter. This interleaving can be used to leverage a stability\nresult for the intrinsically defined dual Degree Cech bifiltration. This\nstability result recently occured in work by Hellmer and Spali\\'nski.","PeriodicalId":501119,"journal":{"name":"arXiv - MATH - Algebraic Topology","volume":"28 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - MATH - Algebraic Topology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.00477","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In topological data analysis (TDA), a longstanding challenge is to recognize
underlying geometric structures in noisy data. One motivating examples is the
shape of a point cloud in Euclidean space given by image. Carlsson et al.
proposed a method to detect topological features in point clouds by first
filtering by density and then applying persistent homology. Later more refined
methods have been developed, such as the degree Rips complex of Lesnick and
Wright and the multicover bifiltration. In this paper we introduce the dual
Degree Cech bifiltration, a Prohorov stable bicomplex of a point cloud in a
metric space with the point cloud itself as vertex set. It is of the same
homotopy type as the Measure Dowker bifiltration of Hellmer and Spali\'nski but
it has a different vertex set. The dual Degree Cech bifiltration can be constructed both in an ambient and
an intrinsic way. The intrinsic dual Degree Cech bifiltration is a
$(1,2)$-intereaved with the ambent dual Degree Cech bifiltration in the
distance parameter. This interleaving can be used to leverage a stability
result for the intrinsically defined dual Degree Cech bifiltration. This
stability result recently occured in work by Hellmer and Spali\'nski.
在拓扑数据分析(TDA)中,一个长期存在的挑战是识别噪声数据中潜在的几何结构。其中一个激励性的例子是图像给出的欧几里得空间中点云的形状。Carlsson 等人提出了一种检测点云拓扑特征的方法,首先通过密度过滤,然后应用持久同源性。后来,人们又开发出了更精细的方法,如莱斯尼克和赖特的度里普斯复合法以及多覆盖分层法。在本文中,我们介绍了对偶度 Cech 双分层,即以点云本身为顶点集的对称空间中点云的普罗霍罗夫稳定双复数。它与赫尔默和斯帕利斯基的度量道克二分层属于同一同调类型,但它的顶点集不同。对偶 Degree Cech 双分层可以通过环境和内在两种方式构造。内在的对偶 Degree Cech 双分层与外在的对偶 Degree Cech 双分层在距离参数上是$(1,2)$交错的。这种交错可以用来利用内在定义的双度切赫分层的稳定性结果。这一稳定性结果最近出现在 Hellmer 和 Spali\'nski 的研究中。