Vietoris$\unicode{x2013}$Rips Complexes of Metric Spaces Near a Metric Graph
Sushovan Majhi

TL;DR
This paper provides a method to choose scale parameters for Vietoris–Rips complexes to recover the topology of metric graphs and related spaces from point cloud data, extending previous qualitative results to quantitative guidelines.
Contribution
It introduces a way to quantitatively select scale parameters for Vietoris–Rips complexes to recover metric graph topology from data with small Gromov–Hausdorff distance.
Findings
Derived a description of the scale parameter based on the convexity radius.
Extended the analysis to Euclidean subsets near embedded metric graphs.
Provided a method to choose parameters ensuring homotopy equivalence.
Abstract
For a sufficiently small scale , the VietorisRips complex of a metric space with a small GromovHausdorff distance to a closed Riemannian manifold has been already known to recover up to homotopy type. While the qualitative result is remarkable and generalizes naturally to the recovery of spaces beyond Riemannian manifoldssuch as geodesic metric spaces with a positive convexity radiusthe generality comes at a cost. Although the scale parameter is known to depend only on the geometric properties of the geodesic space, how to quantitatively choose such a for a given geodesic space is still elusive. In this work, we focus on the topological recovery of a special type of geodesic space, called a metric graph. For an abstract metric graph and a (sample)…
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Taxonomy
TopicsTopological and Geometric Data Analysis
