Delaunay-Rips filtration: a study and an algorithm

Fuente: arXiv
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Main Authors: Clémot, Mattéo, Digne, Julie, Tierny, Julien
Format: Preprint
Published: 2025
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author Clémot, Mattéo
Digne, Julie
Tierny, Julien
author_facet Clémot, Mattéo
Digne, Julie
Tierny, Julien
contents The Delaunay-Rips filtration is a lighter and faster alternative to the well-known Rips filtration for low-dimensional Euclidean point clouds. Despite these advantages, it has seldom been studied. In this paper, we aim to bridge this gap by providing a thorough theoretical and empirical analysis of this construction. From a theoretical perspective, we show how the persistence diagrams associated with the Delaunay-Rips filtration approximate those obtained with the Rips filtration. Additionally, we describe the instabilities of the Delaunay-Rips persistence diagrams when the input point cloud is perturbed. Finally, we introduce an algorithm that computes persistence diagrams of Delaunay-Rips filtrations in any dimension. We show that our method is faster and has a lower memory footprint than traditional approaches in low dimensions. Our C++ implementation, which comes with Python bindings, is available at https://github.com/MClemot/GeoPH.
format Preprint
id arxiv_https___arxiv_org_abs_2512_17382
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Delaunay-Rips filtration: a study and an algorithm
Clémot, Mattéo
Digne, Julie
Tierny, Julien
Computational Geometry
The Delaunay-Rips filtration is a lighter and faster alternative to the well-known Rips filtration for low-dimensional Euclidean point clouds. Despite these advantages, it has seldom been studied. In this paper, we aim to bridge this gap by providing a thorough theoretical and empirical analysis of this construction. From a theoretical perspective, we show how the persistence diagrams associated with the Delaunay-Rips filtration approximate those obtained with the Rips filtration. Additionally, we describe the instabilities of the Delaunay-Rips persistence diagrams when the input point cloud is perturbed. Finally, we introduce an algorithm that computes persistence diagrams of Delaunay-Rips filtrations in any dimension. We show that our method is faster and has a lower memory footprint than traditional approaches in low dimensions. Our C++ implementation, which comes with Python bindings, is available at https://github.com/MClemot/GeoPH.
title Delaunay-Rips filtration: a study and an algorithm
topic Computational Geometry
url https://arxiv.org/abs/2512.17382