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In the applied algebraic topology community, the persistent homology induced by the Vietoris-Rips simplicial filtration is a standard method for capturing topological information from metric spaces. In this paper, we consider a different,…

Algebraic Topology · Mathematics 2024-04-24 Sunhyuk Lim , Facundo Memoli , Osman Berat Okutan

We introduce a new invariant defined on the vertices of a given filtered simplicial complex, called codensity, which controls the impact of removing vertices on persistent homology. We achieve this control through the use of an interleaving…

Algebraic Topology · Mathematics 2018-01-10 Facundo Mémoli , Osman Berat Okutan

We study the concepts of the $\ell_p$-Vietoris-Rips simplicial set and the $\ell_p$-Vietoris-Rips complex of a metric space, where $1\leq p \leq \infty.$ This theory unifies two established theories: for $p=\infty,$ this is the classical…

Algebraic Topology · Mathematics 2025-02-28 Sergei O. Ivanov , Xiaomeng Xu

We introduce the monoidal Rips filtration, a filtered simplicial set for weighted directed graphs and other lattice-valued networks. Our construction generalizes the Vietoris-Rips filtration for metric spaces by replacing the maximum…

Algebraic Topology · Mathematics 2025-10-29 Nello Blaser , Morten Brun , Odin Hoff Gardaa , Lars M. Salbu

In this work, we present a generalization of extended persistent homology to filtrations of graded sub-groups by defining relative homology in this setting. Our work provides a more comprehensive and flexible approach to get an algebraic…

Algebraic Topology · Mathematics 2023-11-01 Fang Sun , Shengwen Xie , Xuezhi Zhao

We introduce the concept of weighted persistence diagrams and develop a functorial pipeline for constructing them from finite metric measure spaces. This builds upon an existing functorial framework for generating classical persistence…

Algebraic Topology · Mathematics 2025-04-17 Aziz Burak Gülen , Facundo Mémoli , Amit Patel

As a step towards establishing homotopy-theoretic foundations for topological data analysis (TDA), we introduce and study homotopy interleavings between filtered topological spaces. These are homotopy-invariant analogues of interleavings,…

Algebraic Topology · Mathematics 2022-05-03 Andrew J. Blumberg , Michael Lesnick

Reeb graphs are a fundamental structure for analyzing the topological and geometric properties of scalar fields. Comparing Reeb graphs is crucial for advancing research in this domain, yet existing metrics are often computationally…

Computational Geometry · Computer Science 2025-07-03 Erin W. Chambers , Guangyu Meng

The primary goal of this paper is to find a homotopy theoretic approximation to moduli spaces of holomorphic maps Riemann surfaces into complex projective space. There is a similar treatment of a partial compactification of these moduli…

Algebraic Topology · Mathematics 2017-12-19 David Ayala

While persistent homology has taken strides towards becoming a wide-spread tool for data analysis, multidimensional persistence has proven more difficult to apply. One reason is the serious drawback of no longer having a concise and…

Algebraic Topology · Mathematics 2018-12-20 Mickaël Buchet , Emerson G. Escolar

Recently, multi-scale notions of local homology (a variant of persistent homology) have been used to study the local structure of spaces around a given point from a point cloud sample. Current reconstruction guarantees rely on constructing…

Computational Geometry · Computer Science 2013-04-24 Primoz Skraba , Bei Wang

Persistent homology is a popular computational tool for analyzing the topology of point clouds, such as the presence of loops or voids. However, many real-world datasets with low intrinsic dimensionality reside in an ambient space of much…

Machine Learning · Computer Science 2024-11-01 Sebastian Damrich , Philipp Berens , Dmitry Kobak

We propose a functorial framework for persistent homology based on finite topological spaces and their associated posets. Starting from a finite metric space, we associate a filtration of finite topologies whose structure maps are…

Algebraic Topology · Mathematics 2026-02-24 Selçuk Kayacan

The computational cost of persistent homology is often dominated by the growth of the underlying simplicial filtrations. Many different filtrations exist, each with its own assumptions and trade-offs, but all face some form of this growth…

Algebraic Topology · Mathematics 2026-05-15 António Leitão

We develop a new method to estimate the area, and more generally the intrinsic volumes, of a compact subset $X$ of $\mathbb{R}^d$ from a set $Y$ that is close in the Hausdorff distance. This estimator enjoys a linear rate of convergence as…

Metric Geometry · Mathematics 2024-07-22 David Cohen-Steiner , Antoine Commaret

The present lack of a stable method to compare persistent homology groups with torsion is a relevant problem in current research about Persistent Homology and its applications in Pattern Recognition. In this paper we introduce a…

Algebraic Topology · Mathematics 2010-12-21 Patrizio Frosini

Dimensionality reduction techniques are powerful tools for data preprocessing and visualization which typically come with few guarantees concerning the topological correctness of an embedding. The interleaving distance between the…

Machine Learning · Computer Science 2022-02-01 Bradley J. Nelson , Yuan Luo

Selective Rips complexes corresponding to a sequence of parameters are a generalization of Vietoris-Rips complexes utilizing the idea of thin simplices. We prove that if a metric space $Y$ is close (in Gromov-Hausdorff distance) to a closed…

Algebraic Topology · Mathematics 2023-04-21 Boštjan Lemež , Žiga Virk

The aim of this paper is to provide new stability results for sequences of metric measure spaces $(X_i,d_i,m_i)$ convergent in the measured Gromov-Hausdorff sense. By adopting the so-called extrinsic approach of embedding all metric spaces…

Metric Geometry · Mathematics 2016-07-06 Luigi Ambrosio , Shouhei Honda

We extend the notion of the distance to a measure from Euclidean space to probability measures on general metric spaces as a way to do topological data analysis in a way that is robust to noise and outliers. We then give an efficient way to…

Computational Geometry · Computer Science 2014-10-09 Mickael Buchet , Frederic Chazal , Steve Y. Oudot , Donald R. Sheehy