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Topological data analysis is becoming increasingly relevant to support the analysis of unstructured data sets. A common assumption in data analysis is that the data set is a sample---not necessarily a uniform one---of some high-dimensional…

Algebraic Topology · Mathematics 2021-01-20 Bastian Rieck , Markus Banagl , Filip Sadlo , Heike Leitte

In this article we study cohomology of a group with coefficients in representations on Banach spaces and its stability under deformations. We show that small, metric deformations of the representation preserve vanishing of cohomology. As…

Group Theory · Mathematics 2014-09-03 Uri Bader , Piotr W. Nowak

Mixing, and coherence are fundamental issues at the heart of understanding transport in fluid dynamics and other non-autonomous dynamical systems. Recently, the notion of coherence has come to a more rigorous footing, and particularly…

Dynamical Systems · Mathematics 2014-05-07 Tian Ma , Erik Bollt

Persistent homology is a popular tool in Topological Data Analysis. It provides numerical characteristics of data sets which reflect global geometric properties. In order to be useful in practice, for example for feature generation in…

Computational Geometry · Computer Science 2020-02-17 Boris Goldfarb

Hierarchically hyperbolic spaces provide a common framework for studying mapping class groups of finite type surfaces, Teichm\"uller space, right-angled Artin groups, and many other cubical groups. Given such a space $\mathcal X$, we build…

Geometric Topology · Mathematics 2018-03-16 Matthew G. Durham , Mark F. Hagen , Alessandro Sisto

Topological data analysis is an emerging area in exploratory data analysis and data mining. Its main tool, persistent homology, has become a popular technique to study the structure of complex, high-dimensional data. In this paper, we…

Graphics · Computer Science 2017-10-04 Mustafa Hajij , Bei Wang , Carlos Scheidegger , Paul Rosen

Persistent homology has been widely used to discover hidden topological structures in data across various applications, including music data. To apply persistent homology, a distance or metric must be defined between points in a point cloud…

Sound · Computer Science 2025-12-15 Eunwoo Heo , Byeongchan Choi , Myung ock Kim , Mai Lan Tran , Jae-Hun Jung

The objective of this paper is to derive the essential invariance and contraction properties for the geometric periodic systems, which can be formulated as a category of differential inclusions, and primarily rendered in the phase…

Systems and Control · Electrical Eng. & Systems 2021-04-30 Chen Qian , Yongchun Fang

The purpose of this paper is to lay the foundations for the study of the problem of when $\Ext^n(X, Y)=0$ in Banach/quasi-Banach spaces. We provide a number of examples of couples $X,Y$ so that $\Ext^n(X,Y)$ is (or is not ) $0$, including…

Functional Analysis · Mathematics 2020-05-05 Félix Cabello Sánchez , Jesús M . F. Castillo , Ricardo García

We present an introduction to the orbital stability of relative equilibria of Hamiltonian dynamical systems on (finite and infinite dimensional) Banach spaces. A convenient formulation of the theory of Hamiltonian dynamics with symmetry and…

Analysis of PDEs · Mathematics 2015-01-07 Stephan De Bievre , François Genoud , Simona Rota Nodari

In this paper, we perform a detailed investigation on the various geometrical properties of trapped surfaces and the boundaries of trapped region in general relativity. This treatment extends earlier work on LRS II spacetimes to a general 4…

General Relativity and Quantum Cosmology · Physics 2018-05-16 Abbas Sherif , Rituparno Goswami , Sunil D Maharaj

Our objective in this article is to show a possibly interesting structure of homotopic nature appearing in persistent (co)homology. Assuming that the filtration of the (say) simplicial set embedded in a finite dimensional vector space…

Algebraic Topology · Mathematics 2014-12-08 Estanislao Herscovich

Persistence homology is a tool used to measure topological features that are present in data sets and functions. Persistence pairs births and deaths of these features as we iterate through the sublevel sets of the data or function of…

Computational Geometry · Computer Science 2010-02-10 Brittany Terese Fasy

Persistent homology is a cornerstone of topological data analysis, offering a multiscale summary of topology with robustness to nuisance transformations, such as rotations and small deformations. Persistent homology has seen broad use…

Methodology · Statistics 2025-11-19 Zitian Wu , Arkaprava Roy , Leo L. Duan

Computational topology has recently known an important development toward data analysis, giving birth to the field of topological data analysis. Topological persistence, or persistent homology, appears as a fundamental tool in this field.…

Statistics Theory · Mathematics 2013-05-28 Frédéric Chazal , Marc Glisse , Catherine Labruère , Bertrand Michel

We introduce a linear dimensionality reduction technique preserving topological features via persistent homology. The method is designed to find linear projection $L$ which preserves the persistent diagram of a point cloud $\mathbb{X}$ via…

Machine Learning · Statistics 2021-06-15 Byeongsu Yu , Kisung You

This paper establishes connections between three of the most prominent metrics used in the analysis of persistence diagrams in topological data analysis: the bottleneck distance, Patel's erosion distance, and Bubenik's landscape distance.…

Metric Geometry · Mathematics 2025-09-09 Cagatay Ayhan , Tom Needham

Let $X$ be a closed subspace of a metric space $M$. Under mild hypotheses, one can estimate the Betti numbers of $X$ from a finite set $P \subset M$ of points approximating $X$. In this paper, we show that one can also use $P$ to estimate…

Algebraic Topology · Mathematics 2019-02-26 Francisco Belchí , Anastasios Stefanou

The aim of this paper is to develop a new axiomatization of planar geometry by reinterpreting the original axioms of Euclid. The basic concept is still that of a line segment but its equivalent notion of betweenness is viewed as a…

Metric Geometry · Mathematics 2015-06-12 Jerzy Dydak

This paper brings together three distinct theories with the goal of quantifying shape textures with complex morphologies. Distance fields are central objects in shape representation, while topological data analysis uses algebraic topology…

Algebraic Topology · Mathematics 2023-07-04 Anna Song , Ka Man Yim , Anthea Monod
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