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Improved approximate rips filtrations with shifted integer lattices and cubical complexes

Rips complexes are important structures for analyzing topological features of metric spaces. Unfortunately, generating these complexes is expensive because of a combinatorial explosion in the complex size. For n points in [Formula: see text] , we present a scheme to construct a 2-approximation of th...

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Detalles Bibliográficos
Autores principales: Choudhary, Aruni, Kerber, Michael, Raghvendra, Sharath
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8549989/
https://www.ncbi.nlm.nih.gov/pubmed/34722862
http://dx.doi.org/10.1007/s41468-021-00072-4
Descripción
Sumario:Rips complexes are important structures for analyzing topological features of metric spaces. Unfortunately, generating these complexes is expensive because of a combinatorial explosion in the complex size. For n points in [Formula: see text] , we present a scheme to construct a 2-approximation of the filtration of the Rips complex in the [Formula: see text] -norm, which extends to a [Formula: see text] -approximation in the Euclidean case. The k-skeleton of the resulting approximation has a total size of [Formula: see text] . The scheme is based on the integer lattice and simplicial complexes based on the barycentric subdivision of the d-cube. We extend our result to use cubical complexes in place of simplicial complexes by introducing cubical maps between complexes. We get the same approximation guarantee as the simplicial case, while reducing the total size of the approximation to only [Formula: see text] (cubical) cells. There are two novel techniques that we use in this paper. The first is the use of acyclic carriers for proving our approximation result. In our application, these are maps which relate the Rips complex and the approximation in a relatively simple manner and greatly reduce the complexity of showing the approximation guarantee. The second technique is what we refer to as scale balancing, which is a simple trick to improve the approximation ratio under certain conditions.