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Barcodes of Towers and a Streaming Algorithm for Persistent Homology

A tower is a sequence of simplicial complexes connected by simplicial maps. We show how to compute a filtration, a sequence of nested simplicial complexes, with the same persistent barcode as the tower. Our approach is based on the coning strategy by Dey et al. (SoCG, 2014). We show that a variant o...

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Detalles Bibliográficos
Autores principales: Kerber, Michael, Schreiber, Hannah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6486534/
https://www.ncbi.nlm.nih.gov/pubmed/31105367
http://dx.doi.org/10.1007/s00454-018-0030-0
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author Kerber, Michael
Schreiber, Hannah
author_facet Kerber, Michael
Schreiber, Hannah
author_sort Kerber, Michael
collection PubMed
description A tower is a sequence of simplicial complexes connected by simplicial maps. We show how to compute a filtration, a sequence of nested simplicial complexes, with the same persistent barcode as the tower. Our approach is based on the coning strategy by Dey et al. (SoCG, 2014). We show that a variant of this approach yields a filtration that is asymptotically only marginally larger than the tower and can be efficiently computed by a streaming algorithm, both in theory and in practice. Furthermore, we show that our approach can be combined with a streaming algorithm to compute the barcode of the tower via matrix reduction. The space complexity of the algorithm does not depend on the length of the tower, but the maximal size of any subcomplex within the tower. Experimental evaluations show that our approach can efficiently handle towers with billions of complexes.
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spelling pubmed-64865342019-05-15 Barcodes of Towers and a Streaming Algorithm for Persistent Homology Kerber, Michael Schreiber, Hannah Discrete Comput Geom Article A tower is a sequence of simplicial complexes connected by simplicial maps. We show how to compute a filtration, a sequence of nested simplicial complexes, with the same persistent barcode as the tower. Our approach is based on the coning strategy by Dey et al. (SoCG, 2014). We show that a variant of this approach yields a filtration that is asymptotically only marginally larger than the tower and can be efficiently computed by a streaming algorithm, both in theory and in practice. Furthermore, we show that our approach can be combined with a streaming algorithm to compute the barcode of the tower via matrix reduction. The space complexity of the algorithm does not depend on the length of the tower, but the maximal size of any subcomplex within the tower. Experimental evaluations show that our approach can efficiently handle towers with billions of complexes. Springer US 2018-10-01 2019 /pmc/articles/PMC6486534/ /pubmed/31105367 http://dx.doi.org/10.1007/s00454-018-0030-0 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Kerber, Michael
Schreiber, Hannah
Barcodes of Towers and a Streaming Algorithm for Persistent Homology
title Barcodes of Towers and a Streaming Algorithm for Persistent Homology
title_full Barcodes of Towers and a Streaming Algorithm for Persistent Homology
title_fullStr Barcodes of Towers and a Streaming Algorithm for Persistent Homology
title_full_unstemmed Barcodes of Towers and a Streaming Algorithm for Persistent Homology
title_short Barcodes of Towers and a Streaming Algorithm for Persistent Homology
title_sort barcodes of towers and a streaming algorithm for persistent homology
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6486534/
https://www.ncbi.nlm.nih.gov/pubmed/31105367
http://dx.doi.org/10.1007/s00454-018-0030-0
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