Expected Complexity of Persistence Barcode Computation via Matrix Reduction

Fuente: arXiv
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Auteurs principaux: Giunti, Barbara, Houry, Guillaume, Kerber, Michael, Söls, Matthias
Format: Preprint
Publié: 2021
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author Giunti, Barbara
Houry, Guillaume
Kerber, Michael
Söls, Matthias
author_facet Giunti, Barbara
Houry, Guillaume
Kerber, Michael
Söls, Matthias
contents We study the algorithmic complexity of computing the persistence barcode of a randomly generated filtration. We provide a general technique to bound the expected complexity of reducing the boundary matrix in terms of the density of its reduced form. We apply this technique finding upper bounds for the average fill-in (number of non-zero entries) of the boundary matrix on Čech, Vietoris--Rips and Erdős--Rényi filtrations after matrix reduction, thus obtaining bounds on the expected complexity of the barcode computation. Our method is based on previous results on the expected Betti numbers of the corresponding complexes. Our fill-in bounds for Čech and Vietoris--Rips complexes are asymptotically tight up to a logarithmic factor. In particular, both our fill-in and computation bounds are better than the worst-case estimates. We also provide an Erdős--Rényi filtration realising the worst-case fill-in and computation.
format Preprint
id arxiv_https___arxiv_org_abs_2111_02125
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Expected Complexity of Persistence Barcode Computation via Matrix Reduction
Giunti, Barbara
Houry, Guillaume
Kerber, Michael
Söls, Matthias
Algebraic Topology
Computational Complexity
We study the algorithmic complexity of computing the persistence barcode of a randomly generated filtration. We provide a general technique to bound the expected complexity of reducing the boundary matrix in terms of the density of its reduced form. We apply this technique finding upper bounds for the average fill-in (number of non-zero entries) of the boundary matrix on Čech, Vietoris--Rips and Erdős--Rényi filtrations after matrix reduction, thus obtaining bounds on the expected complexity of the barcode computation. Our method is based on previous results on the expected Betti numbers of the corresponding complexes. Our fill-in bounds for Čech and Vietoris--Rips complexes are asymptotically tight up to a logarithmic factor. In particular, both our fill-in and computation bounds are better than the worst-case estimates. We also provide an Erdős--Rényi filtration realising the worst-case fill-in and computation.
title Expected Complexity of Persistence Barcode Computation via Matrix Reduction
topic Algebraic Topology
Computational Complexity
url https://arxiv.org/abs/2111.02125