Computing the multicover bifiltration
2021 (Engelska)Ingår i: Leibniz International Proceedings in Informatics, LIPIcs, Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing , 2021Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]
Given a finite set A ⊂ ℝd, let Covr,k denote the set of all points within distance r to at least k points of A. Allowing r and k to vary, we obtain a 2-parameter family of spaces that grow larger when r increases or k decreases, called the multicover bifiltration. Motivated by the problem of computing the homology of this bifiltration, we introduce two closely related combinatorial bifiltrations, one polyhedral and the other simplicial, which are both topologically equivalent to the multicover bifiltration and far smaller than a Čech-based model considered in prior work of Sheehy. Our polyhedral construction is a bifiltration of the rhomboid tiling of Edelsbrunner and Osang, and can be efficiently computed using a variant of an algorithm given by these authors as well. Using an implementation for dimension 2 and 3, we provide experimental results. Our simplicial construction is useful for understanding the polyhedral construction and proving its correctness.
Ort, förlag, år, upplaga, sidor
Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing , 2021.
Nyckelord [en]
Bifiltrations, Denoising, Higher-order Delaunay complexes, Higher-order Voronoi diagrams, Multiparameter persistent homology, Nerves, Rhomboid tiling, Topology, Finite set, K points, Computational geometry
Nationell ämneskategori
Datavetenskap (datalogi) Algebra och logik Beräkningsmatematik
Identifikatorer
URN: urn:nbn:se:kth:diva-309944DOI: 10.4230/LIPIcs.SoCG.2021.27Scopus ID: 2-s2.0-85108226630OAI: oai:DiVA.org:kth-309944DiVA, id: diva2:1645889
Konferens
37th International Symposium on Computational Geometry, SoCG 2021, 7 June 2021 through 11 June 2021
Anmärkning
Part of proceedings: ISBN 978-3-95977-184-9
QC 20220321
2022-03-212022-03-212023-01-18Bibliografiskt granskad