Subdivision bifiltration

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In topological data analysis, a subdivision bifiltration is a collection of filtered simplicial complexes, typically built upon a set of data points in a metric space, that captures shape and density information about the underlying data set. The subdivision bifiltration relies on a natural filtration of the barycentric subdivision of a simplicial complex by flags of minimum dimension, which encodes density information about the metric space upon which the complex is built. The subdivision bifiltration was first introduced by Donald Sheehy in 2011 as part of his doctoral thesis [1] (later subsumed by a conference paper in 2012 [2] ) as a discrete model of the multicover bifiltration, a continuous construction whose underlying framework dates back to the 1970s. [3] In particular, Sheehy applied the construction to both the Vietoris-Rips and Čech filtrations, two common objects in the field of topological data analysis. [4] [5] [6] Whereas single parameter filtrations are not robust with respect to outliers in the data, [7] the subdivision-Rips and -Cech bifiltrations satisfy several desirable stability properties. [8]

Contents

Definition

Let be a simplicial complex. Then a nested sequence of simplices of is called a flag or chain of . The set of all flags of comprises an abstract simplicial complex, known as the barycentric subdivision of , denoted by . The barycentric subdivision is naturally identified with a geometric subdivision of , created by starring the geometric realization of at the barycenter of each simplex. [9]

There is a natural filtration on by considering for each natural number the maximal subcomplex of spanned by vertices of corresponding to simplices of of dimension at least , which is denoted . In particular, by this convention, then . Considering the sequence of nested subcomplexes given by varying the parameter , we obtain a filtration on known as the subdivision filtration. Since the complexes in the subdivision filtration shrink as increases, we can regard it as a functor from the opposite posetal category to the category of simplicial complexes and simplicial maps.

Let be a partially ordered set. Given a simplicial filtration , regarded as a functor from the posetal category of to the category , by applying the subdivision filtration object-wise on , we obtain a two-parameter filtration , called the subdivision bifiltration. [10]

In particular, when we take to be the Rips or Čech filtration, we obtain bifiltrations and , respectively.

Properties

The subdivision-Čech bifiltration is weakly equivalent to the multicover bifiltration, implying that they have isomorphic persistent homology. A combinatorial proof of this statement was given in Sheehy's original conference paper, but a more algebraic version was presented in 2017 by Cavanna et al. [11] The ideas from Cavanna's proof were later generalized by Blumberg and Lesnick in a 2022 paper on 2-parameter persistent homology. [8]

By the size of a bifiltration, we mean the number of simplices in the largest complex. The subdivision-Čech bifiltration has exponential size as a function of the number of vertices. [12] This implies that its homology cannot be directly computed in polynomial time. However, for points in Euclidean space, the homology of subdivision-Čech can be computed in polynomial time, up to weak equivalence, via a construction known as the rhomboid bifiltration. As a precursor to the rhomboid bifiltration, Edelsbrunner and Osang presented in 2021 a polyhedral cell complex called the rhomboid tiling, which they used to compute horizontal or vertices slices of the multicover bifiltration up to weak equivalence. [13] This was extended a year later by Corbet et al. to the rhomboid bifiltration, which is weakly equivalent to the multicover bifiltration, but has polynomial size. [12]

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<span class="mw-page-title-main">Multicover bifiltration</span>

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A persistence module is a mathematical structure in persistent homology and topological data analysis that formally captures the persistence of topological features of an object across a range of scale parameters. A persistence module often consists of a collection of homology groups corresponding to a filtration of topological spaces, and a collection of linear maps induced by the inclusions of the filtration. The concept of a persistence module was first introduced in 2005 as an application of graded modules over polynomial rings, thus importing well-developed algebraic ideas from classical commutative algebra theory to the setting of persistent homology. Since then, persistence modules have been one of the primary algebraic structures studied in the field of applied topology.

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In persistent homology, a persistent Betti number is a multiscale analog of a Betti number that tracks the number of topological features that persist over multiple scale parameters in a filtration. Whereas the classical Betti number equals the rank of the homology group, the persistent Betti number is the rank of the persistent homology group. The concept of a persistent Betti number was introduced by Herbert Edelsbrunner, David Letscher, and Afra Zomorodian in the 2002 paper Topological Persistence and Simplification, one of the seminal papers in the field of persistent homology and topological data analysis. Applications of the persistent Betti number appear in a variety of fields including data analysis, machine learning, and physics.

References

  1. Sheehy, D. R. (2011). Mesh generation and geometric persistent homology (Doctoral dissertation, Carnegie Mellon University).
  2. Sheehy, Donald R. 2012. “A Multicover Nerve for Geometric Inference.” in CCCG: Canadian conference in computational geometry.
  3. Fejes Tóth, G. (March 1976). "Multiple packing and covering of the plane with circles". Acta Mathematica Academiae Scientiarum Hungaricae. 27 (1–2): 135–140. doi:10.1007/BF01896768. ISSN   0001-5954. S2CID   189778121.
  4. Chazal, Frédéric; Oudot, Steve Yann (2008). "Towards persistence-based reconstruction in euclidean spaces". Proceedings of the twenty-fourth annual symposium on Computational geometry. pp. 232–241. arXiv: 0712.2638 . doi:10.1145/1377676.1377719. ISBN   9781605580715. S2CID   1020710.
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  8. 1 2 Blumberg, Andrew J.; Lesnick, Michael (2022-10-17). "Stability of 2-Parameter Persistent Homology". Foundations of Computational Mathematics. arXiv: 2010.09628 . doi:10.1007/s10208-022-09576-6. ISSN   1615-3375. S2CID   224705357.
  9. Rourke, C. P. (1982). Introduction to piecewise-linear topology. B. J. Sanderson. Berlin: Springer-Verlag. ISBN   0-387-11102-6. OCLC   7948164.
  10. Lesnick, Michael (11 March 2023). "Lecture notes for AMAT 840: Multiparameter Persistence" (PDF). Retrieved 27 March 2023.
  11. Cavanna, Nicholas J.; Gardner, Kirk P.; Sheehy, Donald R. (2017). "When and Why the Topological Coverage Criterion Works". Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms. pp. 2679–2690. doi:10.1137/1.9781611974782.177. ISBN   978-1-61197-478-2.
  12. 1 2 Corbet, René; Kerber, Michael; Lesnick, Michael; Osang, Georg (2023-02-20). "Computing the Multicover Bifiltration". Discrete & Computational Geometry. 70 (2): 376–405. arXiv: 2103.07823 . doi:10.1007/s00454-022-00476-8. ISSN   0179-5376. PMC   10423148 . PMID   37581017.
  13. Edelsbrunner, Herbert; Osang, Georg (2021). "The Multi-Cover Persistence of Euclidean Balls". Discrete & Computational Geometry. 65 (4): 1296–1313. doi:10.1007/s00454-021-00281-9. ISSN   0179-5376. PMC   8550220 . PMID   34720303.