Persistence Diagrams as Diagrams: A Categorification of the Stability Theorem
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Abstract (arXiv)
Persistent homology, a central tool of topological data analysis, provides invariants of data called barcodes (also known as persistence diagrams). A barcode is simply a multiset of real intervals. Recent work of Edelsbrunner, Jablonski, and Mrozek suggests an equivalent description of barcodes as functors R -> Mch, where R is the poset category of real numbers and Mch is the category whose objects are sets and whose morphisms are matchings (i.e., partial injective functions). Such functors form a category Mch^R whose morphisms are the natural transformations. Thus, this interpretation of barcodes gives us a hitherto unstudied categorical structure on barcodes. The aim of this note is to show that this categorical structure leads to surprisingly simple reformulations of both the well-known stability theorem for persistent homology and a recent generalization called the induced matching theorem.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 31 Oct 2016.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 1.
3 papers.
- 2024Topologically Faithful Multi-class Segmentation in Medical Imagescited by 12
- 2022Approximating Persistent Homology for Large Datasetscited by 8
- 2021The Universal ℓp-Metric on Merge Treescited by 0
- 2024Topologically Faithful Multi-class Segmentation in Medical Images16 Mar 2024
- 2022Approximating Persistent Homology for Large Datasets19 Apr 2022
- 2021The Universal ℓp-Metric on Merge Trees22 Dec 2021