Multidimensional Persistence and Noise

Scolamiero, Martina; Chachólski, Wojciech; Lundman, Anders; Ramanujam, Ryan; Öberg, Sebastian
December 2017
Foundations of Computational Mathematics;Dec2017, Vol. 17 Issue 6, p1367
Academic Journal
In this paper, we study multidimensional persistence modules (Carlsson and Zomorodian in Discrete Comput Geom 42(1):71-93, 2009; Lesnick in Found Comput Math 15(3):613-650, 2015) via what we call tame functors and noise systems. A noise system leads to a pseudometric topology on the category of tame functors. We show how this pseudometric can be used to identify persistent features of compact multidimensional persistence modules. To count such features, we introduce the feature counting invariant and prove that assigning this invariant to compact tame functors is a 1-Lipschitz operation. For one-dimensional persistence, we explain how, by choosing an appropriate noise system, the feature counting invariant identifies the same persistent features as the classical barcode construction.


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