Computing Betti tables and minimal presentations of zero-dimensional persistent homology

TL;DR

This paper presents efficient algorithms for computing Betti tables and minimal presentations of zero-dimensional persistent homology, significantly improving performance for large datasets in topological data analysis.

Contribution

It introduces log-linear time algorithms for Betti tables and quadratic time algorithms for minimal presentations in zero-dimensional cases, enhancing scalability.

Findings

Bigraded Betti tables can be computed in log-linear time for zero-dimensional homology.

Minimal presentations can be computed in quadratic time regardless of grading complexity.

Algorithms outperform existing methods on large datasets.

Abstract

The Betti tables of a multigraded module encode the grades at which there is an algebraic change in the module. Multigraded modules show up in many areas of pure and applied mathematics, and in particular in topological data analysis, where they are known as persistence modules, and where their Betti tables describe the places at which the homology of filtered simplicial complexes changes. Although Betti tables of singly and bigraded modules are already being used in applications of topological data analysis, their computation in the bigraded case (which relies on an algorithm that is cubic in the size of the filtered simplicial complex) is a bottleneck when working with large datasets. We show that, in the special case of zero-dimensional homology (relevant for clustering and graph classification) Betti tables of bigraded modules can be computed in log-linear time. We also consider the problem of computing minimal presentations, and show that minimal presentations of zero-dimensional persistent homology can be computed in quadratic time, regardless of the grading poset.