Hardness of Approximation for Morse Matching
Ulrich Bauer, Abhishek Rathod

TL;DR
This paper investigates the computational difficulty of approximating Morse matching problems in discrete Morse theory, establishing NP-hardness and UGC-hardness results for various variants and dimensions, highlighting fundamental limits of current heuristics.
Contribution
It proves new hardness of approximation results for Max-Morse and Min-Morse matching problems, clarifying their computational intractability in low-dimensional complexes.
Findings
NP-hard to approximate Min-Morse matching within a factor of $O(n^{1-\e})$ for $d \,\leq\, 3$
NP-hard and UGC-hard to approximate Max-Morse matching within explicit constant factors for $d \,\leq\, 2$
Establishes theoretical limits for heuristic algorithms in discrete Morse theory
Abstract
Discrete Morse theory has emerged as a powerful tool for a wide range of problems, including the computation of (persistent) homology. In this context, discrete Morse theory is used to reduce the problem of computing a topological invariant of an input simplicial complex to computing the same topological invariant of a (significantly smaller) collapsed cell or chain complex. Consequently, devising methods for obtaining gradient vector fields on complexes to reduce the size of the problem instance has become an emerging theme over the last decade. While computing the optimal gradient vector field on a simplicial complex is NP-hard, several heuristics have been observed to compute near-optimal gradient vector fields on a wide variety of datasets. Understanding the theoretical limits of these strategies is therefore a fundamental problem in computational topology. In this paper, we…
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