Minimum cycle and homology bases of surface embedded graphs
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Abstract (arXiv)
We study the problems of finding a minimum cycle basis (a minimum weight set of cycles that form a basis for the cycle space) and a minimum homology basis (a minimum weight set of cycles that generates the 1-dimensional (mathbbZ2)-homology classes) of an undirected graph embedded on a surface. The problems are closely related, because the minimum cycle basis of a graph contains its minimum homology basis, and the minimum homology basis of the 1-skeleton of any graph is exactly its minimum cycle basis. For the minimum cycle basis problem, we give a deterministic O(nω+22gn2+m)-time algorithm for graphs embedded on an orientable surface of genus g. The best known existing algorithms for surface embedded graphs are those for general graphs: an O(mω) time Monte Carlo algorithm and a deterministic O(nm2/log n + n2 m) time algorithm. For the minimum homology basis problem, we give a deterministic O((g+b)3 n log n + m)-time algorithm for graphs embedded on an orientable or non-orientable surface of genus g with b boundary components, assuming shortest paths are unique, improving on existing algorithms for many values of g and n. The assumption of unique shortest paths can be avoided with high probability using randomization or deterministically by increasing the running time of the homology basis algorithm by a factor of O(log n).
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Jul 2016.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 1.
2 papers.
- 2021Dist2Cycle: A Simplicial Neural Network for Homology Localizationcited by 16
- 2024Geometric Localization of Homology Cyclescited by 0
- 2024Geometric Localization of Homology Cycles5 Jun 2024
- 2021Dist2Cycle: A Simplicial Neural Network for Homology Localization28 Oct 2021