Computing eulerian magnitude homology
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866914971582988288 |
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| author | Menara, Giuliamaria Manzoni, Luca |
| author_facet | Menara, Giuliamaria Manzoni, Luca |
| contents | In this paper tackle the problem of computing the ranks of certain eulerian magnitude homology groups of a graph G. First, we analyze the computational cost of our problem and prove that it is #W[1]-complete. Then we develop the first diagonal algorithm, a breadth-first-search-based algorithm parameterized by the diameter of the graph to calculate the ranks of the homology groups of interest. To do this, we leverage the close relationship between the combinatorics of the homology boundary map and the substructures appearing in the graph. We then discuss the feasibility of the presented algorithm and consider future perspectives. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_10376 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Computing eulerian magnitude homology Menara, Giuliamaria Manzoni, Luca Computational Complexity Combinatorics In this paper tackle the problem of computing the ranks of certain eulerian magnitude homology groups of a graph G. First, we analyze the computational cost of our problem and prove that it is #W[1]-complete. Then we develop the first diagonal algorithm, a breadth-first-search-based algorithm parameterized by the diameter of the graph to calculate the ranks of the homology groups of interest. To do this, we leverage the close relationship between the combinatorics of the homology boundary map and the substructures appearing in the graph. We then discuss the feasibility of the presented algorithm and consider future perspectives. |
| title | Computing eulerian magnitude homology |
| topic | Computational Complexity Combinatorics |
| url | https://arxiv.org/abs/2410.10376 |