Topological Correlation
Fuente:
arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866916802930409472 |
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| author | Mastroianni, Isabella Fugacci, Ulderico |
| author_facet | Mastroianni, Isabella Fugacci, Ulderico |
| contents | We introduce two novel concepts, topological difference and topological correlation, that offer a new perspective on the discriminative power of multiparameter persistence. The former quantifies the discrepancy between multiparameter and monoparameter persistence, while the other leverages this gap to measure the interdependence of filtering functions. Our framework sheds light on the expressive advantage of multiparameter over monoparameter persistence and suggests potential applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_16985 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Topological Correlation Mastroianni, Isabella Fugacci, Ulderico Algebraic Topology Computational Geometry We introduce two novel concepts, topological difference and topological correlation, that offer a new perspective on the discriminative power of multiparameter persistence. The former quantifies the discrepancy between multiparameter and monoparameter persistence, while the other leverages this gap to measure the interdependence of filtering functions. Our framework sheds light on the expressive advantage of multiparameter over monoparameter persistence and suggests potential applications. |
| title | Topological Correlation |
| topic | Algebraic Topology Computational Geometry |
| url | https://arxiv.org/abs/2506.16985 |