A statistical approach to knot confinement via persistent homology

Journal article

In this paper, we study how randomly generated knots occupy a volume of space using topological methods. To this end, we consider the evolution of the first homology of an immersed metric neighbourhood of a knot’s embedding for growing radii. Specifically, we extract features from the persistent homology (PH) of the Vietoris–Rips complexes built from point clouds associated with knots. Statistical analysis of our data shows the existence of increasing correlations between geometric quantities associated with the embedding and PH-based features, as a function of the knots’ lengths. We further study the variation of these correlations for different knot types. Finally, this framework also allows us to define a simple notion of deviation from ideal configurations of knots.

Authors: Celoria, D; Mahler, BI

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: The Royal Society
• Journal: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
• Volume: 478
• Issue: 2261
• Pages: 20210709
• Article number: 20210709
• Publication date: 2022-05-18
• Acceptance date: 2022-04-08
• DOI: 10.1098/rspa.2021.0709
• EISSN: 1471-2946
• ISSN: 1364-5021
• Language: English
• Keywords: knots; persistent homology; topological data analysis