A statistical approach to knot confinement via persistent homology

Daniele Celoria1, Barbara I Mahler1

  • 1Mathematical Institute, University of Oxford, Radcliffe Observatory, Andrew Wiles Building, Woodstock Rd, Oxford OX2 6GG, UK.

Proceedings. Mathematical, Physical, and Engineering Sciences
|June 1, 2022
PubMed
Summary

This study uses topological methods and persistent homology to analyze how random knots fill space. Findings reveal correlations between knot geometry and topological features, offering a way to measure knot deviations.

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