The Art of Knot Data

Year: 2024 Authors: Paweł Dłotko; Davide Gurnari; Radmila Sazdanovic

Core claim

Knot invariants can be treated as big data, and Ball Mapper reveals both mathematical patterns and aesthetic images from their global structure.

Topics

knot theory as big data, Ball Mapper visualization, generative art

Domains

knot theory, topological data analysis, machine learning, generative art, data visualization, mathematics and art

Methods

dimension reduction, Ball Mapper, principal component analysis, UMAP, t-SNE

Media

Alexander polynomial data, knot invariants, interactive 3D plots

Source status

This page publishes metadata and extracted analytical signals only. Raw PDF and full OCR text are kept local for now.