Calabi-Yau Links and Machine Learning
High Energy Physics - Theory
2024-01-23 v1
Abstract
Calabi-Yau links are specific -fibrations over Calabi-Yau manifolds, when the link is 7-dimensional they exhibit both Sasakian and G2 structures. In this invited contribution to the DANGER proceedings, previous work exhaustively computing Calabi-Yau links and selected topological properties is summarised. Machine learning of these properties inspires new conjectures about their computation, as well as the respective Gr\"obner bases.
Keywords
Cite
@article{arxiv.2401.11550,
title = {Calabi-Yau Links and Machine Learning},
author = {Edward Hirst},
journal= {arXiv preprint arXiv:2401.11550},
year = {2024}
}
Comments
Invited contribution to IJDSMS as part of the DANGER proceedings; 8 pages; 4 figures