University of Cambridge > Talks.cam > Algebraic Geometry Seminar > Machine learning detects terminal singularities

Machine learning detects terminal singularities

Add to your list(s) Download to your calendar using vCal

  • UserSara Veneziale, Imperial College London
  • ClockWednesday 14 February 2024, 14:15-15:15
  • HouseCMS MR13.

If you have a question about this talk, please contact Holly Krieger.

In this talk, I will describe recent work in the application of machine learning to explore questions in algebraic geometry, specifically in the context of the study of Q-Fano varieties. These are Q-factorial terminal Fano varieties, and they are the key players in the Minimal Model Program. In this work, we ask and answer if machine learning can determine if a toric Fano variety has terminal singularities. We build a high-accuracy neural network that detects this, which has two consequences. Firstly, it inspires the formulation and proof of a new global, combinatorial criterion to determine if a toric variety of Picard rank two has terminal singularities. Secondly, the machine learning model is used directly to give the first sketch of the landscape of Q-Fano varieties in dimension eight. This is joint work with Tom Coates and Al Kasprzyk.

This talk is part of the Algebraic Geometry Seminar series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2024 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity