Speaker
Lara B. Anderson
Description
The metric on the compact internal geometry of a string compacitification has long stood as an important missing piece in the study of low energy physics arising from string theory. I will review recent progress using machine learning to approximate Calabi-Yau and SU(3)-structure metrics, including for the first time their dependence. These methods are demonstrated for Calabi-Yau as well as SU(3)-structure manifolds.
