Machine-Learning the String Theory Landscape: Beyond SageMath and Macaulay2

Tuesday, July 23, 2019 - 2:45pm - 3:30pm
Lind 305
Yang-Hui He (University of London)
We present an overview of how SageMath and Macaulay2 have provided crucial computational help and insight to problems in string theory over the last decade. As concrete examples, we will use the Calabi-Yau landscape.
In parallel, we propose a paradigm to machine-learn the ever-expanding databases which have emerged in mathematical physics, algebraic geometry and particle phenomenology, in efficiently addressing such problems as computing Hodge numbers, recognizing elliptic fibrations, distinguishing finite simple groups, etc. The mysterious success of ML, often bypassing traditional expensive algorithms, potentially suggests hithertofore unseen structures.