Machine Learning ${\cal N}=8, D=5$ Gauged Supergravity
Abstract
Type IIB string theory on a 5-sphere gives rise to gauged supergravity in five dimensions. Motivated by the fact that this is the context of the most widely studied example of the AdS/CFT correspondence, we undertake an investigation of its critical points. The scalar manifold is an coset, and the challenge is that it is 42-dimensional. We take a Machine Learning approach to the problem using TensorFlow, and this results in a substantial increase in the number of known critical points. Our list of 32 critical points contains all five of the previously known ones, including an supersymmetric point identified by Khavaev, Pilch and Warner.
Cite
@article{arxiv.2002.12927,
title = {Machine Learning ${\cal N}=8, D=5$ Gauged Supergravity},
author = {Chethan Krishnan and Vyshnav Mohan and Soham Ray},
journal= {arXiv preprint arXiv:2002.12927},
year = {2020}
}
Comments
v3: precision of gravitino masses at three of the critical points tightened, other minor improvements. Published version + a note added + refs