SO(8) Supergravity and the Magic of Machine Learning

Understand

Using de Wit-Nicolai $D=4\;\mathcal{N}=8\;SO(8)$ supergravity as an example, we show how modern Machine Learning software libraries such as Google's TensorFlow can be employed to greatly simplify the analysis of high-dimensional scalar sectors of some M-Theory compactifications.

• We provide detailed information on the location, symmetries, and particle spectra and charges of 192 critical points on the scalar manifold of SO(8) supergravity, including one newly discovered $\mathcal{N}=1$ vacuum with $SO(3)$ residual symmetry, one new potentially stabilizable non-supersymmetric solution, and examples for "Galois conjugate pairs" of solutions, i.e.
• solution-pairs that share the same gauge group embedding into~$SO(8)$ and minimal polynomials for the cosmological constant.
• Where feasible, we give analytic expressions for solution coordinates and cosmological constants.