Machine Learning $\mathcal{N}=8,D=5$ Gauged Supergravity

Abstract

Type IIB string theory on a 5-sphere gives rise to $\mathcal{N}=8,SO(6)$ 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 $E_{6(6)}/USp(8)$ 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 $\mathcal{N}=2$ supersymmetric point identified by Khavaev, Pilch and Warner.

v3: precision of gravitino masses at three of the critical points tightened, other minor improvements. Published version + a note added + refs

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• Tachyonic Kaluza-Klein modes and the AdS swampland conjecture
• Brane-Jet Instabilities
• The Holographic Conformal Manifold of 3d $\mathcal{N}=2$ $S$-fold SCFTs
• Brane-jet stability of non-supersymmetric AdS vacua
• Learning the black hole metric from holographic conductivity
• Kaluza-Klein Spectroscopy for the Leigh-Strassler SCFT
• Spinor-helicity formalism for massive and massless amplitudes in five dimensions
• Super-Chern-Simons spectra from Exceptional Field Theory
• New AdS${}_4$ Vacua in Dyonic ISO(7) Gauged Supergravity
• Vacua of $\omega$-deformed SO(8) supergravity
• Old and new vacua of 5D maximal supergravity
• Machine-Learning the Classification of Spacetimes
• New methods for old problems: vacua of maximal D = 7 supergravities