Deep learning in the heterotic orbifold landscape

• Published in: Nuclear physics. B Vol. 940; pp. 113 - 129
• Main Authors: Mütter, Andreas, Parr, Erik, Vaudrevange, Patrick K.S.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.03.2019; Elsevier

We use deep autoencoder neural networks to draw a chart of the heterotic Z6-II orbifold landscape. Even though the autoencoder is trained without knowing the phenomenological properties of the Z6-II orbifold models, it identifies fertile islands in this chart where phenomenologically promising model...