94 citations · 213 across the 9 of their papers we have counts for
20 papers
Numerical Metrics for Complete Intersection and Kreuzer-Skarke Calabi-Yau Manifolds
Magdalena Larfors, Andre Lukas, Fabian Ruehle +1
We introduce neural networks to compute numerical Ricci-flat CY metrics for complete intersection and Kreuzer-Skarke Calabi-Yau manifolds at any point in Kähler and complex structu…
Learning Size and Shape of Calabi-Yau Spaces
Magdalena Larfors, Andre Lukas, Fabian Ruehle +1
We present a new machine learning library for computing metrics of string compactification spaces. We benchmark the performance on Monte-Carlo sampled integrals against previous nu…
Swampland Conjectures and Infinite Flop Chains
Callum R. Brodie, Andrei Constantin, Andre Lukas +1
We investigate swampland conjectures for quantum gravity in the context of M-theory compactified on Calabi-Yau threefolds which admit infinite sequences of flops. Naively, the modu…
Moduli-dependent KK towers and the swampland distance conjecture on the quintic Calabi-Yau manifold
Anthony Ashmore, Fabian Ruehle
We use numerical methods to obtain moduli-dependent Calabi-Yau metrics and from them the moduli-dependent massive tower of Kaluza-Klein states for the one-parameter family of quint…
Moduli-dependent Calabi-Yau and SU(3)-structure metrics from Machine Learning
Lara B. Anderson, Mathis Gerdes, James Gray +3
We use machine learning to approximate Calabi-Yau and SU(3)-structure metrics, including for the first time complex structure moduli dependence. Our new methods furthermore improve…
Learning to Unknot
Sergei Gukov, James Halverson, Fabian Ruehle +1
We introduce natural language processing into the study of knot theory, as made natural by the braid word representation of knots. We study the UNKNOT problem of determining whethe…