4 papers
Sven: Singular Value Descent as a Computationally Efficient Natural Gradient Method
Samuel Bright-Thonney, Thomas R. Harvey, Andre Lukas +1
We introduce Sven (Singular Value dEsceNt), a new optimization algorithm for neural networks that exploits the natural decomposition of loss functions into a sum over individual da…
Reproducing Standard Model Fermion Masses and Mixing in String Theory: A Heterotic Line Bundle Study
Andrei Constantin, Lucas T. -Y. Leung, Andre Lukas +1
Deriving the Yukawa couplings and the resulting fermion masses and mixing angles of the Standard Model (SM) from a more fundamental theory remains one of the central outstanding pr…
Approximate Ricci-flat Metrics for Calabi-Yau Manifolds
Seung-Joo Lee, Andre Lukas
We outline a method to determine analytic Kähler potentials with associated approximately Ricci-flat Kähler metrics on Calabi-Yau manifolds. Key ingredients are numerically calcula…
Fermion Masses and Mixing in String-Inspired Models
Andrei Constantin, Kit Fraser-Taliente, Thomas R. Harvey +2
We study a class of supersymmetric Froggatt-Nielsen (FN) models with multiple U(1) symmetries and Standard Model (SM) singlets inspired by heterotic string compactifications on Cal…