Neural Network Gauge Field Transformation for 4D SU(3) gauge fields

Abstract

We construct neural networks that work for any Lie group and maintain gauge covariance, enabling smooth, invertible gauge field transformations. We implement these transformations for 4D SU(3) lattice gauge fields and explore their use in HMC. We focus on developing loss functions and optimizing the transformations. We show the effects on HMC's molecular dynamics and discuss the scalability of the approach.

Comments: 10 pages, 3 figures, The 40th International Symposium on Lattice Field Theory (Lattice 2023), July 31st - August 4th, 2023, Fermi National Accelerator Laboratory