Detmold, Pochinsky and Shanahan have recently been granted an Aurora Early Science for Data and Learning award along with Kyle Cranmer at NYU. This project aims to use machine learning to significantly speed up critical parts of lattice QCD calculations such as the hybrid Monte Carlo (HMC) algorithm, quark propagator calculations, and many body contraction algorithms. The physics focus of this project is the interactions of nuclei with dark matter.
