Speaker: Daniel Hackett (Fermilab)

Host: Srimoyee Sen

Title: Machine Learning for the Strong Force

Abstract: Quantum chromodynamics (QCD) is the quantum field theory that describes the strong nuclear force. Its emergent dynamics generate virtually all of the (visible) mass in the universe, give rise to diverse nuclei and thus allow for complex chemistry and the emergence of life, and shape the substructure of hadrons. As part of the Standard Model, it is fundamental to the best of our present understanding. It is also incredibly difficult to calculate with. In this colloquium, I will discuss two emerging applications of machine learning to QCD challenges: normalizing flows to accelerate numerical lattice QCD calculations, and machine-learned models of neutrino-nucleus cross sections for DUNE.