Learning Feynman Diagrams using Graph Neural Networks

no code implementations • 25 Nov 2022 • Harrison Mitchell, Alexander Norcliffe, Pietro Liò

In the wake of the growing popularity of machine learning in particle physics, this work finds a new application of geometric deep learning on Feynman diagrams to make accurate and fast matrix element predictions with the potential to be used in analysis of quantum field theory.

Graph Attention