14 citations · 14 across the 3 of their papers we have counts for
4 papers
Learning Scattering Amplitudes with Transformer Reinforcement Learning
Philip Velie, Tianji Cai, Piyush Jha +2
We introduce a transformer reinforcement learning algorithm that learns to solve high loop-level scattering amplitudes in planar N = 4 Super Yang-Mills theory. Our algorithm improv…
Toward a Community Roadmap for High Energy Physics and Artificial Intelligence in China and Beyond
Tianji Cai, Ke Li, Teng Li
Artificial Intelligence (AI) is rapidly transforming scientific research and has become central to many data-intensive disciplines. High Energy Physics (HEP), with its vast data vo…
Recurrent Features of Amplitudes in Planar Super Yang-Mills Theory
Tianji Cai, François Charton, Kyle Cranmer +3
The planar three-gluon form factor for the chiral stress tensor operator in planar maximally supersymmetric Yang-Mills theory is an analog of the Higgs-to-three-gluon scattering am…
Transforming the Bootstrap: Using Transformers to Compute Scattering Amplitudes in Planar N = 4 Super Yang-Mills Theory
Tianji Cai, Garrett W. Merz, François Charton +4
We pursue the use of deep learning methods to improve state-of-the-art computations in theoretical high-energy physics. Planar N = 4 Super Yang-Mills theory is a close cousin to th…