Speaker
Description
We pursue the use of Transformers to compute scattering amplitudes in planar N = 4 super-Yang-Mills theory, a quantum field theory closely related to Quantum Chromodynamics (QCD). By expanding multiple polylogarithm functions in the Feynman integrals using the symbol map, we formulate scattering amplitudes in a language-based representation that is amenable to Transformer architectures and standard training objectives. We then show that an encoder-decoder Transformer can achieve high accuracy (> 98%) on two tasks in this representation- prediction of the integer coefficients of individual terms at a given loop order from the terms themselves, and prediction of coefficients at one loop order from a related subset of coefficients at a lower loop order. Finally, we explore interesting properties of the learning dynamics and representations learned by our model.
