most citedA machine learning pipeline for autonomous numerical analytic continuation of Dyson-Schwinger equations

2 citations · 2 across the 1 of their papers we have counts for

collaborators

1 paper

hep-ph2021★ 2 cited

A machine learning pipeline for autonomous numerical analytic continuation of Dyson-Schwinger equations

Andreas Windisch, Thomas Gallien, Christopher Schwarzlmueller

Dyson-Schwinger equations (DSEs) are a non-perturbative way to express n-point functions in quantum field theory. Working in Euclidean space and in Landau gauge, for example, one c…