Light-Cone 2023: Hadrons and Symmetries

Training the machine for learning how to predict the infrared gluon two-point correlation function

Non programmé

20m

Rio de Janeiro, Brazil

Poster

Orateur

Rodrigo Carmo Terin (Instituto Tecnológico de Aeronáutica)

Description

We exploit the use of one of the specific tools of Artificial Intelligence, the Machine Learning setup, to apply it in the infrared quantum chromodynamics context. We display all the required phases that the machine needs to learn to discover how it behaves the already existing gluon two-point correlation function provided by lattice numerical simulations starting from computing error metrics, training instances, and the use of the cross-validation method and then through the previous knowledge acquired by our built-up machine, it can predict in the unseen data the boot samples values in a lattice infrared phantom zone.