Machine Learning for the precision determination of Parton Distribution Functions

by Jesús Urtasun Elizari (Milan University & INFN Milan)

Thursday 30 Jan 2020, 12:00 → 13:00 Europe/Madrid

IFAE seminar room (IFAE)

Parton Distribution Functions (PDFs) are crucial objects in high energy physics, specially in the precision era of the LHC. The non-perturbative nature of PDFs makes them impossible to compute at present, and therefore they need to be extracted from data through complex fitting systems. The determination of PDFs requires three time dependent factors: new experimental data, higher order theoretical predictions and fitting methodology. The NNPDF collaboration has pioneered the use of artificial intelligence techniques in this context, and the N3PDF group is currently exploring modern Machine Learning methods in order to better exploit the wealth of experimental and theoretical information driven by the LHC.