Speaker
Chiara Bissolotti
(Argonne National Laboratory)
Description
We present the first proof of concept extraction using neural networks (NNs) of the unpolarised transverse-momentum distributions (TMDs) at next-to-next-to-next-to- leading logarithmic (N3LL) accuracy. By offering a more flexible and adaptable approach, NNs overcome some of the limitations of traditional functional forms, providing a better description of data. This work focuses exclusively on Drell-Yan (DY) data and establishes the feasibility of NN-based TMD extractions.
Authors
Prof.
Alessandro Bacchetta
Chiara Bissolotti
(Argonne National Laboratory)
Mr
Lorenzo Rossi
(University of Milan & INFN)
Marco Radici
Matteo Cerutti
(Hampton University and Jefferson Lab)
Simone Rodini
(University of Regensburg)
Dr
Valerio Bertone
(C.E.A. Paris-Saclay)
