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(N$^3$LL) 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)
Marco Radici
Matteo Cerutti
(Christopher Newport University and Jefferson Lab)
Simone Rodini
(University of Regensburg)
Dr
Valerio Bertone
(C.E.A. Paris-Saclay)
