%0 Electronic Article
%A Bacchetta, Alessandro
%A Bertone, Valerio
%A Bissolotti, Chiara
%A Cerutti, Matteo
%A Radici, Marco
%A Rodini, Simone
%A Rossi, Lorenzo
%T A Neural-Network Extraction ofUnpolarised Transverse-Momentum-Dependent Distributions
%N DESY-25-022
%M PUBDB-2025-00641
%M DESY-25-022
%M JLAB-THY-25-4221
%M arXiv:2502.04166
%D 2025
%X We present the first extraction from experimental Drell-Yan data of unpolarised transverse-momentum-dependent distributions using neural networks to parametrise their nonperturbativepart. We show that neural networks outperform traditional parametrisations achieving a betterdescription of data. This work not only establishes the feasibility of using neural networks to ex-plore the multi-dimensional partonic structure of hadrons, but also paves the way to more accuratedeterminations which exploit machine-learning techniques.
%F PUB:(DE-HGF)25
%9 Preprint
%R 10.3204/PUBDB-2025-00641
%U https://bib-pubdb1.desy.de/record/623193