{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/unpolarized-transverse-momentum-distributions","title":"Unpolarized Transverse Momentum Distributions from a global fit of Drell-Yan and Semi-Inclusive Deep-Inelastic Scattering data","arxiv_id":"2206.07598","date":"2022-06-15","proceeding":null,"authors":["Alessandro Bacchetta","Valerio Bertone","Chiara Bissolotti","Giuseppe Bozzi","Matteo Cerutti","Fulvio Piacenza","Marco Radici","Andrea Signori"],"abstract":"We present an extraction of unpolarized transverse-momentum-dependent parton distribution and fragmentation functions based on more than two thousands data points from several experiments for two different processes: semi-inclusive deep-inelastic scattering and Drell-Yan production of lepton pairs. The baseline analysis is performed with a Monte Carlo replica method resumming large logarithms at N3LL accuracy. The resulting description of the data is very good ($\\chi^2/N_{\\rm dat} = 1.06$). For semi-inclusive deep-inelastic scattering, predictions for multiplicities are normalized by factors that cure the discrepancy with data introduced by higher-order perturbative corrections.","url_abs":"https://arxiv.org/abs/2206.07598v2","url_pdf":"https://arxiv.org/pdf/2206.07598v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"unpolarized-transverse-momentum-distributions","repo_url":"https://github.com/MapCollaboration/NangaParbat","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"unpolarized-transverse-momentum-distributions","repo_url":"https://github.com/vbertone/NangaParbat","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}