We present an extraction of unpolarized transverse-momentum-dependent parton distribution and fragmentation functions based on more than two thousand data points from several experiments for two different processes: semi-inclusive deep-inelastic scattering and Drell-Yan production. The baseline analysis is performed using the Monte Carlo replica method and resumming large logarithms at N3LL accuracy. The resulting description of the data is very good (χ2/Ndat = 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.

Unpolarized transverse momentum distributions from a global fit of Drell-Yan and semi-inclusive deep-inelastic scattering data

Alessandro Bacchetta;Valerio Bertone;Chiara Bissolotti;Giuseppe Bozzi;Matteo Cerutti;Fulvio Piacenza;Marco Radici;Andrea Signori
2022-01-01

Abstract

We present an extraction of unpolarized transverse-momentum-dependent parton distribution and fragmentation functions based on more than two thousand data points from several experiments for two different processes: semi-inclusive deep-inelastic scattering and Drell-Yan production. The baseline analysis is performed using the Monte Carlo replica method and resumming large logarithms at N3LL accuracy. The resulting description of the data is very good (χ2/Ndat = 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.
2022
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Esperti anonimi
Inglese
Internazionale
ELETTRONICO
2022
10
https://link.springer.com/article/10.1007/JHEP10(2022)127#citeas
no
8
info:eu-repo/semantics/article
262
Bacchetta, Alessandro; Bertone, Valerio; Bissolotti, Chiara; Bozzi, Giuseppe; Cerutti, Matteo; Piacenza, Fulvio; Radici, Marco; Signori, Andrea...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1471454
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