Bayesian reweighting of TMD densities
Protons and neutrons, i.e. the nucleons, are still subject of very intensive reaserch. Since the pioneering measure from the EMC Collaboration, we are aware that a one dimensional description fails in describing their properties (e.g.~their spin) in terms of its constituents, quarks and gluons, and that a more general approach is needed.
Transverse momentum dependent distributions (TMDs) offer a richer description of protons and neutrons inner structure (in momentum space) in three dimensions. Among them, the so-called quark Sivers function, that describes the correlation between the nucleon transverse polarization and the quark intrinsic transverse momentum, is one of the most studied TMDs. Nonetheless, the available amount of data is still scarce for having satisfying constraints on it. Hence, a global approach combining different suitable data sets is needed to shed light on the Sivers distribution. To this extent, in this talk we will see how modern techniques as the Bayesian reweighting can be employed to extend and enrich the current knowledge on such quark TMD density.
Based on: Phys.Lett.B 815 (2021) 136135 (arXiv: 2101.03955 [hep-ph])
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Prof. Umberto D'Alesio - umberto.dalesio@ca.infn.it
Ph.D. Michela Lai - michela.lai@ca.infn.it
Dr Luca Maxia - luca.maxia@ca.infn.it
Dr Mauro Oi - mauro.oi@ca.infn.it