Speaker
Description
We present NNPDFpol2.0, a new set of polarised parton distribution functions (PDFs) of the proton based on legacy measurements of structure functions in inclusive polarised deep-inelastic scattering (DIS), and of W-boson, single-inclusive, and di-jet production asymmetries in polarised proton-proton collisions. The determination is accurate to next-to-next-to-leading order in the strong coupling, and specifically includes heavy quark mass corrections in the analysis of DIS data. Uncertainties due to missing higher-order corrections are systematically incorporated by means of a covariance matrix determined by scale variations. NNPDFpol2.0 is based on a machine learning methodology, that makes use of Monte Carlo sampling for the representation of uncertainties into PDFs, of a neural network for the parametrisation of PDFs, of stochastic gradient descent for the optimisation of PDF parameters, and of hyperoptimisation for the selection of the best fitting model. We study the impact on PDFs of the data, of higher-order corrections, and of theoretical constraints. We assess the phenomenological implications of NNPDFpol2.0, specifically concerning the determination of the proton spin fraction carried by quarks and gluons, and the description of single-hadron production in polarised DIS and proton-proton collisions.
