Speaker
Emanuele Roberto Nocera
(Universita degli Studi di Milano and INFN, Milano)
Description
We present a preliminary determination of a set of polarized parton
distributions of the nucleon, at next-to-leading order, from a global set of
deep-inelastic scattering data. The determination is based on the NNPDF
methodology: a Monte Carlo sampling with neural networks used as unbiased
interpolants. This method, which has already been applied to a determination of
unpolarized parton distributions, is designed to provide a faithful and
statistically sound representation of the uncertainty on parton distributions.
We discuss the general NNPDF procedure to parton fitting, focusing on the
algorithm used to determine the optimal fit. We also present a preliminary set
of polarized PDFs, compared to other parton extractions recently obtained by
other collaborations. In particular, we show that "traditional" fits tend to
underestimate the PDF uncertainty, particularly for the gluon, which is
basically unconstrained by inclusive DIS data.
Primary author
Emanuele Roberto Nocera
(Universita degli Studi di Milano and INFN, Milano)
