A determination of the charm content of the proton: The NNPDF Collaboration

Eur Phys J C Part Fields. 2016;76(11):647. doi: 10.1140/epjc/s10052-016-4469-y. Epub 2016 Nov 24.

Abstract

We present an unbiased determination of the charm content of the proton, in which the charm parton distribution function (PDF) is parametrized on the same footing as the light quarks and the gluon in a global PDF analysis. This determination relies on the NLO calculation of deep-inelastic structure functions in the FONLL scheme, generalized to account for massive charm-initiated contributions. When the EMC charm structure function dataset is included, it is well described by the fit, and PDF uncertainties in the fitted charm PDF are significantly reduced. We then find that the fitted charm PDF vanishes within uncertainties at a scale [Formula: see text] GeV for all [Formula: see text], independent of the value of [Formula: see text] used in the coefficient functions. We also find some evidence that the charm PDF at large [Formula: see text] and low scales does not vanish, but rather has an "intrinsic" component, very weakly scale dependent and almost independent of the value of [Formula: see text], carrying less than [Formula: see text] of the total momentum of the proton. The uncertainties in all other PDFs are only slightly increased by the inclusion of fitted charm, while the dependence of these PDFs on [Formula: see text] is reduced. The increased stability with respect to [Formula: see text] persists at high scales and is the main implication of our results for LHC phenomenology. Our results show that if the EMC data are correct, then the usual approach in which charm is perturbatively generated leads to biased results for the charm PDF, though at small x this bias could be reabsorbed if the uncertainty due to the charm mass and missing higher orders were included. We show that LHC data for processes, such as high [Formula: see text] and large rapidity charm pair production and [Formula: see text] production, have the potential to confirm or disprove the implications of the EMC data.