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arXiv · 1902.10548

Monte Carlo sampling variant of the DSSV14 set of helicity parton densities

Daniel de Florian·Gonzalo Agustin Lucero·Rodolfo Sassot·Marco Stratmann·Werner Vogelsang
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Abstract

We implement a Monte Carlo sampling strategy to extract helicity parton densities and their uncertainties from a reference set of longitudinally polarized scattering data, chosen to be that used in the DSSV14 global analysis. Instead of adopting the simplest possible functional forms for the helicity parton distributions and imposing certain restrictions on their parameter space in order to constrain them, we employ redundant, flexible parametrizations and fit them to a large number of Monte Carlo replicas of the existing data. The optimum fit and its uncertainty estimates are then assumed to be given by the statistical average of the obtained ensemble of replicas of helicity parton densities and their corresponding variance, respectively. We compare our results to those obtained by the traditional fitting approach and to the uncertainty estimates derived with the robust Lagrange multiplier method, finding good agreement. As a first application of our new set of replicas, we discuss the impact of the recent STAR dijet data in further constraining the elusive gluon helicity density through the reweighting method.

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Daniel de Florian, Gonzalo Agustin Lucero, Rodolfo Sassot, Marco Stratmann, Werner Vogelsang. 2019-02-27. Monte Carlo sampling variant of the DSSV14 set of helicity parton densities. https://doi.org/10.1103/physrevd.100.114027

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