Abstract

At large values of x the parton distribution functions (PDFs) of the proton are poorly constrained and there are considerable variations between different global fits. Data at such high x have already been published by the ZEUS Collaboration, but not yet used in PDF extractions. A technique for comparing predictions based on different PDF sets to the observed number of events in the ZEUS data is presented. It is applied to compare predictions from the most commonly used PDFs to published ZEUS data at high Bjorken x. A wide variation is found in the ability of the PDFs to predict the observed results. A scheme for including the ZEUS high-x data in future PDF extractions is discussed.

Highlights

  • Important questions related to the nature of the strong interaction can be addressed by studying the structure of particles composed of quarks and gluons

  • Predictions based on the principal parton distribution functions (PDFs) sets used at the Large Hadron Collider (LHC) are compared to these ZEUS high-x data

  • The evaluation of the probability to have observed these numbers of events according to different PDF sets is discussed in the present paper

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Summary

INTRODUCTION

Important questions related to the nature of the strong interaction can be addressed by studying the structure of particles composed of quarks and gluons. Identifying effects due to new physics beyond the Standard Model at high center-of-mass energies requires precise knowledge of the PDFs at high x, where x is the fractional longitudinal momentum of the struck parton inside the proton. This knowledge is essential for the isolation of some types of new physics. Predictions based on the principal PDF sets used at the LHC are compared to these ZEUS high-x data.

METHOD TO TEST HIGH-x PREDICTIONS
Monte Carlo samples
Determination of matrix elements
Comparison of predictions based on different PDF sets
Comparison of predictions to data
SYSTEMATIC UNCERTAINTIES
Uncertainties on μ and R
Uncertainties on T
PRESCRIPTION FOR PDF EXTRACTIONS INCLUDING THE HIGH-x DATA
CONCLUSIONS

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