Experimental consistency in parton distribution fitting

Abstract

The recently developed "Data Set Diagonalization" method (DSD) is applied to measure compatibility of the data sets that are used to determine parton distribution functions (PDFs). Discrepancies among the experiments are found to be somewhat larger than is predicted by propagating the published experimental errors according to Gaussian statistics. The results support a tolerance criterion of $\Delta {\chi }^2\approx 10$ to estimate the 90% confidence range for PDF uncertainties. No basis is found in the data sets for the much larger $\Delta {\chi }^2$ values that are in current use; though it will be necessary to retain those larger values until improved methods can be developed to take account of systematic errors in applying the theory. The DSD method also measures how much influence each experiment has on the global fit, and identifies experiments that show significant tension with respect to the others. The method is used to explore the contribution from muon scattering experiments, which are found to exhibit the largest discrepancies in the current fit.

30 pages; 7 figures

References in corpus (6)

• Parton distributions for the LHC
• Implications of CTEQ global analysis for collider observables
• Uncertainties on alpha_S in global PDF analyses and implications for predicted hadronic cross sections
• Measurement of the inclusive jet cross section in $p\bar{p}$ collisions at $\sqrt{s}=1.96\mathrm{TeV}$
• Data set diagonalization in a global fit
• Collider Inclusive Jet Data and the Gluon Distribution

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• Structure Functions
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• Charm quark mass dependence in a global QCD analysis
• Mapping the sensitivity of hadronic experiments to nucleon structure
• Charting the coming synergy between lattice QCD and high-energy phenomenology
• Precision determination of alpha_s using an unbiased global NLO parton set
• Parametrization dependence and Delta Chi-squared in parton distribution fitting
• Parton distributions at the dawn of the LHC
• A Stress Test of Global PDF Fits: Closure Testing the MSHT PDFs and a First Direct Comparison to the Neural Net Approach
• Progress in CTEQ/TEA global QCD analysis