Year: 2010
Type: article
Abstract: The recently developed ``data set diagonalization'' method is applied to measure compatibility of the data sets that are used to determine parton distribution functions. 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 $\ensuremath{\Delta}{\ensuremath{\chi}}^{2}\ensuremath{\approx}10$ to estimate the 90% confidence range for parton distribution function uncertainties. No basis is found in the data sets for the larger $\ensuremath{\Delta}{\ensuremath{\chi}}^{2}$ values that are in current use, though it may be necessary to retain those larger values until improved methods can be developed to take account of systematic errors in applying the theory, including the effect of parametrization dependence. The data set diagonalization 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.
Author: Jon Pumplin
Institution: Michigan State University
Language: English
Subfield: Nuclear and High Energy Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2139242639