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Fitting parton distribution data with multiplicative normalization uncertainties

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Original languageEnglish
Article number75
JournalJournal of High Energy Physics
Issue number75
Early online date20 May 2010
Publication statusPublished - 20 May 2010


The extraction of robust parton distribution functions with faithful errors requires a careful treatment of the uncertainties in the experimental results. In particular, the data sets used in current analyses each have a different overall multiplicative normalization uncertainty that needs to be properly accounted for in the fitting procedure. Here we consider the generic problem of performing a global fit to many independent data sets each with a different overall multiplicative normalization uncertainty. We show that the methods in common use to treat multiplicative uncertainties lead to systematic biases. We develop a method which is unbiased, based on a self-consistent iterative procedure. We then apply our generic method to the determination of parton distribution functions with the NNPDF methodology, which uses a Monte Carlo method for uncertainty estimation.

    Research areas

  • QCD Phenomenology

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