Fitting parton distribution data with multiplicative normalization uncertainties
(2010) The Journal of High Energy Physics — n° 5 (2010)
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- Abstract
- 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.
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Ball, R. D., Del Debbio, L., Forte, S., Guffanti, A., Latorre, J. I., Rojo, J., & Ubiali, M. (2010). Fitting parton distribution data with multiplicative normalization uncertainties. The Journal of High Energy Physics, 5. https://doi.org/10.1007/JHEP05(2010)075 (Original work published 2010)