The neural network approach to parton distribution functions
arXiv:hep-ph/0607122
Abstract
We introduce the neural network approach to the parametrization of parton distributions. After a general introduction, we present in detail our approach to parametrize experimental data, based on a combination of Monte Carlo methods and neural networks. We apply this strategy first in three different cases: the proton structure function, hadronic tau decays and B meson decay spectra. Finally we describe the neural network approach applied to the parametrization of parton distribution functions, and present results on the nonsinglet parton distribution.
Ph. D. Thesis, 163 pages, version with higher resolution figures available from the following website: http://www.ecm.ub.es/~joanrojo/thesis.pdf
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