The neural network approach to parton distribution functions
High Energy Physics - Phenomenology
2007-05-23 v1
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.
Cite
@article{arxiv.hep-ph/0607122,
title = {The neural network approach to parton distribution functions},
author = {Joan Rojo},
journal= {arXiv preprint arXiv:hep-ph/0607122},
year = {2007}
}
Comments
Ph. D. Thesis, 163 pages, version with higher resolution figures available from the following website: http://www.ecm.ub.es/~joanrojo/thesis.pdf