The neural network approach to parton distribution functions
| dc.creator | Rojo, Joan | |
| dc.date | 2006-07-11 | |
| dc.date.accessioned | 2026-07-07T07:16:43Z | |
| dc.date.available | 2026-07-07T07:16:43Z | |
| dc.description | 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. | |
| dc.description | Ph. D. Thesis, 163 pages, version with higher resolution figures available from the following website: http://www.ecm.ub.es/~joanrojo/thesis.pdf | |
| dc.identifier | https://arxiv.org/abs/hep-ph/0607122 | |
| dc.identifier | http://arxiv.org/abs/hep-ph/0607122 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/113690 | |
| dc.subject | High Energy Physics - Phenomenology | |
| dc.title | The neural network approach to parton distribution functions | |
| dc.type | text |