Self-Orgazing Maps Parametrization of Parton Distribution Functions
High Energy Physics - Phenomenology
2010-11-19 v1
Abstract
We describe a new method to extract parton distribution functions both in the unpolarized and the polarized case, based on a type of neural networks, the Self-Organizing Maps. Initial quantitative results of our Next to Leading Order analysis are presented for the unpolarized case.
Cite
@article{arxiv.1008.2137,
title = {Self-Orgazing Maps Parametrization of Parton Distribution Functions},
author = {Daniel Z. Perry and Katherine Holcomb and Simonetta Liuti},
journal= {arXiv preprint arXiv:1008.2137},
year = {2010}
}
Comments
5 pages, 1 figure, to appear in the proceedings of "XVIII International Workshop on Deep-Inelastic Scattering and Related Subjects April 19 -23, 2010 Convitto della Calza, Firenze, Italy"