arXiv · hep-ph/0509067
Neural network approach to parton distributions fitting
Abstract
We will show an application of neural networks to extract information on the structure of hadrons. A Monte Carlo over experimental data is performed to correctly reproduce data errors and correlations. A neural network is then trained on each Monte Carlo replica via a genetic algorithm. Results on the proton and deuteron structure functions, and on the nonsinglet parton distribution will be shown.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Andrea Piccione, Joan Rojo. 2005-10-18. Neural network approach to parton distributions fitting. https://doi.org/10.1016/j.nima.2005.11.206
Cite the original work for its findings. Save a collection to share your selection of sources.