2005/05/06 by Rojo, Joan, Andrea Piccione, Piccione, Andrea
Computer Science · Physics and Astronomy · #Computational Physics and Python Applications #FOS: Physical sciences #High Energy Physics - Phenomenology (hep-ph) #Particle physics theoretical and experimental studies #Quantum Chromodynamics and Particle Interactions
paper · pdf · doi:10.48550/arxiv.hep-ph/0505044
openalex publication_date 2005/05/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We introduce the neural network approach to global fits of parton distribution functions. First we review previous work on unbiased parametrizations of deep-inelastic structure functions with faithful estimation of their uncertainties, and then we summarize the current status of neural network parton distribution fits.