Studying Deeply Virtual Compton Scattering with Neural Networks

2011/10/17 by Krešimir Kumerički, Kumericki, Kresimir, A.H. Mueller +3
Physics and Astronomy · #Data Analysis #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #High Energy Physics - Phenomenology (hep-ph) #Neutrino Physics Research #Particle Detector Development and Performance #Particle physics theoretical and experimental studies #Statistics and Probability (physics.data-an)

paper · pdf · doi:10.48550/arxiv.1110.3798

openalex publication_date 2011/10/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Neural networks are utilized to fit Compton form factor H to HERMES data on deeply virtual Compton scattering off unpolarized protons. We used this result to predict the beam charge-spin assymetry for muon scattering off proton at the kinematics of the COMPASS II experiment.

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