Separation of Quark Flavors using DVCS Data
High Energy Physics - Phenomenology
2020-07-02 v1 High Energy Physics - Experiment
Abstract
Using the available data on deeply virtual Compton scattering (DVCS) off protons and utilizing neural networks enhanced by the dispersion relation constraint, we determine six out of eight leading Compton form factors in the valence quark kinematic region. Furthermore, adding recent data on DVCS off neutrons, we separate contributions of up and down quarks to the dominant form factor, thus paving the way towards a three-dimensional picture of the nucleon.
Cite
@article{arxiv.2007.00029,
title = {Separation of Quark Flavors using DVCS Data},
author = {Marija Cuic and Kresimir Kumericki and Andreas Schafer},
journal= {arXiv preprint arXiv:2007.00029},
year = {2020}
}
Comments
6 pages, 5 figures