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.
Highlights
Introduction.—Understanding the structure of hadrons in terms of their partonic constituents is one of the preeminent tasks of modern hadron physics
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
Experiments like deep inelastic scattering (DIS) led to a reasonably accurate knowledge of parton distribution functions (PDFs), which describe the structure of the proton in terms of the fraction of its large longitudinal momentum carried by a quark
Summary
Introduction.—Understanding the structure of hadrons in terms of their partonic constituents (quarks and gluons) is one of the preeminent tasks of modern hadron physics. 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.
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