• Open Access

Separation of Quark Flavors Using Deeply Virtual Compton Scattering Data

Marija Čuić, Krešimir Kumerički, and Andreas Schäfer
Phys. Rev. Lett. 125, 232005 – Published 2 December 2020

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.

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  • Received 8 July 2020
  • Revised 14 October 2020
  • Accepted 10 November 2020

DOI:https://doi.org/10.1103/PhysRevLett.125.232005

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Funded by SCOAP3.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Particles & FieldsNuclear Physics

Authors & Affiliations

Marija Čuić1, Krešimir Kumerički1,2, and Andreas Schäfer2

  • 1Department of Physics, Faculty of Science, University of Zagreb, 10000 Zagreb, Croatia
  • 2Institüt für Theoretische Physik, Universität Regensburg, D-93040 Regensburg, Germany

Article Text

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Issue

Vol. 125, Iss. 23 — 4 December 2020

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