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Cross Sections for Deeply Virtual Exclusive Experiments from Jefferson Lab at 6 GeV to an EIC

ORAL

Abstract

Imaging the 3D partonic structure of the nucleon is a fundamental goal of nuclear experimental programs ranging from Jefferson Lab (JLAB) at 6 GeV to the Electron Ion Collider (EIC). Deeply Virtual Compton Scattering (DVCS) was first proposed as a way to probe the spatial distribution of partons in nuclei [1] by Fourier transform of the exchanged momentum transfer between the initial and final. The extraction of observables from deeply virtual exclusive reactions in a clear and concise formalism is a necessity. We recently presented a completely covariant description of the DVCS process that can be extended to any kinematics, either fixed target or collider [2,3]. In our helicity formalism, we extract observables such that the dependence on Q2 is clear [4]. Utilizing current data from JLAB at both 6 and 12 GeV as well as pseudo-data of an EIC generated by state of the art machine learning techniques, we show predictions of what such an experimental program will do for our understanding of the physical properties of nuclei.  This work was funded by DOE grant DE-SC0016286 and SURA grant C2020-FEMT-002-04 and C2021-FEMT-006-05. 

[1] Xiangdong Ji. Deeply virtual Compton scattering. Phys. Rev. D 55, 1997.

[2] B. Kriesten, S. Liuti, L. Calero-Diaz, D. Keller, A. Meyer, G. R. Goldstein, and J. Osvaldo gonzalez-Hernandez, Phys. Rev. D 101, 054021 (2020).

[3] B. Kriesten and S. Liuti, (2020), arXiv:2004.08890 [hep-ph] submitted to PRD.

[4] B. Kriesten and S. Liuti, (2020), arXiv:2011.04484 [hep-ph] submitted to PLB.

Publication: B. Kriesten, S. Liuti, L. Calero-Diaz, D. Keller, A. Meyer, G. R. Goldstein, and J. Osvaldo gonzalez-Hernandez, Phys. Rev. D 101, 054021 (2020).<br>B. Kriesten and S. Liuti, (2020), arXiv:2004.08890 [hep-ph] submitted to PRD.<br>B. Kriesten and S. Liuti, (2020), arXiv:2011.04484 [hep-ph] submitted to PLB.

Presenters

  • Brandon Kriesten

    University of Virginia

Authors

  • Brandon Kriesten

    University of Virginia

  • Simonetta Liuti

    University of Virginia