May 22 – 26, 2023
IJCLab, Orsay (FRANCE)
Europe/Paris timezone

Shedding light on shadow generalized parton distributions

Not scheduled
Auditorium Joliot Curie (IJCLab, Orsay (FRANCE))

Auditorium Joliot Curie

IJCLab, Orsay (FRANCE)

15, Rue G. Clemenceau 91405 Orsay Cedex FRANCE


Eric Moffat (Argonne National Lab)


The feasibility of extracting generalized parton distributions (GPDs) from deeply-virtual Compton scattering (DVCS) data has recently been questioned because of the existence of an infinite set of so-called ``shadow GPDs'' (SGPDs). These SGPDs are process-dependent and manifest as multiple solutions (at a fixed $Q^2$) to the inverse problem that needs to be solved to infer GPDs from DVCS data. SGPDs therefore pose a significant challenge for extracting GPDs from DVCS data. With this motivation we study the extent to which scale evolution can provide constraints on SGPDs. Our key finding is that scale evolution, coupled with data over a wide range of $\xi$ and $Q^2$, can constrain the known classes of SGPDs and make possible the extraction of GPDs from DVCS data over a limited range in the GPD variables.

Primary authors

Adam Freese (University of Washington) Alexey Prokudin (PSU Berks and JLab) Andreas Metz Eric Moffat (Argonne National Lab) Ian Cloet (Argonne National Laboratory) Prof. Leonard Gamberg (Penn State University Berks) Nobuo Sato Thomas Donohoe (Argonne National Lab) Wally Melnitchouk (Jefferson Lab)

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