Shedding light on shadow generalized parton distributions

The feasibility of extracting generalized parton distributions (GPDs) from deeply virtual Compton scattering (DVCS) data has recently been questioned because the existence an infinite set so-called ``shadow GPDs'' (SGPDs). These SGPDs depend on process and manifest as multiple solutions (at a fixed scale ${Q}^{2}$) to inverse problem that needs be solved infer GPDs DVCS data. therefore pose significant challenge for With this motivation we study extent which QCD evolution can provide constraints SGPDs. This is possible known classes begin contribute observables after evolution, then constrained input ${Q}_{0}^{2}$) by finite ${Q}^{2}$ range. impact could have determining total angular momentum, pressure sheer force distributions, tomography also discussed. We find given empirical over wide range skewness ($\ensuremath{\xi}$) scales, constrains studied at low $x$ $\ensuremath{\xi}$. If finding generalizes all SGPDs---and not able any with qualitatively different behavior---then potentially makes extraction limited