Recognition: unknown
Taming Deeply Virtual Compton Scattering
classification
✦ hep-ph
hep-exnucl-exnucl-th
keywords
dvcscomptondatadeeplymodelparameterizationscatteringvirtual
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We study recent Deeply Virtual Compton scattering (DVCS) data within a dual parameterization of the Generalized Parton Distributions (GPDs). This parameterization allows to quantify the maximum amount of information, that can be extracted from DVCS data, in a ``quintessence'' function. We present a ``zero step'' model for the latter solely based on the forward quark density, providing a parameter free prediction for the imaginary part of the DVCS amplitude. It is shown that the bulk effect of the $e p \to e p \gamma$ beam helicity asymmetry can be understood within such a model.
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