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Parametrization of Quark and Gluon Generalized Parton Distributions in a Dynamical Framework
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We present a parametrization of the chiral even generalized parton distributions, $H$, $E$, $\widetilde{H}$, $\widetilde{E}$, for the quark, antiquark and gluon, in the perturbative QCD-parton framework. Parametric analytic forms are given as a function of two equivalent sets of variables $x,\xi,t$ (symmetric frame) and $X,\zeta,t$ (asymmetric frame), at an initial scale, $Q_o^2$. In the $X>\zeta$ region a convenient and flexible form is obtained as the product of a Regge term $\propto X^{-\alpha + \alpha' t}$, describing the low $X$ behavior, times a spectator model-based functional form depending on various mass parameters; the behavior at $X<\zeta$, is determined using the generalized parton distributions symmetry and polynomiality properties. The parameters are constrained using data on the flavor separated nucleon electromagnetic elastic form factors, the axial and pseudoscalar nucleon form factors, and the parton distribution functions from both the deep inelastic unpolarized and polarized nucleon structure functions. For the gluon distributions we use, in particular, constraints provided by recent lattice QCD moments calculations. The parametrization's kinematical range of validity is: $0.0001 \leq X \leq 0.85$, $0.01 \leq \zeta \leq 0.85$, $0 \leq -t \leq 1$ GeV$^2$, $2 \leq Q^2 \leq 100$ GeV$^2$. With the simultaneous description of the quark, anti-quark and gluon sectors, this parametrization represents a first tool enabling a global QCD analysis of deeply virtual exclusive experiments.
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Cited by 1 Pith paper
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Neural Network Representation of Generalized Parton Distributions (NNGPD)
A neural network trained solely on integral observables from a known GPD model recovers the main features of the underlying distributions in a closure test.
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