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Generalized parton distributions from nucleon form factor data
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We present a simple empirical parameterization of the x- and t-dependence of generalized parton distributions at zero skewness, using forward parton distributions as input. A fit to experimental data for the Dirac, Pauli and axial form factors of the nucleon allows us to discuss quantitatively the interplay between longitudinal and transverse partonic degrees of freedom in the nucleon ("nucleon tomography"). In particular we obtain the transverse distribution of valence quarks at given momentum fraction x. We calculate various moments of the distributions, including the form factors that appear in the handbag approximation to wide-angle Compton scattering. This allows us to estimate the minimal momentum transfer required for reliable predictions in that approach to be around |t|~3 GeV^2. We also evaluate the valence contributions to the energy-momentum form factors entering Ji's sum rule.
Forward citations
Cited by 3 Pith papers
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Extraction of Pion Unpolarized Quark and Gluon Generalized Parton Distributions using Deep Neural-Networks
A DNN fit to pion form-factor and lattice data produces quark and gluon GPDs; quark results agree with lattice, gluon results rely on a fitted normalization factor.
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A Unified Neural-Network Framework for Nucleon Imaging from Numerical Simulations of QCD
One neural network simultaneously fits LaMET and short-distance-expansion lattice data to reconstruct light-cone PDFs and zero-skewness GPDs of the nucleon.
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Mechanical properties of the nucleon from the generalized parton distributions
Using a double-distribution GPD model constrained by elastic-scattering data, the paper fits DQ(0) = -3.37 ± 0.17 from Compton form factors and derives proton pressure, shear, and radii.
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