A neural network framework informed by lattice QCD uses all-order dispersion relations to significantly constrain both real and imaginary parts of Compton Form Factors extracted from DVCS proton data.
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Light-front quark model calculations with two Gaussian wave functions yield transverse mechanical distributions for pseudoscalar charmonium and bottomonium, showing a nodal pressure and positive force.
A hadronic approach based on dispersion relations and meson dominance achieves a successful description of lattice QCD data for gravitational form factors of pions and nucleons.
citing papers explorer
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Constraining DVCS Compton Form Factors Using Lattice QCD informed Neural Network
A neural network framework informed by lattice QCD uses all-order dispersion relations to significantly constrain both real and imaginary parts of Compton Form Factors extracted from DVCS proton data.
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Mechanical distribution of the pseudoscalar charmonium and bottomonium on the light-front
Light-front quark model calculations with two Gaussian wave functions yield transverse mechanical distributions for pseudoscalar charmonium and bottomonium, showing a nodal pressure and positive force.
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Particle seismology: mechanical and gravitational properties from parton-hadron duality
A hadronic approach based on dispersion relations and meson dominance achieves a successful description of lattice QCD data for gravitational form factors of pions and nucleons.