Lattice QCD pseudo-distributions at m_π=358 MeV are inverted via multidimensional Gaussian process regression to reconstruct the full kinematic dependence of GPDs H^{u-d} and E^{u-d} while directly extracting double distributions.
Mart´ ınez-Fern´ andez, D
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
citation-role summary
background 2
extension 1
citation-polarity summary
years
2026 5verdicts
UNVERDICTED 5representative citing papers
Derives t/P_z² and m_N²/P_z² kinematic corrections to the short-distance expansion of quasi-GPD matrix elements for lattice QCD applications.
A proposed μCLAS12 upgrade at CLAS12 targets di-muon production to access the complete phase space of nucleon Generalized Parton Distributions via Double Deeply Virtual Compton Scattering.
Computes kinematic twist-3, twist-4 and NLO alpha_s corrections to coherent DVCS on He-4 and extracts the first 3D quark-gluon tomography of the nucleus.
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.
citing papers explorer
-
Reconstructing the full kinematic dependence of GPDs from pseudo-distributions
Lattice QCD pseudo-distributions at m_π=358 MeV are inverted via multidimensional Gaussian process regression to reconstruct the full kinematic dependence of GPDs H^{u-d} and E^{u-d} while directly extracting double distributions.
-
Finite-$t$ and target mass corrections for the short-distance expansion of quasi(pseudo) GPDs
Derives t/P_z² and m_N²/P_z² kinematic corrections to the short-distance expansion of quasi-GPD matrix elements for lattice QCD applications.
-
Electro- and photoproduction of muon pairs with $\mu$CLAS12: Double Deeply Virtual Compton Scattering, Timelike Compton Scattering, and $J/\psi$ production
A proposed μCLAS12 upgrade at CLAS12 targets di-muon production to access the complete phase space of nucleon Generalized Parton Distributions via Double Deeply Virtual Compton Scattering.
-
Coherent deeply virtual Compton scattering on helium-4 beyond leading power
Computes kinematic twist-3, twist-4 and NLO alpha_s corrections to coherent DVCS on He-4 and extracts the first 3D quark-gluon tomography of the nucleus.
-
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.