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Combining lattice QCD and phenomenological inputs on generalised parton distributions at moderate skewness

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arxiv 2306.01647 v1 pith:ISXLDSUT submitted 2023-06-02 hep-ph hep-latnucl-th

classification hep-phhep-latnucl-th
keywords gpdslatticedataextractiondistributionsgeneralisedimpactinputs
verification ladder T0 review T1 audit T2 compute T3 formal

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abstract

We present a systematic study demonstrating the impact of lattice QCD data on the extraction of generalised parton distributions (GPDs). For this purpose, we use a previously developed modelling of GPDs based on machine learning techniques fulfilling the theoretical requirements of polynomiality, a form of positivity constraint and known reduction limits. A special care is given to estimate the uncertainty stemming from the ill-posed character of the connection between GPDs and the experimental processes usually considered to constrain them, like deeply virtual Compton scattering (DVCS). Mock lattice QCD data inputs are included in a Bayesian framework to the prior model which is fitted to reproduce the most experimentally accessible information of a phenomenological model by Goloskov and Kroll. We highlight the impact of the precision, correlation and kinematic coverage of lattice data on GPD extraction at moderate $\xi$ which has only been brushed in the literature so far, paving the way for a joint extraction of GPDs.

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Forward citations

Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A Unified Neural-Network Framework for Nucleon Imaging from Numerical Simulations of QCD

    hep-lat 2025-09 conditional novelty 6.0 of 10

    One neural network simultaneously fits LaMET and short-distance-expansion lattice data to reconstruct light-cone PDFs and zero-skewness GPDs of the nucleon.

  2. Assessing the impact of the electron ion collider in China on Deeply Virtual Compton Scattering

    hep-ph 2025-12 conditional novelty 5.0 of 10

    Projected EicC DVCS asymmetry data would substantially reduce uncertainties on all leading-order Compton form factors, most strongly in the sea-quark region.

  3. Mechanical properties of the nucleon from the generalized parton distributions

    hep-ph 2025-01 conditional novelty 5.0 of 10

    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.

  4. Mapping spatial distributions within pseudoscalar mesons

    hep-ph 2024-12 conditional novelty 5.0 of 10

    A new analytic parametrization of meson valence-quark GPDs yields spatial charge and mass distributions and radius ratios for pions, kaons and heavy-light mesons.

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