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Article Dans Une Revue European Physical Journal C: Particles and Fields Année : 2024

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

Résumé

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.

Dates et versions

hal-04128055 , version 1 (14-06-2023)

Identifiants

Citer

Michael Joseph Riberdy, Hervé Dutrieux, Cédric Mezrag, Paweł Sznajder. Combining lattice QCD and phenomenological inputs on generalised parton distributions at moderate skewness. European Physical Journal C: Particles and Fields, 2024, 84 (2), pp.201. ⟨10.1140/epjc/s10052-024-12513-2⟩. ⟨hal-04128055⟩
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