AI-assisted modeling and Bayesian inference of unpolarized quark transverse momentum distributions from Drell-Yan data
This paper presents a global Bayesian analysis of unpolarized quark transverse-momentum-dependent parton distribution functions using Drell-Yan data at and accuracy, leveraging AI-driven functional form selection and machine-learning emulators to enable efficient Markov Chain Monte Carlo sampling and quantify uncertainties.