Bayesian inference of the fluctuating proton shape in DIS and hadronic collisions

Abstract

We determine the likelihood distribution for the model parameters describing the event-by-event fluctuating proton geometry at small $x$ by performing a Bayesian analysis within the Color Glass Condensate framework. The exclusive $\mathrm{J}/\ddot{I}ˆ$ production data from HERA is found to constrain the model parameters well, and we demonstrate that complementary constraints can be obtained from simulations of Pb+Pb collisions at the LHC.

6 pages, contribution to the proceedings of the Quark Matter 2022 conference