Bayesian inference of the fluctuating proton shape

TL;DR

This paper uses Bayesian inference within the color glass condensate framework to probabilistically constrain models of the fluctuating proton structure based on HERA diffractive scattering data.

Contribution

It introduces a Bayesian approach to determine parameters of the proton's fluctuating shape, integrating experimental data to improve understanding of nucleon structure.

Findings

Most model parameters are well constrained by the data.

The approach sets the stage for comprehensive future analyses including various collision types.

Provides probabilistic constraints on proton shape fluctuations.

Abstract

Using Bayesian inference, we determine probabilistic constraints on the parameters describing the fluctuating structure of protons at high energy. We employ the color glass condensate framework supplemented with a model for the spatial structure of the proton, along with experimental data from the ZEUS and H1 Collaborations on coherent and incoherent diffractive $\mathrm{J}/\psi$ production in e+p collisions at HERA. This data is found to constrain most model parameters well. This work sets the stage for future global analyses, including experimental data from e+p, p+p, and p+A collisions, to constrain the fluctuating structure of nucleons along with properties of the final state.