Litcius/Paper detail

Bayesian inference of the fluctuating proton shape

Heikki Mäntysaari, Björn Schenke, Chun Shen, W. Zhao

2022Physics Letters B49 citationsDOIOpen Access PDF

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 J/ψ 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.

Topics & Concepts

PhysicsBayesian inferenceBayesian probabilityInferenceProtonStatistical physicsParticle physicsNuclear physicsArtificial intelligenceComputer scienceHigh-Energy Particle Collisions ResearchQuantum Chromodynamics and Particle InteractionsParticle physics theoretical and experimental studies