Multi-observable analysis of jet quenching using Bayesian inference with JETSCAPE

Abstract

The Jetscape Collaboration presents a new determination of the jet transport parameter $\hat{q}$ in the Quark-Gluon Plasma (QGP) using Bayesian Inference. This study expands on previous work by incorporating a comprehensive data set from inclusive hadron and jet yield suppression measurements at RHIC and the LHC. Utilizing Active Learning and other machine-learning approaches for computational efficiency, the analysis efficiently explores the parameter space and studies systematic dependencies across various kinematic and centrality ranges. The results highlight tensions in the extracted $\hat{q}$ values across different data sets, providing deeper insights into the physics of jet transport in the QGP.