Bayesian inference and jet quenching

TL;DR

This paper reviews how Bayesian inference is applied to study the quark-gluon plasma, emphasizing calibration, jet observables, and lessons for future research in high-energy physics.

Contribution

It introduces Bayesian inference techniques in high momentum transfer probes and discusses recent calibrations and analyses involving jet and soft-hard correlation observables.

Findings

Bayesian methods improve calibration of QGP models

Jet observables significantly impact QGP characterization

Lessons learned guide future high-energy physics analyses

Abstract

These proceedings review the application of Bayesian inference to high momentum transfer probes of the quark--gluon plasma (QGP). Bayesian inference techniques are introduced, highlighting critical components to consider when comparing analyses. Recent calibrations using hadron observables are described, illustrating the importance of the choice of parametrization. Additional recent analyses that characterize the impact of the inclusion of jet observables, as well as soft-hard correlations, are reviewed. Finally, lessons learned from these analyses and important questions for the future are highlighted.