Measuring jet quenching with a Bayesian inference analysis of hadron and jet data by JETSCAPE
Abstract
The JETSCAPE Collaboration reports the first multi-messenger study of the QGP jet transport parameter using Bayesian inference, incorporating all available hadron and jet inclusive yield and jet substructure data from RHIC and the LHC. The theoretical model utilizes virtuality-dependent in-medium partonic energy loss coupled to a detailed dynamical model of QGP evolution. Tension is observed when constraining for different kinematic cuts of the inclusive hadron data. The addition of substructure data is shown to improve the constraint on , without inducing tension with the constraint due to inclusive observables. These studies provide new insight into the mechanisms of jet interactions in matter, and point to next steps in the field for comprehensive understanding of jet quenching as a probe of the QGP.
Cite
@article{arxiv.2401.04201,
title = {Measuring jet quenching with a Bayesian inference analysis of hadron and jet data by JETSCAPE},
author = {R. Ehlers and A. Angerami and R. Arora and S. A. Bass and S. Cao and Y. Chen and L. Du and H. Elfner and W. Fan and R. J. Fries and C. Gale and Y. He and U. Heinz and B. V. Jacak and P. M. Jacobs and S. Jeon and Y. Ji and L. Kasper and M. Kordell and A. Kumar and R. Kunnawalkam-Elayavalli and J. Latessa and S. Lee and Y. -J. Lee and D. Liyanage and M. Luzum and S. Mak and A. Majumder and A. Mankolli and C. Martin and H. Mehryar and T. Mengel and J. Mulligan and C. Nattrass and J. -F. Paquet and C. Parker and J. H. Putschke and H. Roch and G. Roland and B. Schenke and L. Schwiebert and A. Sengupta and C. Shen and C. Sirimanna and D. Soeder and R. A. Soltz and I. Soudi and M. Strickland and Y. Tachibana and J. Velkovska and G. Vujanovic and X. -N. Wang and W. Zhao},
journal= {arXiv preprint arXiv:2401.04201},
year = {2024}
}
Comments
4 pages, 2 figures. Proceedings of Quark Matter 2023 - XXXth International Conference on Ultra-relativistic Nucleus-Nucleus Collisions, Houston, TX, 3-9 September 2023