Speakers
Description
The JETSCAPE Collaboration reports a new determination of jet transport coefficients in the
Quark-Gluon Plasma, using both reconstructed jet and hadron data measured at RHIC and the
LHC. The JETSCAPE framework incorporates detailed modeling of the dynamical evolution of
the QGP; a multi-stage theoretical approach to in-medium jet evolution and medium response;
and Bayesian inference for quantitative comparison of model calculations and data. The multi-
stage framework incorporates multiple models to cover a broad range in scale of the in-medium
parton shower evolution, with dynamical choice of model that depends on the current virtuality
or energy of the parton.
We will discuss the physics of the multi-stage modeling, and then present a new Bayesian
analysis incorporating it. This analysis extends the recently published JETSCAPE determination
of the jet transport parameter $\hat{q}$ that was based solely on inclusive hadron suppression
data [1], by incorporating reconstructed jet measurements of quenching. We explore the
functional dependence of jet transport coefficients on QGP temperature and jet energy and
virtuality, and report the consistency and tensions found for current jet quenching modeling with
hadron and reconstructed jet data over a wide range in kinematics and $\sqrt{s}$. This analysis
represents the next step in the program of comprehensive analysis of jet quenching
phenomenology and its constraint of properties of the QGP.
[1] JETSCAPE Collaboration (S. Cao et al.), Phys. Rev. C104 (2021) 1, 024905
