Speaker
Description
Determining QCD properties via experimental observations is an
essential part of the heavy-ion program, and a crucial aspect of any
such study is an accurate assessment of uncertainty. This uncertainty
comes not only from experiments but also from theoretical modeling.
Bayesian inference methods provide an ideal framework for a systematic
treatment of these sources of uncertainty and an accurate
determination of QGP properties. We present a Bayesian Model
Averaging framework to account for different sources of theoretical
uncertainty [1] and show results obtained from comparison to RHIC and
LHC measurements. We further show how including additional deuteron
observables affect the posterior constraints. Finally, we discuss the
choice of observables to use in an analysis, especially the benefits
and risks of including observables with strong constraining power but
also significant sensitivity to theoretical uncertainty.
[1] D. Everett et al. [JETSCAPE], Phenomenological constraints on
the transport properties of QCD matter with data-driven model
averaging, Phys. Rev. Lett. 126, 242301 (2021)
