Speaker
Description
We present a numerical investigation of partonic energy loss in the Quark-Gluon Plasma (QGP) using a data-driven Bayesian inference framework. This study explores the energy, transverse momentum, and angular characteristics of the energy loss distribution associated with medium-induced multiple gluon emissions by hard partons traversing the QGP. The inference process employs the Markov Chain Monte Carlo method, implemented via the Metropolis-Hastings algorithm. Independent radiation mechanisms are modeled under the effects of boost-invariant longitudinal expansion, incorporating gamma and log-normal energy distribution functions to examine transverse momentum broadening and angular profiles of partonic cascades, providing insights into the interplay between medium properties and partonic evolution. Our results demonstrate con-
sistent nuclear modification factor RAA values with the LHC data across both energy distributions.
