Enhancing Bayesian parameter estimation by adapting to multiple energy scales in RHIC and LHC heavy-ion collisions
Abstract
Improved constraints on current model parameters in a heavy-ion collision model are established using the latest measurements from three distinct collision systems. Various observables are utilized from Au--Au collisions at ~GeV and Pb--Pb collisions at ~TeV and ~TeV. Additionally, the calibration of centrality is now carried out separately for all parametrizations. The inclusion of an Au--Au collision system with an order of magnitude lower beam energy, along with separate centrality calibration, suggests a preference for smaller values of nucleon width, minimum volume per nucleon, and free-streaming time. The results with the acquired \textit{maximum a posteriori} parameters show improved agreement with the data for the second-order flow coefficient, identified particle yields, and mean transverse momenta. This work contributes to a more comprehensive understanding of heavy-ion collision dynamics and sets the stage for future improvements in theoretical modeling and experimental measurements.
Keywords
Cite
@article{arxiv.2411.01932,
title = {Enhancing Bayesian parameter estimation by adapting to multiple energy scales in RHIC and LHC heavy-ion collisions},
author = {Maxim Virta and Jasper Parkkila and Dong Jo Kim},
journal= {arXiv preprint arXiv:2411.01932},
year = {2024}
}
Comments
17 pages, 19 figures