Toward a deeper understanding of how experiments constrain the underlying physics of heavy-ion collisions

High-energy heavy ion collisions at RHIC and LHC are complex dynamical phenomena. To understand them one typically relies upon complex numerical simulations that are compared to an array of experimental measurements. This paper presents a novel extension of the standard Bayesian Markov chain Monte Carlo method that helps establish a relationship of the model parameters to the measurements, as well as determine the uncertainties in the inferred parameters. The approach may have applications in other areas of physics and astrophysics.