Quantifying properties of hot and dense QCD matter through systematic model-to-data comparison

We systematically compare an event-by-event heavy-ion collision model to data from the CERN Large Hadron Collider. Using a general Bayesian method, we probe multiple model parameters including fundamental quark-gluon plasma properties such as the specific shear viscosity η/s, calibrate the model to optimally reproduce experimental data, and extract quantitative constraints for all parameters simultaneously. Furthermore, the method is universal and easily extensible to other data and collision models.