Bayesian parameter estimation for relativistic heavy-ion collisions

Understand

I develop and apply a Bayesian method for quantitatively estimating properties of the quark-gluon plasma (QGP), an extremely hot and dense state of fluid-like matter created in relativistic heavy-ion collisions.

• The QGP cannot be directly observed -- it is extraordinarily tiny and ephemeral, about $10^{-14}$ meters in size and living $10^{-23}$ seconds before freezing into discrete particles -- but it can be indirectly characterized by matching the output of a computational collision model to experimental observations.
• The model, which takes the QGP properties of interest as input parameters, is calibrated to fit the experimental data, thereby extracting a posterior probability distribution for the parameters.
• In this dissertation, I construct a specific computational model of heavy-ion collisions and formulate the Bayesian parameter estimation method, which is based on general statistical techniques.