Posterior distributions for physical parameters describing relativistic heavy-ion collisions, such as the viscosity of the quark-gluon plasma, are extracted through a comparison of hydrodynamicbased transport models to experimental results from 100A GeV + 100A GeV Au+Au collisions at the Relativistic Heavy Ion Collider (RHIC). By simultaneously varying six parameters and by evaluating several classes of observables, we are able to explore the complex intertwined dependencies of observables on model parameters. The methods proved a full multi-dimensional posterior distribution for the model output, including a range of acceptable values for each parameter, and reveal correlations between them. The breadth of observables and the number of parameters considered here go beyond previous studies in this field. The statistical tools, which are based upon Gaussian Process emulators, are tested in detail and should be extendable to larger data sets and a higher number of parameters.

In this paper we conduct a systematic study of the granularity of the initial state of hot and dense QCD matter produced in ultra-relativistic heavy-ion collisions and its influence on bulk observables like particle yields, m T spectra and elliptic flow. For our investigation we use a hybrid transport model, based on (3+1)d hydrodynamics and a microscopic Boltzmann transport approach. The initial conditions are generated by a non-equilibrium hadronic transport approach and the size of their fluctuations can be adjusted by defining a Gaussian smoothing parameter σ. The dependence of the hydrodynamic evolution on the choices of σ and t start is explored by means of a Gaussian emulator. To generate particle yields and elliptic flow that are compatible with experimental data the initial state parameters are constrained to be σ = 1 fm and t start = 0.5 fm. In addition, the influence of changes in the equation of state is studied and the results of our event-by-event calculations are compared to a calculation with averaged initial conditions. We conclude that even though the initial state parameters can be constrained by yields and elliptic flow, the granularity needs to be constrained by other correlation and fluctuation observables.

We systematically compare an event-by-event heavy-ion collision model to data from the 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. The method is universal and easily extensible to other data and collision models.

We use the semi-analytic model ChemTreeN, coupled to cosmological N-body simulations, to explore how different galaxy formation histories can affect observational properties of Milky Way-like galaxies' stellar haloes and their satellite populations. Gaussian processes are used to generate model emulators that allow one to statistically estimate a desired set of model outputs at any location of a p-dimensional input parameter space. This enables one to explore the full input parameter space orders of magnitude faster than could be done otherwise. Using mock observational data sets generated by ChemTreeN itself, we show that it is possible to successfully recover the input parameter vectors used to generate the mock observables if the merger history of the host halo is known. However, our results indicate that for a given observational data set the determination of "best fit" parameters is highly susceptible to the particular merger history of the host. Very different halo merger histories can reproduce the same observational dataset, if the "best fit" parameters are allowed to vary from history to history. Thus, attempts to characterize the formation history of the Milky Way using these kind of techniques must be performed statistically, analyzing large samples of high resolution N-body simulations.

We determine the limit of the lowest achievable photoemitted electron temperature, and therefore the maximum achievable electron brightness, from unstructured photoemitting materials producing dense relativistic or nonrelativistic photoelectron beams. The limit is given by electron heating that occurs just after emission into vacuum, and is due to poorly screened Coulomb interactions equivalent to disorder induced heating seen in ultracold neutral plasmas. We first show that traditional analytic methods of Coulomb collisions fail for the calculation of this strongly coupled heating. Instead, we employ an N -body tree algorithm to compute the universal scaling of the disorder induced heating in fully contained bunches, and show it to agree well with a simple model utilizing the tabulated correlated energy of one component plasmas. We also present simulations for beams undergoing Coulomb explosion at the photoemitter, and demonstrate that both the temperature growth and subsequent cooling must be characterized by correlated effects, as well as correlation-frozen dynamics. In either case, the induced temperature is found to be of several meV