High dimensional parameter tuning for event generators
Monte Carlo Event Generators are important tools for the understanding of physics at particle colliders like the LHC. In order to best predict a wide variety of observables, the optimization of parameters in the Event Generators based on precision data is crucial. However, the simultaneous optimization of many parameters is computationally challenging. We present an algorithm that allows to tune M
