EPJ Web of Conferences · 2021 · 26 citations · 15 references
Artificial IntelligenceEvent GeneratorEngineeringMachine LearningModel TuningIntelligent SystemsHyperparameter EstimationData ScienceUncertainty QuantificationComplex Event ProcessingEvent Generator TuningManagementSystems EngineeringModeling And SimulationEvent GeneratorsEvent ProcessingPredictive AnalyticsComputer EngineeringComputer ScienceSurrogate ModelModel OptimizationParameter TuningEvent-driven ProgrammingProcess ControlSimulation Optimization
APPRENTICE is a tool developed for event generator tuning. It contains a range of conceptual improvements and extensions over the tuning tool Professor. Its core functionality remains the construction of a multivariate analytic surrogate model to computationally expensive Monte-Carlo event generator predictions. The surrogate model is used for numerical optimization in chi-square minimization and likelihood evaluation. Apprentice also introduces algorithms to automate the selection of observable weights to minimize the effect of mis-modeling in the event generators. We illustrate our improvements for the task of MC-generator tuning and limit setting.
15