277 citations · 952 across the 23 of their papers we have counts for
5 papers · 1 filter
More Synergies from Beauty, Top, and Drell-Yan Measurements in SMEFT
Cornelius Grunwald, Gudrun Hiller, Kevin Kröninger +1
We perform a global analysis of Beauty, Top, and Drell-Yan measurements in the framework of the Standard Model effective theory (SMEFT). We work within the minimal flavor viola…
A Bayesian tune of the Herwig Monte Carlo event generator
Salvatore La Cagnina, Kevin Kröninger, Stefan Kluth +1
The optimisation (tuning) of the free parameters of Monte Carlo event generators by comparing their predictions with data is important since the simulations are used to calculate e…
Machine Learning and LHC Event Generation
Anja Butter, Tilman Plehn, Steffen Schumann +48
First-principle simulations are at the heart of the high-energy physics research program. They link the vast data output of multi-purpose detectors with fundamental theory predicti…
Reformulation of a likelihood approach to fake-lepton estimation in the framework of Bayesian inference
Johannes Erdmann, Cornelius Grunwald, Kevin Kröninger +3
Prompt isolated leptons are essential in many analyses in high-energy particle physics but are subject to fake-lepton background, i.e. objects that mimic the lepton signature. The…
(MC)**3 -- a Multi-Channel Markov Chain Monte Carlo algorithm for phase-space sampling
Kevin Kroeninger, Steffen Schumann, Benjamin Willenberg
A new Monte Carlo algorithm for phase-space sampling, named (MC)**3, is presented. It is based on Markov Chain Monte Carlo techniques but at the same time incorporates prior knowle…