58 citations · 69 across the 7 of their papers we have counts for
4 papers · 1 filter
Efficient Event Generation for High-Multiplicity LHC Processes: An End-to-End GPU Workflow with Normalizing Flows
Enrico Bothmann, Joshua Isaacson, Claudius Krause +3
Producing very large unweighted event samples for high-multiplicity processes is limited by expensive matrix-element evaluations and low unweighting efficiencies. We present the fi…
Open LHC Monte Carlo Event Generation
Enrico Bothmann, Jon Butterworth, Shu Chen +16
The LHC physics programme involves a vast amount of Monte Carlo event simulation. This paper reviews current efforts towards sharing the generated events as Open Data. Open Event G…
The Monte Carlo Ecosystem in High-Energy Physics: A Primer
Melissa van Beekveld, Enrico Bothmann, Andy Buckley +3
Monte Carlo event generators are the central interface between theoretical calculations and experimental measurements in collider physics. Over several decades, a comprehensive and…
Monte Carlo Event Generation with Continuous Normalizing Flows
Enrico Bothmann, Timo Janßen, Max Knobbe +2
We apply Continuous Normalizing Flows trained with the Flow Matching method to the problem of phase-space sampling in Monte Carlo event generation for high-energy collider physics.…