8 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…
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…
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…
Monte Carlo Event Generation with Continuous Normalizing Flows
Enrico Bothmann, Timo JanÃen, 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.…
Efficient many-jet event generation with Flow Matching
Enrico Bothmann, Timo JanÃen, Max Knobbe +2
We apply for the first time the Flow Matching method to the problem of phase-space sampling for event generation in high-energy collider physics. By training the model to remap the…
Event Generators for High-Energy Physics Experiments
J. M. Campbell, M. Diefenthaler, T. J. Hobbs +221
We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of acti…