7 citations · 15 across the 6 of their papers we have counts for
3 papers · 1 filter
Efficient many-jet event generation with Flow Matching
Enrico Bothmann, Timo Janßen, 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…
Accelerating multijet-merged event generation with neural network matrix element surrogates
Tim Herrmann, Timo Janßen, Mathis Schenker +2
The efficient simulation of multijet final states presents a serious computational task for analyses of LHC data and will be even more so at the HL-LHC. We here discuss means to ac…
Sampling NNLO QCD phase space with normalizing flows
Timo Janßen, Rene Poncelet, Steffen Schumann
We showcase the application of neural importance sampling for the evaluation of NNLO QCD scattering cross sections. We consider Normalizing Flows in the form of discrete Coupling L…