In pursuit of precise and fast theory predictions for the LHC, we present an implementation of the MadNIS method in the MadGraph event generator. A series of improvements in MadNIS further enhance its efficiency and speed. We validate this implementation for realistic partonic processes and find significant gains from using modern machine learning in event generators.
Heimel, T., Huetsch, N., Maltoni, F., Mattelaer, O., Plehn, T., Winterhalder, R. (2024). The MadNIS reloaded. SCIPOST PHYSICS, 17(1), 1-23 [10.21468/scipostphys.17.1.023].
The MadNIS reloaded
Maltoni, Fabio;
2024
Abstract
In pursuit of precise and fast theory predictions for the LHC, we present an implementation of the MadNIS method in the MadGraph event generator. A series of improvements in MadNIS further enhance its efficiency and speed. We validate this implementation for realistic partonic processes and find significant gains from using modern machine learning in event generators.File in questo prodotto:
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