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The MadNIS Reloaded

Authors :
Heimel, Theo
Huetsch, Nathan
Maltoni, Fabio
Mattelaer, Olivier
Plehn, Tilman
Winterhalder, Ramon
Source :
SciPost Phys. 17, 023 (2024)
Publication Year :
2023

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.<br />Comment: 15 pages, 6 figures, 2 tables; v3: updates incl. referee requests

Details

Database :
arXiv
Journal :
SciPost Phys. 17, 023 (2024)
Publication Type :
Report
Accession number :
edsarx.2311.01548
Document Type :
Working Paper
Full Text :
https://doi.org/10.21468/SciPostPhys.17.1.023