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The MadNIS Reloaded

High Energy Physics - Phenomenology 2024-07-31 v3 High Energy Physics - Experiment Computational Physics
Authors: Theo Heimel , Nathan Huetsch , Fabio Maltoni , Olivier Mattelaer , Tilman Plehn , Ramon Winterhalder
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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.

Cite

@article{arxiv.2311.01548,
  title  = {The MadNIS Reloaded},
  author = {Theo Heimel and Nathan Huetsch and Fabio Maltoni and Olivier Mattelaer and Tilman Plehn and Ramon Winterhalder},
  journal= {arXiv preprint arXiv:2311.01548},
  year   = {2024}
}

Comments

15 pages, 6 figures, 2 tables; v3: updates incl. referee requests

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