Outputs (6)

UFO 2.0: the ‘Universal Feynman Output’ format (2023)
Journal Article
Darmé, L., Degrande, C., Duhr, C., Fuks, B., Goodsell, M., Heinrich, G., …Zaro, M. (2023). UFO 2.0: the ‘Universal Feynman Output’ format. The European Physical Journal C, 83(7), Article 631. https://doi.org/10.1140/epjc/s10052-023-11780-9

We present an update of the Universal FeynRules Output model format, commonly known as the UFO format, that is used by several automated matrix-element generators and high-energy physics software. We detail different features that have been proposed... Read More about UFO 2.0: the ‘Universal Feynman Output’ format.

Machine learning and LHC event generation (2023)
Journal Article
Butter, A., Plehn, T., Schumann, S., Badger, S., Caron, S., Cranmer, K., …Zupan, J. (2023). Machine learning and LHC event generation. SciPost Physics, 14(4), Article 079. https://doi.org/10.21468/scipostphys.14.4.079

First-principle simulations are at the heart of the high-energy physics research program. They link the vast data output of multi-purpose detectors with fundamental theory predictions and interpretation. This review illustrates a wide range of applic... Read More about Machine learning and LHC event generation.

On the maximal use of Monte Carlo samples: re-weighting events at NLO accuracy (2016)
Journal Article
Mattelaer, O. (2016). On the maximal use of Monte Carlo samples: re-weighting events at NLO accuracy. The European Physical Journal C, 76(12), Article 674. https://doi.org/10.1140/epjc/s10052-016-4533-7

Accurate Monte Carlo simulations for high-energy events at CERN’s Large Hadron Collider, are very expensive, both from the computing and storage points of view. We describe a method that allows to consistently re-use parton-level samples accurate up... Read More about On the maximal use of Monte Carlo samples: re-weighting events at NLO accuracy.

Fully automated precision predictions for heavy neutrino production mechanisms at hadron colliders (2016)
Journal Article
Degrande, C., Mattelaer, O., Ruiz, R., & Turner, J. (2016). Fully automated precision predictions for heavy neutrino production mechanisms at hadron colliders. Physical Review D, 94(5), Article 053002. https://doi.org/10.1103/physrevd.94.053002

Motivated by TeV-scale neutrino mass models, we propose a systematic treatment of heavy neutrino (N) production at hadron colliders. Our simple and efficient modeling of the vector boson fusion (VBF) Wγ → Nl and Nl þ nj signal definitions resolve col... Read More about Fully automated precision predictions for heavy neutrino production mechanisms at hadron colliders.

Automated event generation for loop-induced processes (2015)
Journal Article
Hirschi, V., & Mattelaer, O. (2015). Automated event generation for loop-induced processes. Journal of High Energy Physics, 2015(10), Article 146. https://doi.org/10.1007/jhep10%282015%29146

We present the first fully automated implementation of cross-section computation and event generation for loop-induced processes. This work is integrated in the MadGraph5_aMC@NLO framework. We describe the optimisations implemented at the level of th... Read More about Automated event generation for loop-induced processes.

Dark-matter production through loop-induced processes at the LHC: the s-channel mediator case (2015)
Journal Article
Mattelaer, O., & Vryonidou, E. (2015). Dark-matter production through loop-induced processes at the LHC: the s-channel mediator case. The European Physical Journal C, 75(9), Article 436. https://doi.org/10.1140/epjc/s10052-015-3665-5

We show how studies relevant for mono-X searches at the LHC in simplified models featuring a dark-matter candidate and an s-channel mediator can be performed within the MadGraph5_aMC@NLO framework. We focus on gluon-initiated loop-induced processes,... Read More about Dark-matter production through loop-induced processes at the LHC: the s-channel mediator case.