Dr Jack Araz jack.araz@durham.ac.uk
Academic Visitor
Recasting LHC searches for long-lived particles with MadAnalysis 5
Araz, Jack Y.; Fuks, Benjamin; Goodsell, Mark D.; Utsch, Manuel
Authors
Benjamin Fuks
Mark D. Goodsell
Manuel Utsch
Abstract
We present an extension of the simplified fast detector simulator of MADANALYSIS 5 – the SFS framework – with methods making it suitable for the treatment of long-lived particles of any kind. This allows users to make use of intuitive PYTHON commands and straightforward C++ methods to introduce detector effects relevant for long-lived particles, and to implement selection cuts and plots related to their properties. In particular, the impact of the magnetic field inside a typical high-energy physics detector on the trajectories of any charged object can now be easily simulated. As an illustration of the capabilities of this new development, we implement three existing LHC analyses dedicated to long-lived objects, namely a CMS run 2 search for displaced leptons in the eμ channel (CMS-EXO-16-022), the full run 2 CMS search for disappearing track signatures (CMS-EXO-19-010), and the partial run 2 ATLAS search for displaced vertices featuring a pair of oppositely charged leptons (ATLAS-SUSY-2017-04). We document the careful validation of all MADANALYSIS 5 SFS implementations of these analyses, which are publicly available as entries in the MADANALYSIS 5 Public Analysis Database and its associated dataverse.
Citation
Araz, J. Y., Fuks, B., Goodsell, M. D., & Utsch, M. (2022). Recasting LHC searches for long-lived particles with MadAnalysis 5. The European Physical Journal C, 82(7), Article 597 (2022). https://doi.org/10.1140/epjc/s10052-022-10511-w
Journal Article Type | Article |
---|---|
Acceptance Date | Jun 11, 2022 |
Online Publication Date | Jul 7, 2022 |
Publication Date | 2022 |
Deposit Date | Aug 2, 2022 |
Publicly Available Date | Aug 2, 2022 |
Journal | The European Physical Journal C |
Print ISSN | 1434-6044 |
Publisher | SpringerOpen |
Peer Reviewed | Peer Reviewed |
Volume | 82 |
Issue | 7 |
Article Number | 597 (2022) |
DOI | https://doi.org/10.1140/epjc/s10052-022-10511-w |
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Advance online version This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
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