Reduce, Reuse, Reinterpret: an end-to-end pipeline for recycling particle physics results

Fuente: arXiv
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Auteurs principaux: Stark, Giordon, Ots, Camila Aristimuno, Hance, Mike
Format: Preprint
Publié: 2023
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author Stark, Giordon
Ots, Camila Aristimuno
Hance, Mike
author_facet Stark, Giordon
Ots, Camila Aristimuno
Hance, Mike
contents Searches for new physics at the Large Hadron Collider have constrained many models of physics beyond the Standard Model. Many searches also provide resources that allow them to be reinterpreted in the context of other models. We describe a reinterpretation pipeline that examines previously untested models of new physics using supplementary information from ATLAS Supersymmetry (SUSY) searches in a way that provides accurate constraints even for models that differ meaningfully from the benchmark models of the original analysis. The public analysis information, such as public analysis routines and serialized probability models, is combined with common event generation and simulation toolkits MadGraph, Pythia8, and Delphes into workflows steered by TOML configuration files, and bundled into the mapyde python package. The use of mapyde is demonstrated by constraining previously untested SUSY models with compressed sleptons and electroweakinos using ATLAS results.
format Preprint
id arxiv_https___arxiv_org_abs_2306_11055
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Reduce, Reuse, Reinterpret: an end-to-end pipeline for recycling particle physics results
Stark, Giordon
Ots, Camila Aristimuno
Hance, Mike
High Energy Physics - Experiment
High Energy Physics - Phenomenology
Searches for new physics at the Large Hadron Collider have constrained many models of physics beyond the Standard Model. Many searches also provide resources that allow them to be reinterpreted in the context of other models. We describe a reinterpretation pipeline that examines previously untested models of new physics using supplementary information from ATLAS Supersymmetry (SUSY) searches in a way that provides accurate constraints even for models that differ meaningfully from the benchmark models of the original analysis. The public analysis information, such as public analysis routines and serialized probability models, is combined with common event generation and simulation toolkits MadGraph, Pythia8, and Delphes into workflows steered by TOML configuration files, and bundled into the mapyde python package. The use of mapyde is demonstrated by constraining previously untested SUSY models with compressed sleptons and electroweakinos using ATLAS results.
title Reduce, Reuse, Reinterpret: an end-to-end pipeline for recycling particle physics results
topic High Energy Physics - Experiment
High Energy Physics - Phenomenology
url https://arxiv.org/abs/2306.11055