Categorisation of dark photon jets using machine learning techniques
dc.catalogador | gjm | |
dc.contributor.advisor | Garay Walls, Francisca | |
dc.contributor.advisor | Olivares Pino, Sebastián Andrés | |
dc.contributor.author | Haacke Concha, Michael | |
dc.contributor.other | Pontificia Universidad Católica de Chile. Instituto de Física | |
dc.date.accessioned | 2024-01-04T15:13:20Z | |
dc.date.available | 2024-01-04T15:13:20Z | |
dc.date.issued | 2023 | |
dc.date.updated | 2024-01-02T00:55:19Z | |
dc.description | Tesis (Master in theoretical physics)--Pontificia Universidad Católica de Chile, 2023. | |
dc.description.abstract | This thesis presents a search for Dark Photons decaying into two Hidden Lightest Stable Particles (HLSP) and fermions or light hadrons using ATLAS experiment data from the LHC at a center-of-mass energy of 13 TeV, with an integrated luminosity of 139.0 fb^-1. This study looks to discriminate the dark photon signal produced by a vector-boson-fusion Higgs from all backgrounds using various machine learning techniques. Among the methods tested, XGBoost emerged as the most effective, achieving a MC simulated significance of 5.88 standard deviations. This marked a substantial 22.5% improvement compared to the standard VBF analysis. | |
dc.fechaingreso.objetodigital | 2024-01-04 | |
dc.format.extent | xi, 50 páginas | |
dc.fuente.origen | Autoarchivo | |
dc.identifier.doi | 10.7764/tesisUC/FIS/75619 | |
dc.identifier.uri | http://doi.org/10.7764/tesisUC/FIS/75619 | |
dc.identifier.uri | https://repositorio.uc.cl/handle/11534/75619 | |
dc.information.autoruc | Instituto de física; Garay Walls, Francisca; S/I; 165844 | |
dc.information.autoruc | Instituto de física; Olivares Pino, Sebastián Andrés; 0000-0003-4616-6973; 125165 | |
dc.information.autoruc | Instituto de física; Haacke Concha, Michael; S/I; 245292 | |
dc.language.iso | en | |
dc.nota.acceso | Contenido completo | |
dc.rights | acceso abierto | |
dc.subject.ddc | 510 | |
dc.subject.dewey | Matemática física y química | es_ES |
dc.title | Categorisation of dark photon jets using machine learning techniques | |
dc.type | tesis de maestría | |
sipa.codpersvinculados | 165844 | |
sipa.codpersvinculados | 125165 | |
sipa.codpersvinculados | 245292 |