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Identification of highly boosted 𝒁 → 𝒆 + 𝒆 − decays with the ATLAS detector using deep neural networks
This note describes the development and evaluation of a new algorithm dedicated to identify highly boosted $Z\rightarrow e^+e^-$ decays. Jets, clustered via the anti-$k_{t}$ algorithm using a radius parameter of $0.4$ are used to reconstruct the $Z\rightarrow e^+e^-$ candidates, while a deep neural...
| Autor principal: | |
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| Lenguaje: | eng |
| Publicado: |
2022
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| Materias: | |
| Acceso en línea: | http://cds.cern.ch/record/2845238 |
| _version_ | 1780976540284092416 |
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| author | The ATLAS collaboration |
| author_facet | The ATLAS collaboration |
| author_sort | The ATLAS collaboration |
| collection | CERN |
| description | This note describes the development and evaluation of a new algorithm dedicated to identify highly boosted $Z\rightarrow e^+e^-$ decays. Jets, clustered via the anti-$k_{t}$ algorithm using a radius parameter of $0.4$ are used to reconstruct the $Z\rightarrow e^+e^-$ candidates, while a deep neural network trained on the jet properties is used to reduce the backgrounds. In addition, the mass and transverse momentum resolutions are studied for these objects as well as the background rejection rates. |
| id | cern-2845238 |
| institution | Organización Europea para la Investigación Nuclear |
| language | eng |
| publishDate | 2022 |
| record_format | invenio |
| spelling | cern-28452382022-12-23T23:36:06Zhttp://cds.cern.ch/record/2845238engThe ATLAS collaborationIdentification of highly boosted 𝒁 → 𝒆 + 𝒆 − decays with the ATLAS detector using deep neural networksParticle Physics - ExperimentThis note describes the development and evaluation of a new algorithm dedicated to identify highly boosted $Z\rightarrow e^+e^-$ decays. Jets, clustered via the anti-$k_{t}$ algorithm using a radius parameter of $0.4$ are used to reconstruct the $Z\rightarrow e^+e^-$ candidates, while a deep neural network trained on the jet properties is used to reduce the backgrounds. In addition, the mass and transverse momentum resolutions are studied for these objects as well as the background rejection rates.ATL-PHYS-PUB-2022-056oai:cds.cern.ch:28452382022-12-23 |
| spellingShingle | Particle Physics - Experiment The ATLAS collaboration Identification of highly boosted 𝒁 → 𝒆 + 𝒆 − decays with the ATLAS detector using deep neural networks |
| title | Identification of highly boosted 𝒁 → 𝒆 + 𝒆 − decays with the ATLAS detector using deep neural networks |
| title_full | Identification of highly boosted 𝒁 → 𝒆 + 𝒆 − decays with the ATLAS detector using deep neural networks |
| title_fullStr | Identification of highly boosted 𝒁 → 𝒆 + 𝒆 − decays with the ATLAS detector using deep neural networks |
| title_full_unstemmed | Identification of highly boosted 𝒁 → 𝒆 + 𝒆 − decays with the ATLAS detector using deep neural networks |
| title_short | Identification of highly boosted 𝒁 → 𝒆 + 𝒆 − decays with the ATLAS detector using deep neural networks |
| title_sort | identification of highly boosted 𝒁 → 𝒆 + 𝒆 − decays with the atlas detector using deep neural networks |
| topic | Particle Physics - Experiment |
| url | http://cds.cern.ch/record/2845238 |
| work_keys_str_mv | AT theatlascollaboration identificationofhighlyboostedzeedecayswiththeatlasdetectorusingdeepneuralnetworks |