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Jet Flavour Classification Using DeepJet
Jet flavour classification is of paramount importance for a broad range of applications in modern-day high-energy-physics experiments, particularly at the LHC. In this paper we propose a novel architecture for this task that exploits modern deep learning techniques. This new model, called DeepJet, o...
| Autores principales: | , , , , |
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| Lenguaje: | eng |
| Publicado: |
2020
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1088/1748-0221/15/12/P12012 http://cds.cern.ch/record/2730134 |
| _version_ | 1780966472944713728 |
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| author | Bols, Emil Kieseler, Jan Verzetti, Mauro Stoye, Markus Stakia, Anna |
| author_facet | Bols, Emil Kieseler, Jan Verzetti, Mauro Stoye, Markus Stakia, Anna |
| author_sort | Bols, Emil |
| collection | CERN |
| description | Jet flavour classification is of paramount importance for a broad range of applications in modern-day high-energy-physics experiments, particularly at the LHC. In this paper we propose a novel architecture for this task that exploits modern deep learning techniques. This new model, called DeepJet, overcomes the limitations in input size that affected previous approaches. As a result, the heavy flavour classification performance improves, and the model is extended to also perform quark-gluon tagging. |
| id | cern-2730134 |
| institution | Organización Europea para la Investigación Nuclear |
| language | eng |
| publishDate | 2020 |
| record_format | invenio |
| spelling | cern-27301342023-09-27T08:04:49Zdoi:10.1088/1748-0221/15/12/P12012http://cds.cern.ch/record/2730134engBols, EmilKieseler, JanVerzetti, MauroStoye, MarkusStakia, AnnaJet Flavour Classification Using DeepJetstat.MLMathematical Physics and Mathematicsphysics.data-anOther Fields of Physicshep-exParticle Physics - ExperimentJet flavour classification is of paramount importance for a broad range of applications in modern-day high-energy-physics experiments, particularly at the LHC. In this paper we propose a novel architecture for this task that exploits modern deep learning techniques. This new model, called DeepJet, overcomes the limitations in input size that affected previous approaches. As a result, the heavy flavour classification performance improves, and the model is extended to also perform quark-gluon tagging.arXiv:2008.10519oai:cds.cern.ch:27301342020-08-24 |
| spellingShingle | stat.ML Mathematical Physics and Mathematics physics.data-an Other Fields of Physics hep-ex Particle Physics - Experiment Bols, Emil Kieseler, Jan Verzetti, Mauro Stoye, Markus Stakia, Anna Jet Flavour Classification Using DeepJet |
| title | Jet Flavour Classification Using DeepJet |
| title_full | Jet Flavour Classification Using DeepJet |
| title_fullStr | Jet Flavour Classification Using DeepJet |
| title_full_unstemmed | Jet Flavour Classification Using DeepJet |
| title_short | Jet Flavour Classification Using DeepJet |
| title_sort | jet flavour classification using deepjet |
| topic | stat.ML Mathematical Physics and Mathematics physics.data-an Other Fields of Physics hep-ex Particle Physics - Experiment |
| url | https://dx.doi.org/10.1088/1748-0221/15/12/P12012 http://cds.cern.ch/record/2730134 |
| work_keys_str_mv | AT bolsemil jetflavourclassificationusingdeepjet AT kieselerjan jetflavourclassificationusingdeepjet AT verzettimauro jetflavourclassificationusingdeepjet AT stoyemarkus jetflavourclassificationusingdeepjet AT stakiaanna jetflavourclassificationusingdeepjet |