Exploring jets: substructure and flavour tagging in CMS and ATLAS
Fuente:
arXiv
Guardado en:
| Autor principal: | |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866916444861628416 |
|---|---|
| author | Malara, Andrea |
| author_facet | Malara, Andrea |
| contents | The identification and characterization of jets are crucial tasks for effectively probing fundamental particle interactions. The ATLAS and CMS experiments have developed cutting-edge techniques to improve jet identification and calibration, employing innovative approaches including advanced neural network architectures, attention-based mechanisms, and adversarial training. These proceedings provide a comprehensive review of the state-of-the-art methods employed by both collaborations, highlighting their similarities, unique strengths, and limitations through a comparative analysis. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_14330 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Exploring jets: substructure and flavour tagging in CMS and ATLAS Malara, Andrea High Energy Physics - Experiment The identification and characterization of jets are crucial tasks for effectively probing fundamental particle interactions. The ATLAS and CMS experiments have developed cutting-edge techniques to improve jet identification and calibration, employing innovative approaches including advanced neural network architectures, attention-based mechanisms, and adversarial training. These proceedings provide a comprehensive review of the state-of-the-art methods employed by both collaborations, highlighting their similarities, unique strengths, and limitations through a comparative analysis. |
| title | Exploring jets: substructure and flavour tagging in CMS and ATLAS |
| topic | High Energy Physics - Experiment |
| url | https://arxiv.org/abs/2410.14330 |