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Usage of machine learning for the separation of electroweak and strong $Z_{\gamma}$ production at the LHC experiments
Separation of electroweak component from strong component of associated Zγ production on hadron colliders is a very challenging task due to identical final states of such processes. The only difference is the origin of two leading jets in these two processes. Rectangular cuts on jet kinematic variab...
| Autores principales: | , |
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| Lenguaje: | eng |
| Publicado: |
2017
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1088/1742-6596/934/1/012028 http://cds.cern.ch/record/2310258 |