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Probing stop pair production at the LHC with graph neural networks
Abstract Top-squarks (stops) play a crucial role for the naturalness of supersymmetry (SUSY). However, searching for the stops is a tough task at the LHC. To dig the stops out of the huge LHC data, various expert-constructed kinematic variables or cutting-edge analysis techniques have been invented....
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| Main Authors: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
SpringerOpen
2019-08-01
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| Colecção: | Journal of High Energy Physics |
| Assuntos: | |
| Acesso em linha: | http://link.springer.com/article/10.1007/JHEP08(2019)055 |
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