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Fast neural-net based fake track rejection in the LHCb reconstruction
A neural-network based algorithm to identify fake tracks in the LHCb pattern recognition is presented. This algorithm, called ghost probability, retains more than 99 % of well reconstructed tracks while reducing the number of fake tracks by 60 %. It is fast enough to fit into the CPU time budget of...
| Autores principales: | , , , |
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| Lenguaje: | eng |
| Publicado: |
2017
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| Materias: | |
| Acceso en línea: | http://cds.cern.ch/record/2255039 |