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Hashing and metric learning for charged particle tracking
We propose a novel approach to charged particle tracking at high intensity particle colliders based on Approximate Nearest Neighbors search. With hundreds of thousands of measurements per collision to be reconstructed e.g. at the High Luminosity Large Hadron Collider, the currently employed combinat...
| Autores principales: | , , , |
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| Lenguaje: | eng |
| Publicado: |
2021
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| Materias: | |
| Acceso en línea: | http://cds.cern.ch/record/2750641 |