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Machine learning predictor for ‘measurement-to-track’ association for the ATLAS inner detector trigger
The track finding algorithm adopted for the LHC Run-2 data taking period is based on combinatorial track following, where the seed number scales non-linearly with the number of hits. The corresponding CPU time increase, close to cubical, creates huge and ever-increasing demand for computing power. T...
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| Lenguaje: | eng |
| Publicado: |
2022
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| Acceso en línea: | https://dx.doi.org/10.1088/1742-6596/2438/1/012101 http://cds.cern.ch/record/2801227 |