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Machine learning and parallelism in the reconstruction of LHCb and its upgrade
After a highly successful first data taking period at the LHC, the LHCb experiment developed a new trigger strategy with a real-time reconstruction, alignment and calibration for Run II. This strategy relies on offline-like track reconstruction in the high level trigger, making a separate offline ev...
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| Lenguaje: | eng |
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2017
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| Acceso en línea: | https://dx.doi.org/10.1088/1742-6596/898/4/042042 http://cds.cern.ch/record/2260684 |
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