Ontology type: schema:ScholarlyArticle
2019-12
AUTHORSRoel Aaij, Lucio Anderlini, Sean Benson, Marco Cattaneo, Philippe Charpentier, Marco Clemencic, Antonio Falabella, Fabio Ferrari, Marianna Fontana, Vladimir Vava Gligorov, Donal Hill, Tibaud Humair, Christopher Robert Jones, Oliver Lupton, Sneha Malde, Carla Marin Benito, Rosen Matev, Alex Pearce, Anton Poluektov, Barbara Sciascia, Federico Stagni, Ricardo Vazquez Gomez, Yanxi Zhang
ABSTRACTSince 2015, with the restart of the LHC for its second run of data taking, the LHCb experiment has been empowered with a dedicated computing model to select and analyse calibration samples to measure the performance of the particle identification (PID) detectors and algorithms. The novel technique was developed within the framework of the innovative trigger model of the LHCb experiment, which relies on online event reconstruction for most of the datasets, reserving offline reconstruction to special physics cases. The strategy to select and process the calibration samples, which includes a dedicated data-processing scheme combining online and offline reconstruction, is discussed. The use of the calibration samples to measure the detector PID performance, and the efficiency of PID requirements across a large range of decay channels, is described. Applications of the calibration samples in data-quality monitoring and validation procedures are also detailed. More... »
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http://scigraph.springernature.com/pub.10.1140/epjti/s40485-019-0050-z
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