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Processing and Quality Monitoring for the ATLAS Tile Hadronic Calorimeter Data

An overview is presented of Data Processing and Data Quality (DQ) Monitoring for the ATLAS Tile Hadronic Calorimeter. Calibration runs are monitored from a data quality perspective and used as a cross-check for physics runs. Data quality in physics runs is monitored extensively and continuously. Any...

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Detalles Bibliográficos
Autor principal: Burghgrave, Blake
Lenguaje:eng
Publicado: 2017
Materias:
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/898/9/092025
http://cds.cern.ch/record/2244531
Descripción
Sumario:An overview is presented of Data Processing and Data Quality (DQ) Monitoring for the ATLAS Tile Hadronic Calorimeter. Calibration runs are monitored from a data quality perspective and used as a cross-check for physics runs. Data quality in physics runs is monitored extensively and continuously. Any problems are reported and immediately investigated. The DQ efficiency achieved was 99.6% in 2012 and 100% in 2015, after the detector maintenance in 2013-2014. Changes to detector status or calibrations are entered into the conditions database (DB) during a brief calibration loop between the end of a run and the beginning of bulk processing of data collected in it. Bulk processed data are reviewed and certified for the ATLAS Good Run List if no problem is detected. Experts maintain the tools used by DQ shifters and the calibration teams during normal operation, and prepare new conditions for data reprocessing and Monte Carlo (MC) production campaigns. Conditions data are stored in 3 databases: Online DB, Offline DB for data and a special DB for Monte Carlo. Database updates can be performed through a custom-made web interface.