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Automatised data quality monitoring of the LHCb Vertex Locator

The LHCb Vertex Locator (VELO) is a silicon strip semiconductor detector operating at just 8mm distance to the LHC beams. Its 172,000 strips are read at a frequency of 1.1 MHz and processed by off-detector FPGAs followed by a PC cluster that reduces the event rate to about 10 kHz. During the second...

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Autores principales: Bel, L, Crocombe, A Ch, Gersabeck, M, Pearce, A, Majewski, M, Szumlak, T
Lenguaje:eng
Publicado: 2017
Materias:
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/898/9/092046
http://cds.cern.ch/record/2296673
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author Bel, L
Crocombe, A Ch
Gersabeck, M
Pearce, A
Majewski, M
Szumlak, T
author_facet Bel, L
Crocombe, A Ch
Gersabeck, M
Pearce, A
Majewski, M
Szumlak, T
author_sort Bel, L
collection CERN
description The LHCb Vertex Locator (VELO) is a silicon strip semiconductor detector operating at just 8mm distance to the LHC beams. Its 172,000 strips are read at a frequency of 1.1 MHz and processed by off-detector FPGAs followed by a PC cluster that reduces the event rate to about 10 kHz. During the second run of the LHC, which lasts from 2015 until 2018, the detector performance will undergo continued change due to radiation damage effects. This necessitates a detailed monitoring of the data quality to avoid adverse effects on the physics analysis performance. The VELO monitoring infrastructure has been re-designed compared to the first run of the LHC when it was based on manual checks. The new system is based around an automatic analysis framework, which monitors the performance of new data as well as long-term trends and using dedicated algorithms flags issues whenever they arise. The new analysis framework then analyses the plots that are produced by these algorithms. One of its tasks is to perform custom comparisons between the newly processed data and that from reference runs. The most-likely scenario in which this analysis would identify an issue is the parameters of the readout electronics no longer being optimal and requiring retuning. The data of the monitoring plots can be reduced further, e.g. by evaluating averages, and these quantities are input to long-term trending. This is used to detect slow variation of quantities, which are not detectable by the comparison of two nearby runs. Such gradual change is what is expected due to radiation damage effects. It is essential to detect these changes early such that measures can be taken, e.g. adjustments of the operating voltage, to prevent any impact on the quality of high-level quantities and thus on physics analyses. The plots as well as the analysis results and trends are made available through graphical user interfaces (GUIs). These GUIs are dynamically configured by a single configuration that determines the choice and arrangement of plots and trends and ensures a common look and feel.
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language eng
publishDate 2017
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spelling oai-inspirehep.net-16386322021-02-09T10:06:09Zdoi:10.1088/1742-6596/898/9/092046http://cds.cern.ch/record/2296673engBel, LCrocombe, A ChGersabeck, MPearce, AMajewski, MSzumlak, TAutomatised data quality monitoring of the LHCb Vertex LocatorComputing and ComputersThe LHCb Vertex Locator (VELO) is a silicon strip semiconductor detector operating at just 8mm distance to the LHC beams. Its 172,000 strips are read at a frequency of 1.1 MHz and processed by off-detector FPGAs followed by a PC cluster that reduces the event rate to about 10 kHz. During the second run of the LHC, which lasts from 2015 until 2018, the detector performance will undergo continued change due to radiation damage effects. This necessitates a detailed monitoring of the data quality to avoid adverse effects on the physics analysis performance. The VELO monitoring infrastructure has been re-designed compared to the first run of the LHC when it was based on manual checks. The new system is based around an automatic analysis framework, which monitors the performance of new data as well as long-term trends and using dedicated algorithms flags issues whenever they arise. The new analysis framework then analyses the plots that are produced by these algorithms. One of its tasks is to perform custom comparisons between the newly processed data and that from reference runs. The most-likely scenario in which this analysis would identify an issue is the parameters of the readout electronics no longer being optimal and requiring retuning. The data of the monitoring plots can be reduced further, e.g. by evaluating averages, and these quantities are input to long-term trending. This is used to detect slow variation of quantities, which are not detectable by the comparison of two nearby runs. Such gradual change is what is expected due to radiation damage effects. It is essential to detect these changes early such that measures can be taken, e.g. adjustments of the operating voltage, to prevent any impact on the quality of high-level quantities and thus on physics analyses. The plots as well as the analysis results and trends are made available through graphical user interfaces (GUIs). These GUIs are dynamically configured by a single configuration that determines the choice and arrangement of plots and trends and ensures a common look and feel.oai:inspirehep.net:16386322017
spellingShingle Computing and Computers
Bel, L
Crocombe, A Ch
Gersabeck, M
Pearce, A
Majewski, M
Szumlak, T
Automatised data quality monitoring of the LHCb Vertex Locator
title Automatised data quality monitoring of the LHCb Vertex Locator
title_full Automatised data quality monitoring of the LHCb Vertex Locator
title_fullStr Automatised data quality monitoring of the LHCb Vertex Locator
title_full_unstemmed Automatised data quality monitoring of the LHCb Vertex Locator
title_short Automatised data quality monitoring of the LHCb Vertex Locator
title_sort automatised data quality monitoring of the lhcb vertex locator
topic Computing and Computers
url https://dx.doi.org/10.1088/1742-6596/898/9/092046
http://cds.cern.ch/record/2296673
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AT crocombeach automatiseddataqualitymonitoringofthelhcbvertexlocator
AT gersabeckm automatiseddataqualitymonitoringofthelhcbvertexlocator
AT pearcea automatiseddataqualitymonitoringofthelhcbvertexlocator
AT majewskim automatiseddataqualitymonitoringofthelhcbvertexlocator
AT szumlakt automatiseddataqualitymonitoringofthelhcbvertexlocator