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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...
Autores principales: | , , , , , |
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Lenguaje: | eng |
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2017
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1088/1742-6596/898/9/092046 http://cds.cern.ch/record/2296673 |
_version_ | 1780956909910622208 |
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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. |
id | oai-inspirehep.net-1638632 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2017 |
record_format | invenio |
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 |
work_keys_str_mv | AT bell automatiseddataqualitymonitoringofthelhcbvertexlocator AT crocombeach automatiseddataqualitymonitoringofthelhcbvertexlocator AT gersabeckm automatiseddataqualitymonitoringofthelhcbvertexlocator AT pearcea automatiseddataqualitymonitoringofthelhcbvertexlocator AT majewskim automatiseddataqualitymonitoringofthelhcbvertexlocator AT szumlakt automatiseddataqualitymonitoringofthelhcbvertexlocator |