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CMS ECAL DAQ monitoring system

The Large Hadron Collider (LHC) at CERN in Geneva, Switzerland, has just completed the Run 2 era, colliding protons at a center-of-mass energy of 13 TeV at high instantaneous luminosity. The Compact Muon Solenoid (CMS) is a general-purpose particle detector experiment at the LHC. The CMS electromagn...

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Detalles Bibliográficos
Autor principal: Cucciati, Giacomo
Lenguaje:eng
Publicado: 2018
Materias:
Acceso en línea:https://dx.doi.org/10.1051/epjconf/201921401045
http://cds.cern.ch/record/2650362
Descripción
Sumario:The Large Hadron Collider (LHC) at CERN in Geneva, Switzerland, has just completed the Run 2 era, colliding protons at a center-of-mass energy of 13 TeV at high instantaneous luminosity. The Compact Muon Solenoid (CMS) is a general-purpose particle detector experiment at the LHC. The CMS electromagnetic calorimeter (ECAL) has been designed to achieve excellent energy and position resolution for electrons and photons. A multi-machine distributed software configures the on-detector and off-detector electronic boards composing the ECAL data acquisition (DAQ) system and follows the life cycle of the acquisition process. Since the beginning of Run 2 in 2015, many improvements to the ECAL DAQ have been implemented to reduce and mitigate occasional errors in the front-end electronics and not only. Efforts at the software level have been made to introduce automatic recovery in case of errors. Automatic actions has made even more important the online monitoring of the DAQ boards status. For this purpose a new web application, EcalView, has been developed. It runs on a light Node.js JavaScript server framework. It is composed of several routines that cyclically collect the status of the electronics. It display the information when web requests are launched by client side graphical interfaces. For each board, detailed information can be loaded and presented in specific pages if requested by the expert. Server side routines store information regarding electronics errors in a SQLite database in order to perform offline analysis about the long term status of the boards.