Speaker
Dr
Alexander Singovski
(University of Minnesota)
Description
The High Luminosity LHC (HL-LHC) will provide unprecedented instantaneous and integrated luminosities. The lead tungstate (PbWO4) crystals forming the barrel part of the Electromagnetic Calorimeter (ECAL) of the Compact Muon Solenoid (CMS) will still perform well, even after the expected integrated luminosity of 3000fb-1 at the end of HL-LHC. The avalanche photodiodes (APDs) used to detect the scintillation light will also continue to be operational, although there will be some increase in electronics noise due to radiation-induced APD dark currents.
During the third long shutdown of the LHC (LS3), the barrel ECAL will undergo extensive changes in order to prepare for the next decade of operation under the more challenging conditions of the HL-LHC. The barrel operating temperature will be reduced, to mitigate the increasing APD-induced noise. The most significant change will be the replacement of a majority of the on-detector and off-detector readout. This will remove existing constraints on trigger rate and latency, and will provide additional functionality to exploit the higher luminosity delivered by the HL-LHC.
We start with the comparison of the legacy detector design goals and the real detector performance. Then we review the design and R&D studies for the barrel calorimeter upgrade and present results from test beam studies of the first prototype readout electronics. We present test beam results on hadron irradiated PbWO4 crystals up to fluences expected at HL-LHC and detail the status of the new readout and trigger electronics R&D. The mitigation of the larger number of concurrent interactions per bunch crossing (pileup) expected at HL-LHC may be substantially improved by means of precision time tagging of calorimeter clusters, by associating them to primary vertices via 4D triangulation. We present recent test beam results on the precision timing potential of the CMS lead tungstate calorimeter and discuss how the readout electronics may be adapted to exploit this performance in CMS.
Primary author
Dr
Alexander Singovski
(University of Minnesota)
