Ponente
Descripción
For the HL-LHC era, the Phase-2 CMS upgrade includes a full replacement of the trigger and data acquisition system. The upgraded readout electronics will support a maximum Level-1 (L1) accept rate of 750 kHz with a latency of 12.5 µs. The muon trigger is implemented as a multi-layered system that reconstructs and measures muon momenta by correlating signals from different muon chambers within dedicated muon track finders. This reconstruction relies on advanced pattern recognition algorithms executed on FPGA processors.
In the barrel muon system, stub building proceeds in two stages: the first constructs stubs using local information from individual muon stations, while the second combines, refines, and correlates information across multiple chambers before passing it to the track finders.
This work presents a muon shower tagging algorithm designed to efficiently detect and reconstruct muon showers, with potential application in the barrel muon system of the CMS experiment. The algorithm clusters hits to identify showers and then matches those clusters to muon stubs in neighboring stations. Such a method is particularly valuable for recovering efficiency lost when high-momentum muons radiate while traversing the detector.
Abstract
For the HL-LHC era, the Phase-2 CMS upgrade includes a full replacement of the trigger and data acquisition system. The upgraded readout electronics will support a maximum Level-1 (L1) accept rate of 750 kHz with a latency of 12.5 µs. The muon trigger is implemented as a multi-layered system that reconstructs and measures muon momenta by correlating signals from different muon chambers within dedicated muon track finders. This reconstruction relies on advanced pattern recognition algorithms executed on FPGA processors.
In the barrel muon system, stub building proceeds in two stages: the first constructs stubs using local information from individual muon stations, while the second combines, refines, and correlates information across multiple chambers before passing it to the track finders.
This work presents a muon shower tagging algorithm designed to efficiently detect and reconstruct muon showers, with potential application in the barrel muon system of the CMS experiment. The algorithm clusters hits to identify showers and then matches those clusters to muon stubs in neighboring stations. Such a method is particularly valuable for recovering efficiency lost when high-momentum muons radiate while traversing the detector.
