Abstract
The LHCb RICH system provides hadron identification over a wide momentum range (2–100GeV/c). This detector system is key to LHCb's precision flavour physics programme, which has unique sensitivity to physics beyond the standard model. This paper reports on the performance of the LHCb RICH in Run II, following significant changes in the detector and operating conditions. The changes include the refurbishment of significant number of photon detectors, assembled using new vacuum technologies, and the removal of the aerogel radiator. The start of Run II of the LHC saw the beam energy increase to 6.5TeV per beam and a new trigger strategy for LHCb with full online detector calibration. The RICH information has also been made available for all trigger streams in the High Level Trigger for the first time.
Highlights
After the start of Run II in 2015 at the LHC [1] the LHCb experiment [2] has been able to study the properties and decays of mesons containing b and c quarks produced at a pp centre-of-mass energy of 13 TeV
With the new trigger strategy the Ring Imaging Cherenkov (RICH) particle identification (ID) information is used in HLT2 for all trigger streams
The LHCb RICH system consists of two RICH detectors: RICH 1 located upstream of the LHCb magnet and close to the interaction point and RICH 2 located downstream of the tracking system and before the calorimeter
Summary
After the start of Run II in 2015 at the LHC [1] the LHCb experiment [2] has been able to study the properties and decays of mesons containing b and c quarks produced at a pp centre-of-mass energy of 13 TeV. HLT1 is a fast track-based trigger that runs online with an output rate of ∼100 kHz. The data are buffered on local disks, and read by the HLT2, after the sub-detector systems have been calibrated and aligned (see Fig. 1). The data are buffered on local disks, and read by the HLT2, after the sub-detector systems have been calibrated and aligned (see Fig. 1) This results in almost offline-quality datasets straight from the LHCb trigger. For this strategy to work it is required that the same algorithms are used online and offline. This increases the need for speed optimisation in the event reconstruction. Some physics analyses take advantage of this and can be done without the extra step of offline reprocessing of the events
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