Operation and performance of the ALICE Muon IDentifier RPCs during LHC Run 3

Not scheduled
20m
Talk HEP performance

Speaker

Luca Quaglia (Universita e INFN Torino (IT))

Description

ALICE (A Large Ion Collider Experiment) is a multi-purpose detector installed at the CERN Large Hadron Collider (LHC). Its main goal is the characterization of the quark-gluon plasma (QGP) in ultra-relativistic heavy-ion collisions. The QGP is a state of nuclear matter where quarks and gluons are not confined into hadrons. In the forward rapidity region (2.5 < y < 4) ALICE is equipped with a muon spectrometer (MS), allowing the study of the muonic decays of quarkonia (bound states of cc̄ and bb̄ quarks) and open heavy-flavor particles, both key probes to investigate QGP properties.

During the LHC Run 1 and Run 2, event selection in the MS was based on a hardware trigger provided by a set of 72 Resistive Plate Chambers (RPCs) operated in maxi-avalanche mode and referred to as Muon Trigger (MTR). Following a successful upgrade during the LHC Long Shutdown 2 (2019-2022), ALICE is now taking data in continuous readout mode, without a hardware trigger and the Muon Trigger has evolved into a Muon Identifier (MID).

To cope with increased luminosities, reduce aging and enable triggerless readout mode, two major upgrades were carried out. Front-end electronics now include a pre-amplification stage, allowing to switch to avalanche mode and to lower both thresholds and high voltages, while back-end electronics were adapted for continuous readout. These upgrades allow the detector to operate safely and efficiently at a hadronic interaction rate of 50 kHz in Pb-Pb collisions, an increase by more than a factor 5 with respect to Run 2.

A summary of the MID operation during the whole LHC Run 3 will be presented in the contribution. This includes an overview of the RPC performance in terms of efficiency, dark current, dark counting rate and data quality, as well as a report on the charge integrated during Run 3 and a comparison with the Run 1 and Run 2 trends.

Author

Luca Quaglia (Universita e INFN Torino (IT))

Co-author

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