Monitoring and data quality assessment of the ATLAS liquid argon calorimeter

TL;DR

The paper details a comprehensive data quality framework for the ATLAS LAr calorimeter, combining online and offline monitoring, a robust calibration-loop, and a defect-logging system to maximize usable physics data. It documents concrete methods to identify and mitigate HV trips, large-scale coherent noise, and per-channel noise, including time-window vetoes and per-run channel masking. The results show substantial data-quality improvements from 2011 to 2012, achieving data usability at the ~98–99% level across large datasets, with low losses even under high-luminosity conditions and varied collision systems. The work provides practical strategies and infrastructure for maintaining calorimeter data integrity in future, higher-luminosity LHC runs, including planned hardware upgrades and automation enhancements. Overall, the study demonstrates a mature, end-to-end approach to preserving calorimeter data quality for precision ATLAS physics analyses.

Abstract

The liquid argon calorimeter is a key component of the ATLAS detector installed at the CERN Large Hadron Collider. The primary purpose of this calorimeter is the measurement of electrons and photons. It also provides a crucial input for measuring jets and missing transverse momentum. An advanced data monitoring procedure was designed to quickly identify issues that would affect detector performance and ensure that only the best quality data are used for physics analysis. This article presents the validation procedure developed during the 2011 and 2012 LHC data taking periods, in which more than 98% of the proton proton luminosity recorded by ATLAS at a centre-of-mass energy of 7 and 8 TeV had calorimeter data quality suitable for physics analysis.

Figures (27)

• Figure 1: (a) Cut-away view of the liquid argon calorimeter. (b) Signal shape as produced in the electromagnetic barrel (triangle), and after shaping (curve with dots). The dots represent the time and amplitude of the digitized samples.
• Figure 2: ATLAS data processing and monitoring organization and calibration loop scheme (with focus on the LAr calorimeter case).
• Figure 3: Example of a typical trip of a HV line supplying one HEC sector. (a) Recorded voltage, current and status evolution. The luminosity block numbers shown in bold indicate a red DCS flag. (b) Number of readout cells with a HV correction greater than 5% (with respect to the start of run) as a function of the luminosity block number.
• Figure 4: Distributions of missing transverse momentum, $E_{\rm{T}}^{\rm{miss}}$, measured in 2011 collision data in JetTauEtmiss stream for luminosity blocks with stable HV conditions (dashed line), a HV trip (dotted line) and a HV line ramping up (full line). Distributions are shown (a) without any jet-cleaning and (b) with a loose jet-cleaning procedure applied.
• Figure 5: Lost luminosity due to (a) HV trips and (b) inefficient areas impacting detector coverage as a function of the data-taking period in 2012.