ATLAS Data Quality Monitoring

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ATLAS Data Quality Monitoring

Introduction

The ATLAS Data Quality group provides the tools to monitor ATLAS data and provides data quality information to physics analyses. I have co-authored and maintained the data quality tools of of muon Cathode Strip Chambers (CSC) sub-detector, Trigger and Data Acquisition (TDAQ) system - specifically of the jet and MET triggers during the last four years (2008-12).

Muon CSC Data Quality
Trigger/Data Acquisition Data Quality
ATLAS notes related to Muon CSC, trigger jet/MET Data Quality

Muon CSC Data Quality

Muons resulting from the collision event traverse the Cathode Strip Chambers (CSC) and ionize the gaseous medium in a strong electric field. The ionization is recorded by the readout electronics using four time samples of induced charge measurements from the strips in a chamber. Adjacent strips with charge above threshold are grouped into clusters. Muon track segments are built from clusters. Muon trajectory and hence its momentum are measured by a global fit to the tracks. Data collected by the readout electronics is digitized and stored in raw (hits) format. Muon reconstruction algorithms calibrate and convert the raw hits into muon tracks. Data quality monitoring involves defining monitored quantities at each stage of reconstruction i.e., raw hits, clusters and track segments, histogramming them, performing checks on monitored quantities and extracting results and overall data quality assessment from the set of monitored quantities.

Contribution

Defined monitored quantities for CSC detector: raw hits, cluster and segments
Co-authored CSC monitoring algorithms written within Athena data quality monitoring framework
Defined checks on monitored quantities, some specific to CSC monitoring are:
- Sideband test for cluster sampling time
- Grubbs outlier test to identify noisy / dead channels
- Most probable value (MPV) of Landau fit to cluster charge sum
- Checks on chamber segment-efficiency
Muon physics monitoring using muon tracks from Z to mu mu control sample
Developed and coded summary algorithm to assess overall data quality of muon CSC detector and flag data-taking runs as normal (green), abnormal (red) [ Back to top ]

Trigger/Data Acquisition (TDAQ) Data Quality

ATLAS triggering system is designed to identify and flag collision events of interest for physics analyses and performance studies. It has a three-level architecture which includes a first level (L1) of decision made by fast electronics (custom hardware) and subsequent two levels (L2 and Event Filter) operating in a software environment. The three levels are designed to select physics events of interest and filter them at each successive level finally to be digitized and stored by the data-acquisition system. I co-authored and maintained the monitoring of jets and missing transverse energy (MET) triggers.

Contribution

Developed and maintained jet and MET offline monitoring tools (2009 - 2012)

Histograms of basic jet trigger signatures, trigger efficiency, comparison of online/offline quantities
MET histograms of various calorimeter components as a function of detector pseudorapidity and azimuthal angle for different definitions of trigger MET (cell-based, locally calibrated topological clusters, FEB-based) definitions. Post-processing of histograms to extract information on status of run (red/green)
Developed algorithms for automatic data quality assessment based on monitored histograms

Provided documentation/references to help data quality shifters/on-call data quality experts and participated and presented status updates in regular monitoring reviews [ Back to top ]

ATLAS notes related to Muon CSC, trigger jet and MET Data Quality

Muon Offline Monitoring at Tier0 using cosmics and FDR (full dress rehearsal) data [ Internal Note ]
Performance of the ATLAS jet trigger in early data [ 7 TeV, 900 GeV ]
Performance of the ATLAS Missing ET trigger in early data [ 7 TeV, 900 GeV ]
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