Virgo detector characterization and data quality: tools

Open Access
Authors
Publication date 10-09-2023
Journal Classical and Quantum Gravity
Article number 185005
Volume | Issue number 40 | 18
Number of pages 43
Organisations
  • Faculty of Science (FNWI) - Anton Pannekoek Institute for Astronomy (API)
  • Faculty of Science (FNWI) - Institute of Physics (IoP) - Institute for High Energy Physics (IHEF)
Abstract
Detector characterization and data quality studies—collectively referred to as DetChar activities in this article—are paramount to the scientific exploitation of the joint dataset collected by the LIGO-Virgo-KAGRA global network of ground-based gravitational-wave (GW) detectors. They take place during each phase of the operation of the instruments (upgrade, tuning and optimization, data taking), are required at all steps of the dataflow (from data acquisition to the final list of GW events) and operate at various latencies (from near real-time to vet the public alerts to offline analyses). This work requires a wide set of tools which have been developed over the years to fulfill the requirements of the various DetChar studies: data access and bookkeeping; global monitoring of the instruments and of the different steps of the data processing; studies of the global properties of the noise at the detector outputs; identification and follow-up of noise peculiar features (whether they be transient or continuously present in the data); quick processing of the public alerts. The present article reviews all the tools used by the Virgo DetChar group during the third LIGO-Virgo Observation Run (O3, from April 2019 to March 2020), mainly to analyze the Virgo data acquired at EGO. Concurrently, a companion article focuses on the results achieved by the DetChar group during the O3 run using these tools.
Document type Article
Language English
Related publication Virgo detector characterization and data quality: results from the O3 run
Published at https://doi.org/10.48550/arXiv.2210.15634 https://doi.org/10.1088/1361-6382/acdf36
Downloads
2210.15634 (Submitted manuscript)
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