Automating Veto Algorithms for Application to the Search for Burst Gravitational Waves with LIGO

Document #:

LIGO-G2201147-v1

Document type:

G - Presentations (eg Graphics)

Abstract:

The Laser Interferometer Gravitational-Wave Observatory (LIGO) measures astrophysical gravitational waves. During the process of data acquisition, transient noise from environmental and instrumental sources creates glitches in the data. The impact of these glitches on the search for gravitational waves can be mitigated by removing (vetoing) them from the data. Omicron is an algorithm that is currently used to automatically identify data segments likely to be glitches. Two different statistical algorithms evaluate data quality when Omicron glitches originating from different auxiliary channels are vetoed: hierarchical veto (Hveto) and Used Percentage Veto (UPV).
 
This research applies these automated veto tools to evaluate their potential to improve the search for burst (unmodelled) gravitational waves. We have developed software to collect the daily results of Hveto and UPV and apply those candidate vetoes to the burst search algorithm, Coherent WaveBurst (cWB). The results are evaluated by the Veto Evaluation Tool (VET) to measure a veto’s efficiency in removing cWB triggers, deadtime (amount of time removed by the veto), and the ratio of efficiency to deadtime. The higher this ratio, the more effective the veto. This work will be integrated onto the LIGO summary webpages, a data quality utility that is available to the entire LIGO collaboration.
 
Results of this research show that Hveto and UPV provide vetoes that identify unique glitch features, and both have the potential to improve data quality for burst gravitational wave search.

Files in Document:

• PDF Poster (G2201147-v1.pdf, 6.3 MB)

Topics:

• Data Analysis
• Detector Characterization
• GW Bursts
• Data quality / vetoes

Authors:

• Michael Davis
• Amber Stuver