5 papers
Rapid data quality investigations of gravitational-wave events with the Data Quality Report Builder toolkit
Derek Davis, Zach Yarbrough, Joseph Areeda +30
We present the Data Quality Report Builder toolkit, DQRbuild, a suite of data quality tools that have been developed to vet gravitational-wave events in preparation for the fourth…
Coalescing Compact Binary Parameter Estimation with Gravitational Waves in the Presence of non-Gaussian Transient Noise
Yannick Lecoeuche, Jess McIver, Alan M. Knee +7
Data from gravitational-wave (GW) detectors often contains a high rate of non-Gaussian transient noise, known as glitches. The parameters estimated from GW signals coinciding with…
Inferring the spins of merging black holes in the presence of data-quality issues
Rhiannon Udall, Sophie Bini, Katerina Chatziioannou +5
Gravitational waves from black hole binary mergers carry information about the component spins, but inference is sensitive to analysis assumptions, which may be broken by terrestri…
GSpyNetTreeS: a machine learning solution for glitch localization in time and frequency
Man Leong Chan, Jess McIver, Yannick Lecoeuche +6
Data from ground-based gravitational wave detectors are often contaminated by non-Gaussian instrumental artifacts or detector noise transients. Unbiased source property estimation…
LIGO Detector Characterization in the first half of the fourth Observing run
S. Soni, B. K. Berger, D. Davis +232
Progress in gravitational-wave astronomy depends upon having sensitive detectors with good data quality. Since the end of the LIGO-Virgo-KAGRA third Observing run in March 2020, de…