415 citations · 1.6k across the 22 of their papers we have counts for
22 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…
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…
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…
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…
GWSkyNet II : a refined machine learning pipeline for real-time classification of public gravitational wave alerts
Man Leong Chan, Jess McIver, Ashish Mahabal +12
Electromagnetic follow-up observations of gravitational wave events offer critical insights and provide significant scientific gain from this new class of astrophysical transients.…