60 citations · 62 across the 5 of their papers we have counts for
5 papers
GSpyNetTree-O4: an event validation tool used in the fourth LIGO-Virgo-KAGRA observing run
Sofia Alvarez-Lopez, Man Leong Chan, Franz S. Herbst +7
The frequent presence of non-Gaussian transient noise, or glitches, in gravitational-wave detector data can affect gravitational-wave searches, parameter estimation, and downstream…
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…
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…
GSpyNetTree: A signal-vs-glitch classifier for gravitational-wave event candidates
Sofia Alvarez-Lopez, Annudesh Liyanage, Julian Ding +2
Despite achieving sensitivities capable of detecting the extremely small amplitude of gravitational waves (GWs), LIGO and Virgo detector data contain frequent bursts of non-Gaussia…