From the 2 of 5 linked papers with an AI index.
1 citations · 1 across the 3 of their papers we have counts for
5 papers
LIGO Detector Characterization in the Second and Third Parts of the Fourth Observing Run
J. Glanzer, A. F. Helmling-Cornell, A. Calafat +244
LIGO detector characterization efforts enabled the confident detection of gravitational waves from hundreds of compact binary coalescences during the fourth observing run. Reliable…
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 paper presents GSpyNetTree-O4, a machine‑learning tool deployed in the fourth LIGO‑Virgo‑KAGRA observing run to classify detector glitches and validate gravitational‑wave event…
Nowhere left to hide: revealing realistic gravitational-wave populations in high dimensions and high resolution with PixelPop
Sofia Alvarez-Lopez, Jack Heinzel, Matthew Mould +1
The paper presents PixelPop, a high‑resolution Bayesian non‑parametric framework that captures multidimensional correlations among masses, spins, and redshifts of binary black hole…
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…