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Demonstration of Machine Learning-assisted real-time noise regression in gravitational wave detectors
Muhammed Saleem, Alec Gunny, Chia-Jui Chou +17
Real-time noise regression algorithms are crucial for maximizing the science outcomes of the LIGO, Virgo, and KAGRA gravitational-wave detectors. This includes improvements in the…
QoQ: a Q-transform based test for Gravitational Wave transient events
Siddharth Soni, Ethan Marx, Erik Katsavounidis +6
The observation of transient gravitational waves is hindered by the presence of transient noise, colloquially referred to as glitches. These glitches can often be misidentified as…
Performance of the low-latency GstLAL inspiral search towards LIGO, Virgo, and KAGRA's fourth observing run
Becca Ewing, Rachael Huxford, Divya Singh +40
GstLAL is a stream-based matched-filtering search pipeline aiming at the prompt discovery of gravitational waves from compact binary coalescences such as the mergers of black holes…
Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network
The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration +1692
Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about funda…
Open data from the third observing run of LIGO, Virgo, KAGRA and GEO
The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration +1741
The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data…
Correlated 1-1000 Hz magnetic field fluctuations from lightning over earth-scale distances and their impact on gravitational wave searches
Kamiel Janssens, Matthew Ball, Robert M. S. Schofield +9
We report Earth-scale distance magnetic correlations from lightning strokes in the frequency range 1-1000 Hz at several distances ranging from 1100 to 9000 km. Noise sources which…