5 papers · 1 filter
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…
Training a neural network to rapidly identify candidate gravitational-wave events in the lower mass gap
Nayyer Raza, Man Leong Chan, Daryl Haggard +5
The physics governing the boundary between the most massive neutron stars (NSs) and the least massive black holes (BHs) is currently uncertain, but could potentially be constrained…
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…
GWSkyNet-Multi II: an updated machine learning model for rapid classification of gravitational-wave events
Nayyer Raza, Man Leong Chan, Daryl Haggard +5
Multi-messenger observations of gravitational waves and electromagnetic emission from compact object mergers offer unique insights into the structure of neutron stars, the formatio…
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.…