5 papers
Microseismic Noise Mitigation with Machine Learning for Advanced LIGO
Christina Reissel, Devin Lai, Shivanshu Dwivedi +9
The unprecedented sensitivity of the Laser Interferometer Gravitational-Wave Observatory, which enables the detection of distant astrophysical sources, also renders the detectors h…
Likelihood-free inference for gravitational-wave data analysis and public alerts
Ethan Marx, Deep Chatterjee, Malina Desai +7
Rapid and reliable detection and dissemination of source parameter estimation data products from gravitational-wave events, especially sky localization, is critical for maximizing…
A machine learning-enabled search for binary black hole mergers in LIGO-Virgo-KAGRAs third observing run
Ethan Marx, William Benoit, Trevor Blodgett +8
We conduct a search for stellar-mass binary black hole mergers in gravitational-wave data collected by the LIGO detectors during the LIGO-Virgo-KAGRA (LVK) third observing run (O3)…
Coherence DeepClean: Toward autonomous denoising of gravitational-wave detector data
Christina Reissel, Siddharth Soni, Muhammed Saleem +3
Technical and environmental noise in ground-based laser interferometers designed for gravitational-wave observations like Advanced LIGO, Advanced Virgo and KAGRA, can manifest as n…
A Neural Network-Based Search for Unmodeled Transients in LIGO-Virgo-KAGRA's Third Observing Run
Ryan Raikman, Eric A. Moreno, Katya Govorkova +13
This paper presents the results of a Neural Network (NN)-based search for short-duration gravitational-wave transients in data from the third observing run of LIGO, Virgo, and KAGR…