104 citations · 170 across the 20 of their papers we have counts for
7 papers · 1 filter
Hybrid algorithm combining matched filtering and convolutional neural networks for searching gravitational waves from binary black hole mergers
Takahiro S. Yamamoto, Kipp Cannon, Hayato Motohashi +1
Efficient searches for gravitational waves from compact binary coalescence are crucial for gravitational wave observations. We present a proof-of-concept for a method that utilizes…
Estimation of the Hubble parameter from unedited compact object merger catalogues
Reiko Harada, Heather Fong, Kipp Cannon
In recent years, constraints on the Hubble parameter using multiple dark sirens have been made,relying on a galaxy catalogue, correlations between the mass and redshift distributio…
Auto-encoder model for faster generation of effective one-body gravitational waveform approximations
Suyog Garg, Feng-Li Lin, Kipp Cannon
Upgrades to current gravitational wave detectors for the next observation run and upcoming third-generation observatories, like the Einstein telescope, are expected to have enormou…
Observational constraints on the nonlinear regime of gravity with a parametrized beyond-GR gravitational waveform model
Daiki Watarai, Atsushi Nishizawa, Hiroki Takeda +2
Gravitational waves from compact binary coalescences provide unique opportunities to test general relativity (GR) in the strong-field regime. In particular, the merger phase, durin…
New Methods for Offline GstLAL Analyses
Prathamesh Joshi, Leo Tsukada, Chad Hanna +38
In this work, we present new methods implemented in the GstLAL offline gravitational wave search. These include a technique to reuse the matched filtering data products from a GstL…
How Many Times Should We Matched Filter Gravitational Wave Data? A Comparison of GstLAL's Online and Offline Performance
Prathamesh Joshi, Wanting Niu, Chad Hanna +34
Searches for gravitational waves from compact binary coalescences employ a process called matched filtering, in which gravitational wave strain data is cross-correlated against a b…