Publications (17)
When to Point Your Telescopes: Gravitational Wave Trigger Classification for Real-Time Multi-Messenger Followup Observations
Anarya Ray, Wanting Niu, Shio Sakon +36
We develop a robust and self-consistent framework to extract and classify gravitational wave candidates from noisy data, for the purpose of assisting in real-time multi-messenger f…
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…
A binary tree approach to template placement for searches for gravitational waves from compact binary mergers
Chad Hanna, James Kennington, Shio Sakon +30
We demonstrate a new geometric method for fast template placement for searches for gravitational waves from the inspiral, merger and ringdown of compact binaries. The method is bas…
Gauge Theoretic Signal Processing II: Zero-Latency Whitening for Early Warning Pipelines
James Kennington, Joshua Black, Zach Yarbrough +9
Low-latency gravitational-wave search pipelines provide early-warning alerts for multimessenger astrophysical transients. Current pipelines whiten the data stream using acausal, li…
SGNL: Scalable Low-Latency Gravitational Wave Detection Pipeline for Compact Binary Mergers
Yun-Jing Huang, Chad Hanna, Leo Tsukada +8
We present SGNL, a scalable, low-latency gravitational-wave search pipeline. It reimplements the core matched-filtering principles of the GstLAL pipeline within a modernized framew…
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…