8 papers
No persuasive evidence yet of gravitational-wave tails from perturbers along the line of sight in LVK observations
Kuba Kopczuk, Ethan Blake, Matthew F. Carney +7
The authors search LIGO‑Virgo‑KAGRA data for gravitational‑wave tail signals, called "glints," using Bayesian model comparison and find no convincing evidence, setting upper limits…
SGN: A python framework for stream-processing pipelines
Yun-Jing Huang, Olivia Godwin, Chad Hanna +11
We present the Stream Graph Navigator (SGN), a lightweight Python framework for building streaming data applications. In SGN, stream-processing pipelines are built by connecting co…
Method to get Better Sky Maps in a GstLAL Low-Latency Analysis
Prathamesh Joshi, Becca Ewing, Chad Hanna +40
Modeled gravitational wave searches correlate the strain data with a bank of gravitational wave template waveforms to make detections of gravitational wave candidates, and these re…
GstLAL O4 Online Results Paper
Shomik Adhicary, Pratyusava Baral, Amanda Baylor +39
Gravitational-wave observations of merging binary neutron stars and black holes are now routinely made by detectors in the Advanced LIGO-Virgo-KAGRA network. Neutron star binary sy…
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…