6 papers
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…
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…
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…
GW231109_235456: A Sub-threshold Binary Neutron Star Merger in the LIGO-Virgo-KAGRA O4a Observing Run?
Wanting Niu, Carl-Johan Haster, Jolien D. E. Creighton +25
We present a subthreshold search for gravitational-wave inspirals from binary neutron stars using data from the first part of the fourth observing run of the LIGO-Virgo-KAGRA Colla…
Template bank for sub solar mass compact binary mergers in the fourth observing run of Advanced LIGO, Advanced Virgo, and KAGRA
Chad Hanna, James Kennington, Wanting Niu +38
Matched-filtering searches for gravitational-wave signals from compact binary mergers employ template banks which are a collection of modeled waveforms described by unique intrinsi…