10 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…
Fast targeted gravitational-wave followup search for compact binary mergers using GSTLAL pipeline
Leo Tsukada, Noah Zhang, Surabhi Sachdev +4
We present a novel method to conduct targeted gravitational-wave searches for compact binary mergers using the GstLAL inspiral pipeline. By incorporating sky localization and timin…
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…