학술논문
Improved ranking statistics of the GstLAL inspiral search for compact binary coalescences
Document Type
Working Paper
Author
Tsukada, Leo; Joshi, Prathamesh; Adhicary, Shomik; George, Richard; Guimaraes, Andre; Hanna, Chad; Magee, Ryan; Zimmerman, Aaron; Baral, Pratyusava; Baylor, Amanda; Cannon, Kipp; Caudill, Sarah; Cousins, Bryce; Creighton, Jolien D. E.; Ewing, Becca; Fong, Heather; Godwin, Patrick; Harada, Reiko; Huang, Yun-Jing; Huxford, Rachael; Kennington, James; Kuwahara, Soichiro; Li, Alvin K. Y.; Meacher, Duncan; Messick, Cody; Morisaki, Soichiro; Mukherjee, Debnandini; Niu, Wanting; Pace, Alex; Posnansky, Cort; Ray, Anarya; Sachdev, Surabhi; Sakon, Shio; Singh, Divya; Tapia, Ron; Tsutsui, Takuya; Ueno, Koh; Viets, Aaron; Wade, Leslie; Wade, Madeline
Source
Subject
Language
Abstract
Starting from May 2023, the LIGO Scientific, Virgo and KAGRA Collaboration is planning to conduct the fourth observing run with improved detector sensitivities and an expanded detector network including KAGRA. Accordingly, it is vital to optimize the detection algorithm of low-latency search pipelines, increasing their sensitivities to gravitational waves from compact binary coalescences. In this work, we discuss several new features developed for ranking statistics of GstLAL-based inspiral pipeline, which mainly consist of: the signal contamination removal, the bank-$\xi^2$ incorporation, the upgraded $\rho-\xi^2$ signal model and the integration of KAGRA. An injection study demonstrates that these new features improve the pipeline's sensitivity by approximately 15% to 20%, paving the way to further multi-messenger observations during the upcoming observing run.
Comment: 13pages, 6figures
Comment: 13pages, 6figures