Performance of the low-latency GstLAL inspiral search towards LIGO, Virgo, and KAGRA's fourth observing run

被引：6

作者：

Ewing, Becca ^{[1
,2
]}

Huxford, Rachael ^{[1
,2
]}

Singh, Divya ^{[1
,2
]}

Tsukada, Leo ^{[1
,2
]}

Hanna, Chad ^{[1
,2
,3
,4
]}

Huang, Yun-Jing ^{[1
,2
]}

Joshi, Prathamesh ^{[1
,2
]}

Li, Alvin K. Y. ^{[5
]}

Magee, Ryan ^{[5
]}

Messick, Cody ^{[6
]}

Pace, Alex ^{[1
,2
]}

Ray, Anarya ^{[7
]}

Sachdev, Surabhi ^{[7
,8
]}

Sakon, Shio ^{[1
,2
]}

Tapia, Ron ^{[1
,4
]}

Adhicary, Shomik ^{[1
,2
]}

Baral, Pratyusava ^{[7
]}

Baylor, Amanda ^{[7
]}

Cannon, Kipp ^{[9
]}

Caudill, Sarah ^{[10
,11
]}

Chaudhary, Sushant Sharma ^{[12
]}

Coughlin, Michael W. ^{[13
]}

Cousins, Bryee ^{[1
,2
,14
]}

Creighton, Jolien D. E. ^{[7
]}

Essick, Reed ^{[15
]}

Fong, Heather ^{[9
,16
]}

George, Richard N. ^{[17
]}

Godwin, Patrick ^{[1
,2
,18
]}

Harada, Reiko ^{[9
,16
]}

Kennington, James ^{[1
,2
]}

Kuwahara, Soichiro ^{[9
,16
]}

Meacher, Duncan ^{[7
]}

Morisaki, Soichiro ^{[7
,19
]}

Mukherjee, Debnandini ^{[20
,21
]}

Niu, Wanting ^{[1
,2
]}

Posnansky, Cort ^{[1
,2
]}

Toivonen, Andrew ^{[13
]}

Tsutsui, Takuya ^{[9
]}

Ueno, Koh ^{[9
]}

Viets, Aaron ^{[22
]}

Wade, Leslie ^{[23
]}

Wade, Madeline ^{[23
]}

Waratkar, Gaurav ^{[24
]}

机构：

[1] Penn State Univ, Dept Phys, University Pk, PA 16802 USA

[2] Penn State Univ, Inst Gravitat & Cosmos, University Pk, PA 16802 USA

[3] Penn State Univ, Dept Astron & Astrophys, University Pk, PA 16802 USA

[4] Penn State Univ, Inst Computat & Data Sci, University Pk, PA 16802 USA

[5] CALTECH, LIGO Lab, Pasadena, CA 91125 USA

[6] MIT, Kavli Inst Astrophys & Space Res, Cambridge, MA 02139 USA

[7] Univ Wisconsin Milwaukee, Leonard E Parker Ctr Gravitat Cosmol & Astrophys, Milwaukee, WI USA

[8] Georgia Inst Technol, Sch Phys, Atlanta, GA 30332 USA

[9] Univ Tokyo, RESCEU, Tokyo 1130033, Japan

[10] Univ Massachusetts, Dept Phys, Dartmouth, MA 02747 USA

[11] Univ Massachusetts, Ctr Sci Comp & Data Sci Res, Dartmouth, MA 02747 USA

[12] Missouri Univ Sci & Technol, Inst Multimessenger Astrophys & Cosmol, Phys Bldg 1315 North Pine St, Rolla, MO 65409 USA

[13] Univ Minnesota, Sch Phys & Astron, Minneapolis, MN 55455 USA

[14] Univ Illinois, Dept Phys, Urbana, IL 61801 USA

[15] Canadian Inst Theoret Astrophys, 60 St George St, Toronto, ON M5S 3H8, Canada

[16] Univ Tokyo, Grad Sch Sci, Tokyo 1130033, Japan

[17] Univ Texas Austin, Ctr Gravitat Phys, Austin, TX 78712 USA

[18] CALTECH, LIGO Lab, MS 100-36, Pasadena, CA 91125 USA

[19] Univ Tokyo, Inst Cosm Ray Res, 5-1-5 Kashiwanoha Kashiwa, Chiba 2778582, Japan

[20] NASA Marshall Space Flight Ctr, Huntsville, AL 35811 USA

[21] Univ Alabama Huntsville, Ctr Space Plasma & Aeron Res, Huntsville, AL 35899 USA

[22] Concordia Univ Wisconsin, Mequon, WI 53097 USA

[23] Kenyon Coll, Dept Phys, 212 Hayes Hall, Gambier, OH 43022 USA

[24] Indian Inst Technol, Environm Sci & Engn Dept, Mumbai 400076, India

来源：

PHYSICAL REVIEW D | 2024年 / 109卷 / 04期

基金：

加拿大自然科学与工程研究理事会; 美国国家科学基金会;

关键词：

D O I：

10.1103/PhysRevD.109.042008

中图分类号：

P1 [天文学];

学科分类号：

0704 ;

摘要：

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 and neutron stars. Over the past three observation runs by the LIGO, Virgo, and KAGRA Collaboration, the GstLAL search pipeline has participated in several tens of gravitational wave discoveries. The fourth observing run (O4) is set to begin in May 2023 and is expected to see the discovery of many new and interesting gravitational wave signals which will inform our understanding of astrophysics and cosmology. We describe the current configuration of the GstLAL low -latency search and show its readiness for the upcoming observation run by presenting its performance on a mock data challenge. The mock data challenge includes 40 days of LIGO Hanford, LIGO Livingston, and Virgo strain data along with an injection campaign in order to fully characterize the performance of the search. We find an improved performance in terms of detection rate and significance estimation as compared to that observed in the O3 online analysis. The improvements are attributed to several incremental advances in the likelihood ratio ranking statistic computation and the method of background estimation.

引用

页数：18

共 19 条

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