首页|Synergy between CSST galaxy survey and gravitational-wave observation:Inferring the Hubble constant from dark standard sirens

Synergy between CSST galaxy survey and gravitational-wave observation:Inferring the Hubble constant from dark standard sirens

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Gravitational waves(GWs)from compact binary coalescences encode the absolute luminosity distances of GW sources.Once the redshifts of GW sources are known,one can use the distance-redshift relation to constrain cosmological parameters.One way to obtain the redshifts is to localize GW sources by GW observations and then use galaxy catalogs to determine redshifts from a statistical analysis of redshift information of the potential host galaxies,commonly referred to as the dark siren method.The third-generation(3G)GW detectors are planned to work in the 2030s and will observe numerous compact binary coalescences.Using these GW events as dark sirens requires high-quality galaxy catalogs from future sky survey projects.The China Space Station Telescope(CSST)will be launched in 2024 and will observe billions of galaxies within a 17500 deg2 survey area with redshift up to z～4,providing photometric and spectroscopic galaxy catalogs.In this work,we simulate the CSST galaxy catalogs and the 5-year GW data from the 3G GW detectors and combine them to infer the Hubble constant(H0).Our results show that the measurement precision of H0 could reach the sub-percent level,meeting the standard of precision cosmology.We conclude that the synergy between CSST and the 3G GW detectors is of great significance in measuring the Hubble constant.

CSST galaxy surveygalaxy catalogsgravitational wavesdark sirensthe Hubble constant

Ji-Yu Song、Ling-Feng Wang、Yichao Li、Ze-Wei Zhao、Jing-Fei Zhang、Wen Zhao、Xin Zhang

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Key Laboratory of Cosmology and Astrophysics(Liaoning)& College of Sciences,Northeastern University Shenyang 110819,China

CAS Key Laboratory for Researches in Galaxies and Cosmology,Department of Astronomy,University of Science and Technology of China,Chinese Academy of Sciences,Hefei 230026,China

School of Astronomy and Space Sciences,University of Science and Technology of China,Hefei 230026,China

National Frontiers Science Center for Industrial Intelligence and Systems Optimization,Northeastern University,Shenyang 110819,China

Key Laboratory of Data Analytics and Optimization for Smart Industry(Ministry of Education),Northeastern University Shenyang 110819,China

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National SKA Program of ChinaNational SKA Program of China国家自然科学基金国家自然科学基金国家自然科学基金science research grants from the China Manned Space Project高等学校学科创新引智计划(111计划)

2022SKA01102002022SKA0110203119750721187510211835009CMS-CSST-2021-B01B16009

2024

10.1007/s11433-023-2260-2

中国科学:物理学 力学 天文学(英文版)
中国科学院

中国科学:物理学 力学 天文学(英文版)

CSTPCD
影响因子：0.91
ISSN：1674-7348
年,卷(期)：2024.67(3)
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