首页|Taiji-TianQin-LISA network:Precisely measuring the Hubble constant using both bright and dark sirens

Taiji-TianQin-LISA network:Precisely measuring the Hubble constant using both bright and dark sirens

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In the coming decades,the space-based gravitational-wave(GW)detectors such as Taiji,TianQin,and LISA are expected to form a network capable of detecting millihertz GWs emitted by the mergers of massive black hole binaries(MBHBs).In this work,we investigate the potential of GW standard sirens from the Taiji-TianQin-LISA network in constraining cosmological parameters.For the optimistic scenario in which electromagnetic(EM)counterparts can be detected,we predict the number of detectable bright sirens based on three different MBHB population models,i.e.,pop Ⅲ,Q3d,and Q3nod.Our results show that the Taiji-TianQin-LISA network alone could achieve a constraint precision of 0.9％for the Hubble constant,meeting the standard of precision cosmology.Moreover,the Taiji-TianQin-LISA network could effectively break the cosmological parameter degenera-cies generated by the CMB data,particularly in the dynamical dark energy models.When combined with the CMB data,the joint CMB+Taiji-TianQin-LISA data offer σ(w)=0.036 in the wCDM model,which is close to the latest constraint result obtained from the CMB+SN data.We also consider a conservative scenario in which EM counterparts are not available.Due to the precise sky localizations of MBHBs by the Taiji-TianQin-LISA network,the constraint precision of the Hubble constant is expected to reach 1.2％.In conclusion,the GW standard sirens from the Taiji-TianQin-LISA network will play a critical role in helping solve the Hubble tension and shedding light on the nature of dark energy.

space-based gravitational wave detectionstandard sirensthe Taiji-TianQin-LISA networkthe Hubble constantdark energy

Shang-Jie Jin、Ye-Zhu Zhang、Ji-Yu Song、Jing-Fei Zhang、Xin Zhang

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

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

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

National SKA Program of ChinaNational SKA Program of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational 111 ProjectFundamental Research Funds for the Central Universities

2022SKA01102002022SKA0110203119750721187510211835009B16009N232410019

2024

10.1007/s11433-023-2276-1

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(2)
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