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arXiv · 2603.13080

Three-band dark-siren cosmology with intermediate mass black hole binaries: Synergy of Taiji, LGWA, and the Einstein Telescope

Ji-Yu Song·Yue-Yan Dong·Shang-Jie Jin·Si-Ren Xiao·Jing-Fei Zhang·Xin Zhang
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Abstract

Gravitational-wave (GW) dark sirens provide an independent probe of the cosmic expansion history. Their cosmological constraining power, however, depends critically on precise luminosity-distance measurements and sky localizations for cross-matching with galaxy catalogs. Multiband GW observations can track GW events across different frequency bands and thus improve both. Motivated by this, we forecast the cosmological potential of intermediate-mass black hole binaries (IMBHBs) observed by a three-band GW detector network composed of Taiji (TJ), the Lunar Gravitational-wave Antenna (LGWA), and the Einstein Telescope (ET). We simulate detectable IMBHB populations and analyze them with a hierarchical Bayesian dark-siren framework that includes galaxy-catalog completeness and redshift uncertainties. We find that the TJ-LGWA-ET network outperforms all two-detector configurations considered here. In the $\Lambda$CDM model, it constrains the Hubble constant and matter density to $\sim 0.12\%$ and $\sim 0.6\%$, respectively. In the $w$CDM model, a 4-year dark-siren sample alone constrains the dark-energy equation-of-state parameter $w$ to $\sim 2.7\%$. Adding baryon acoustic oscillation (BAO) and Type Ia supernova (SNe Ia) data improves the $w$ constraint to $\sim 2.1\%$, slightly better than that from the current CMB+BAO+SNe Ia combination. We also show that the final constraints remain sensitive to IMBHB population assumptions and galaxy-catalog limitations, which highlights the need for deep galaxy surveys with precise redshift measurements.

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Ji-Yu Song, Yue-Yan Dong, Shang-Jie Jin, Si-Ren Xiao, Jing-Fei Zhang, Xin Zhang. 2026-03-13. Three-band dark-siren cosmology with intermediate mass black hole binaries: Synergy of Taiji, LGWA, and the Einstein Telescope. https://arxiv.org/abs/2603.13080

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