English

Forecast for cosmological parameter estimation with gravitational-wave standard sirens from the LISA-Taiji network

General Relativity and Quantum Cosmology 2021-10-12 v4 Cosmology and Nongalactic Astrophysics High Energy Physics - Phenomenology

Abstract

LISA and Taiji are expected to form a space-based gravitational-wave (GW) detection network in the future. In this work, we make a forecast for the cosmological parameter estimation with the standard siren observation from the LISA-Taiji network. We simulate the standard siren data based on a scenario with configuration angle of 4040^{\circ} between LISA and Taiji. Three models for the population of massive black hole binary (MBHB), i.e., pop III, Q3d, and Q3nod, are considered to predict the events of MBHB mergers. We find that, based on the LISA-Taiji network, the number of electromagnetic (EM) counterparts detected is almost doubled compared with the case of single Taiji mission. Therefore, the LISA-Taiji network's standard siren observation could provide much tighter constraints on cosmological parameters. For example, solely using the standard sirens from the LISA-Taiji network, the constraint precision of H0H_0 could reach 1.3%1.3\%. Moreover, combined with the CMB data, the GW-EM observation based on the LISA-Taiji network could also tightly constrain the equation of state of dark energy, e.g., the constraint precision of ww reaches about 4%4\%, which is comparable with the result of CMB+BAO+SN. It is concluded that the GW standard sirens from the LISA-Taiji network will become a useful cosmological probe in understanding the nature of dark energy in the future.

Keywords

Cite

@article{arxiv.2101.11882,
  title  = {Forecast for cosmological parameter estimation with gravitational-wave standard sirens from the LISA-Taiji network},
  author = {Ling-Feng Wang and Shang-Jie Jin and Jing-Fei Zhang and Xin Zhang},
  journal= {arXiv preprint arXiv:2101.11882},
  year   = {2021}
}

Comments

13 pages, 4 figures; accepted for publication in Science China - Physics, Mechanics & Astronomy