Back to Search
Start Over
Prospects for improving cosmological parameter estimation with gravitational-wave standard sirens from Taiji.
- Source :
-
Science bulletin [Sci Bull (Beijing)] 2020 Aug 30; Vol. 65 (16), pp. 1340-1348. Date of Electronic Publication: 2020 Apr 28. - Publication Year :
- 2020
-
Abstract
- Taiji, a space-based gravitational-wave observatory, consists of three satellites forming an equilateral triangle with arm length of 3×10 <superscript>6</superscript> km, orbiting around the Sun. Taiji is able to observe the gravitational-wave standard siren events of massive black hole binary (MBHB) merger, which is helpful in probing the expansion of the universe. In this paper, we preliminarily forecast the capability of Taiji for improving cosmological parameter estimation with the gravitational-wave standard siren data. We simulate five-year standard siren data based on three fiducial cosmological models and three models of MBHB's formation and growth. It is found that the standard siren data from Taiji can effectively break the cosmological parameter degeneracies generated by the cosmic microwave background (CMB) anisotropies data, especially for dynamical dark energy models. The constraints on cosmological parameters are significantly improved by the data combination CMB + Taiji, compared to the CMB data alone. Compared to the current optical cosmological observations, Taiji can still provide help in improving the cosmological parameter estimation to some extent. In addition, we consider an ideal scenario to investigate the potential of Taiji on constraining cosmological parameters. We conclude that the standard sirens of MBHB from Taiji will become a powerful cosmological probe in the future.<br />Competing Interests: Conflict of interest The authors declare that they have no conflict of interest.<br /> (Copyright © 2020 Science China Press. Published by Elsevier B.V. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 2095-9281
- Volume :
- 65
- Issue :
- 16
- Database :
- MEDLINE
- Journal :
- Science bulletin
- Publication Type :
- Academic Journal
- Accession number :
- 36659212
- Full Text :
- https://doi.org/10.1016/j.scib.2020.04.032