Listening Across the Cosmic Time: Standard Sirens from Ground- and Space-Based Missions in the Next Decade

Abstract

Precise measurement of the Hubble parameter will enable stringent tests of the standard model for cosmology. Standard sirens, using the luminosity distances measured by gravitational-wave observations of compact binary mergers, are expected to provide such measurements independently in the next decade. With the ground- and space-based gravitational wave observatories, the LIGO-Virgo-KAGRA (LVK) network and the Laser Interferometer Space Antenna (LISA), different types of standard sirens altogether will place constraints across a wide redshift range. In this paper, we forecast the precisions of standard siren Hubble parameter measurements and compare various scenarios, accounting for the dominant sources of systematic uncertainty. Specifically, we find a $2\%$ constraint on $H_0$, a $1.5-3\%$ constraint on $H(z)$ at $z=1$, and a $3-5\%$ constraint on $H(z)$ at $z=7$ when combining LVK and LISA standard sirens with precise redshift measurements from electromagnetic counterpart observations. We do not find a significant improvement when including standard sirens with no EM counterpart, but which rely on features in the black hole mass distribution, and the potential systematics introduced by the possible redshift evolution of such features could further degrade the measurement accuracy if not properly accounted for.

Figures (6)

• Figure 1: The three simulated primary mass distribution evolution scenarios. The left, central and right panel shows a Mass-peak only, a Power-law only, and a combined Peak+Power-law evolution in redshift, respectively.
• Figure 2: $H_0$ and $\Omega_m$ joint inference using a population of LVK spectral sirens evolved with the Power-law only evolution scenario. We show the cosmological parameter inference with (blue) and without (orange) assuming the mass distribution evolves in the inference. The different shaded regions report the $68\%$, $90\%$, and $95\%$ credible intervals. The fiducial cosmological values are shown as black dashed lines. The dashed blue lines in the marginalized posterior distributions indicate the $68\%$ credible intervals for the inference that assumes an evolving primary mass distribution.
• Figure 3: An example of the inferred cosmological parameter posterior from different sirens and the combined posterior. The blue, orange, and green contours show the joint ($H_0$, $\Omega_m$) posterior inferred from the LVK spectral (assuming the mass distribution evolves following the Power-law only scenario), LVK bright, and PessimisticPop3 LISA bright sirens, respectively. The red contour shows the combined posterior of the three. The black dashed lines denote the injected $H_0$ and $\Omega_m$ values. The different shaded regions represent the 68% (dark) and 90% (light) credible intervals.
• Figure 4: Relative systematic uncertainties for LVK spectral sirens. We estimate the systematics by comparing the absolute difference between the medians of the $H(z)$ posteriors inferred assuming evolving and non-evolving primary mass distribution, for three different evolution scenarios: Mass-peak only, Power-law only, and Peak+Power-law. Left panel: LVK spectral sirens only. Central panel: combination of LVK spectral and LVK bright sirens. Right panel: combination of LVK spectral, LVK bright, and LISA bright sirens (Pop3 Pessimistic scenario). Combining all classes of sources reduces the relative systematic uncertainties across redshift and mitigates the variability between different evolution scenarios.
• Figure 5: Left panels: Relative statistical uncertainties on $H(z)$ obtained from the different methods considered, shown for the LVK bright sirens, LVK spectral sirens with a Peak+Power-law evolving primary mass distribution, and the LISA bright siren Pop3 formation channel. The upper and lower panels correspond to the LISA bright siren Pessimistic and Optimistic EM counterpart scenarios, respectively. Right panels: same as the left panel but including the spectral siren systematic ($\sigma_{\rm syst}$) uncertainties.