Detection of the stochastic gravitational wave background with the space-borne gravitational-wave detector network

TL;DR

This paper develops a Bayesian data analysis method for detecting the stochastic gravitational wave background using a network of space-borne detectors like TianQin and LISA, demonstrating potential for confident detection within three months.

Contribution

It introduces a Bayesian analysis approach based on TDI channels for SGWB detection with detector networks, addressing challenges when noise monitoring channels are unavailable.

Findings

TianQin-LISA network can detect SGWB with energy density as low as 6.0×10⁻¹³ for power-law models.

The method achieves detection thresholds of 2.0×10⁻¹² and 1.2×10⁻¹² for flat and single-peak models.

Three-month observation period suffices for confident detection of various SGWB models.

Abstract

The stochastic gravitational wave background (SGWB) is one of the main detection targets for future millihertz space-borne gravitational-wave observatories such as the \ac{LISA}, TianQin, and Taiji. For a single LISA-like detector, a null-channel method was developed to identify the SGWB by integrating data from the A and E channels with a noise-only T channel. However, the noise monitoring channel will not be available if one of the laser interferometer arms fails. By combining these detectors, it will be possible to build detector networks to search for SGWB via cross-correlation analysis.In this work, we developed a Bayesian data analysis method based on \ac{TDI} Michelson-type channel. We then investigate the detectability of the TianQin-LISA detector network for various isotropic SGWB. Assuming a three-month observation, the TianQin-LISA detector network could be able to confidently detect SGWB with energy density as low as $\Omega_{\rm PL} = 6.0 \times 10^{-13}$, $\Omega_{\rm Flat} = 2.0 \times 10^{-12}$ and $\Omega_{\rm SP} = 1.2 \times 10^{-12}$ for power-law, flat and single-peak models, respectively.