Unveiling a multi-component stochastic gravitational-wave background with the TianQin + LISA network
Zheng-Cheng Liang, Zhi-Yuan Li, En-Kun Li, Jian-dong Zhang, Yi-Ming Hu

TL;DR
This paper demonstrates that a space-borne detector network combining TianQin and LISA can detect and distinguish multiple stochastic gravitational-wave backgrounds from astrophysical and cosmological sources within four years, despite foreground noise.
Contribution
It introduces a novel likelihood method for cross-correlation detection using a space-borne detector network and applies it to simulated data for model selection and parameter estimation.
Findings
Detection of a single SGWB within 4 years at $ imes 10^{-12}$ energy density.
Ability to distinguish cosmological background at $ imes 10^{-11}$ energy density.
Network can identify multiple SGWBs despite Galactic foreground interference.
Abstract
Space-borne detectors, including TianQin and Laser Interferometry Space Antenna (LISA), are tasked with simultaneously observing the Galactic foreground, astrophysical and cosmological stochastic gravitational-wave backgrounds (SGWBs). For the first time, we employ a space-borne detector network to identify these SGWBs. Specifically, we develop a tailored likelihood for cross-correlation detection with such networks. Combined with the likelihood, we use the simulated datasets of the TianQin + LISA network to conduct an analysis for model selection and parameter estimation. In our analysis, we adopt an astrophysical background originating from extragalactic white-dwarf binaries, along with a flat cosmological background associated with the early Universe. Our results indicate that, after 4 years of operation, the network could detect a single SGWB from either astrophysical or…
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Taxonomy
TopicsEarthquake Detection and Analysis · Pulsars and Gravitational Waves Research · Complex Systems and Time Series Analysis
