Speaker
Description
The stochastic gravitational-wave background (SGWB) is a key science target for next-generation detectors. In this talk, I will present a Bayesian study of the impact of correlated noise on SGWB reconstruction in the triangular Einstein Telescope configuration. Using simulated data, I will show that neglecting detector correlations can significantly bias the inferred SGWB parameters, while a joint inference of signal and noise yields an unbiased recovery of both.
This study provides a useful example of how such correlations can affect the SGWB inference and it is linked to the LISA data analysis where similar effects are present. More broadly, it highlights the importance of performing SGWB analyses with increasingly realistic noise models and of continuing to develop robust frameworks in which signal and instrumental noise are inferred jointly.