Likelihood for a Network of Gravitational-Wave Detectors with Correlated Noise

TL;DR

This paper develops a statistical likelihood framework for gravitational-wave detector networks that accounts for correlated noise, demonstrating its importance for accurate parameter estimation in future detectors like the Einstein Telescope.

Contribution

It introduces a new likelihood formulation incorporating correlated noise, highlighting its impact on parameter estimation accuracy for gravitational-wave events.

Findings

Neglecting correlated noise reduces chirp mass estimation accuracy

Proper noise modeling is critical for Einstein Telescope data analysis

Correlated noise can significantly affect gravitational-wave parameter inference

Abstract

The Einstein Telescope faces a critical data analysis challenge with correlated noise, often overlooked in current parameter estimation analyses. We address this issue by presenting the statistical formulation of the likelihood that includes correlated noise for the Einstein Telescope or any detector network. By considering varying degrees of correlation, we probe the impact of noise correlations on the parameter estimation analysis of a GW150914-like event. We show that neglecting these correlations may significantly reduce the accuracy of the chirp mass reconstruction. This emphasizes how critical a proper treatment of correlated noise is, as presented in this work, to unlocking the wealth of results promised by the Einstein Telescope.