Anatomy of parameter-estimation biases in overlapping gravitational-wave signals

Abstract

Abstract In future gravitational-wave (GW) detections, a large number of overlapping GW signals will appear in the data stream of detectors. When extracting information from one signal, the presence of other signals can cause large parameter estimation biases. Using the Fisher matrix (FM), we develop a bias analysis procedure to investigate how each parameter of other signals affects the inference biases. Taking two-signal overlapping as an example, we show detailedly and quantitatively that the biases essentially originate from the overlapping of the frequency evolution. Furthermore, we find that the behaviors of the correlation coefficients between the parameters of the two signals are similar to the biases. Both of them can be used as characterization of the influence between signals. We also corroborate the bias results of the FM method with full Bayesian analysis. Our results can provide guidance for the development of new parameter estimation algorithms on overlapping signals, and the analysis methodology has the potential to generalize.