Parameter Estimation Bias From Overlapping Binary Black Hole Events In Second Generation Interferometers

TL;DR

This paper investigates the impact of overlapping binary black hole signals on parameter estimation in next-generation gravitational wave detectors, revealing conditions under which biases occur and how signals can be distinguished.

Contribution

It provides an analysis of parameter estimation biases caused by overlapping events in future detectors and identifies conditions for accurate separation of signals.

Findings

Current techniques can distinguish signals separated by ~0.1 seconds with uneven SNR ratios.

Highly overlapping signals can lead to biased parameter estimates and apparent precession.

Bias can occur even when one signal is below the detection threshold.

Abstract

Since the initial detection of Gravitational Waves in 2015, 50 candidate events have been reported by the LIGO-Virgo-KAGRA collaboration. As the current generation of detectors move towards their design sensitivity the rate of these detections will increase. The next generation of detectors are likely to have high enough sensitivities that multiple merging binaries will be visible at the same time. In this paper we show that this is likely to happen before the end of the decade, with the move to the LIGO-Voyager detector. We investigate the situation of overlapping Binary-Black-Hole mergers in these detectors. We find that current parameter estimation techniques are capable of distinguishing the louder of two merging BBH events, without significant bias, when their merger times are not less than $\sim0.1$ seconds apart and when the ratio of the signal-to-noise ratios of the systems is uneven. This region of overlapping parameter space is dependent upon the sky locations of the signals and the relation of those locations to the light travel time between detectors. We also find that, if two signals are highly overlapping, then the recovered set of parameters often show strong evidence of precession. Finally we show that bias can occur even when the signal causing the bias is below the detection threshold.