# Testing general relativity using gravitational wave signals from the inspiral, merger and ringdown of binary black holes

## TL;DR

This paper explores how gravitational wave observations from binary black hole mergers can be used to test general relativity, especially by combining multiple modest SNR events to detect potential deviations.

## Contribution

It introduces a method to combine data from many low SNR gravitational wave events to improve constraints on deviations from general relativity.

## Key findings

- Combining multiple events enhances sensitivity to deviations from GR.
- The method can identify certain types of deviations if present in the waveforms.
- The robustness of the test is confirmed against analysis parameter variations.

## Abstract

Advanced LIGO's recent observations of gravitational waves (GWs) from merging binary black holes have opened up a unique laboratory to test general relativity (GR) in the highly relativistic regime. One of the tests used to establish the consistency of the first LIGO event with a binary black hole merger predicted by GR was the inspiral-merger-ringdown consistency test. This involves inferring the mass and spin of the remnant black hole from the inspiral (low-frequency) part of the observed signal and checking for the consistency of the inferred parameters with the same estimated from the post-inspiral (high-frequency) part of the signal. Based on the observed rate of binary black hole mergers, we expect the advanced GW observatories to observe hundreds of binary black hole mergers every year when operating at their design sensitivities, most of them with modest signal to noise ratios (SNRs). Anticipating such observations, this paper shows how constraints from a large number of events with modest SNRs can be combined to produce strong constraints on deviations from GR. Using kludge modified GR waveforms, we demonstrate how this test could identify certain types of deviations from GR if such deviations are present in the signal waveforms. We also study the robustness of this test against reasonable variations of a variety of different analysis parameters.