Merger-Ringdown Consistency: A New Test of Strong Gravity using Deep Learning (2101.07817v4)

Abstract: The gravitational waves emitted during the coalescence of binary black holes are an excellent probe to test the behaviour of strong gravity. In this paper, we propose a new test called the merger-ringdown consistency test that focuses on probing the imprints of the dynamics in strong-gravity around the black-holes during the plunge-merger and ringdown phase. Furthermore, we present a scheme that allows us to efficiently combine information across multiple ringdown observations to perform a statistical null test of GR using the detected BH population. We present a proof-of-concept study for this test using simulated binary black hole ringdowns embedded in the next-generation ground-based detector noise. We demonstrate the feasibility of our test using a deep learning framework, setting a precedence for performing precision tests of gravity with neural networks.