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Detectability of dense-environment effects on black-hole mergers: The scalar field case, higher-order ringdown modes, and parameter biases

Samson H. W. Leong, J. Calderón Bustillo, Miguel Gracia-Linares, Pablo Laguna

2023Physical review. D/Physical review. D.16 citationsDOI

Abstract

Dense environments hosting compact binary mergers can leave an imprint on the gravitational-wave emission which, in turn, can be used to identify the characteristics of the environment. To demonstrate such a scenario, we consider a simple setup of binary black holes with an environment consisting of a scalar-field bubble. We use this as a proxy for more realistic environments and as an example of the simplest physics beyond the standard model. We perform Bayesian inference on the numerical relativity waveforms using state-of-the-art waveform templates for black-hole mergers. In particular, we perform parameter estimation and model selection on signals from black-hole mergers with different mass ratio, total mass, and loudness, hosted by scalar-field bubbles of varying field amplitude. We find that subdominant gravitational-wave modes emitted during the coalescence and ringdown are key to identifying environmental effects. In particular, we find that for face-on signals dominated by the quadrupole mode, the environment is only detectable if both the ringdown and the late inspiral/early merger fall in the detector band; thus, inconsistencies can be found between the inferred binary parameters and those of the final black hole. For edge-on mergers we find that the environment can be detected even if only the ringdown is in band, thanks to the information encoded in the quasinormal mode structure of the final black hole.

Topics & Concepts

PhysicsGravitational waveBinary black holeBlack hole (networking)Mass ratioQuasinormal modeScalar fieldAmplitudeBinary numberComputational physicsQuadrupoleScalar (mathematics)Numerical relativityAstrophysicsClassical mechanicsQuantum mechanicsComputer scienceMathematicsRouting protocolRouting (electronic design automation)ArithmeticComputer networkLink-state routing protocolGeometryPulsars and Gravitational Waves ResearchAstrophysical Phenomena and ObservationsModel Reduction and Neural Networks