Parameter estimation of compact binaries

The estimation of parameter values and associated waveforms of observed compact-binary coalescences (CBCs) is an important contribution to the science case of GW detectors. It is key to tests of general relativity, to many cosmological studies, to population studies of compact objects, to studies of gravitational lensing of gravitational waves, and of course, to the exploration of the nature and properties of the objects involved in the merger.

One of the libraries used for CBC parameter estimation is Bilby [Ashton et al (2019)]. It is written in Python, and its main function is to provide tools for Bayesian inference. It uses the waveform models defined in the LALSimulation package [LALSimulation]. We have used Bilby for the simulation of third-generation detector networks and parameter estimation by posterior sampling for the investigation of a CBC foreground reduction as described in the Cosmology page.

Another popular analysis framework is based on Fisher matrices, which can be used to calculate Gaussian estimation errors, i.e., it is based on an approximation of the likelihood function as a Gaussian distribution. The advantage is significantly faster computations compared to posterior or likelihood sampling. This framework was developed in a time-domain simulation of GW data for future detector networks to investigate their capabilities to estimate intrinsic and extrinsic source parameters [Grimm / Harms (2020)].

[Maggiore et al (2020)]