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Bilby: A user-friendly Bayesian inference library for gravitational-wave astronomy
Gregory Ashton, Moritz Huebner, Paul D. Lasky +18
Bayesian parameter estimation is fast becoming the language of gravitational-wave astronomy. It is the method by which gravitational-wave data is used to infer the sources' astroph…
An introduction to Bayesian inference in gravitational-wave astronomy: parameter estimation, model selection, and hierarchical models
Eric Thrane, Colm Talbot
This is an introduction to Bayesian inference with a focus on hierarchical models and hyper-parameters. We write primarily for an audience of Bayesian novices, but we hope to provi…
Gravitational-wave memory: waveforms and phenomenology
Colm Talbot, Eric Thrane, Paul D. Lasky +1
The non-linear gravitational-wave memory effect is a prediction of general relativity in which test masses are permanently displaced by gravitational radiation. We implement a meth…
Measuring the binary black hole mass spectrum with an astrophysically motivated parameterization
Colm Talbot, Eric Thrane
Gravitational-wave detections have revealed a previously unknown population of stellar mass black holes with masses above . These observations provide a new way to…