Transdimensional Inference for Gravitational-wave Astronomy with Bilby - Hui Tong; Nir Guttman; Teagan A. Clarke; Paul D. Lasky; Eric Thrane; Ethan Payne; Rowina Nathan; Ben Farr; Maya Fishbach; Gregory Ashton; Valentina Di Marco (The Astrophysical Journal Supplement Series)
It has become increasingly useful to answer questions in gravitational-wave astronomy using transdimensional models, where the number of free parameters can be varied depending on the complexity required to fit the data. Given the growing interest in transdimensional inference, we introduce a new package for the Bayesian inference Library ( Bilby ), called tBilby . The tBilby package allows users to set up transdimensional inference calculations using the existing Bilby architecture with off-the-shelf nested samplers and/or Markov Chain Monte Carlo algorithms. Transdimensional models are particularly helpful when seeking to test theoretically uncertain predictions described by phenomenological models. For example, bursts of gravitational waves can be modeled using a superposition of N wavelets, where N is itself a free parameter. Short pulses are modeled with small values of N , whereas longer, more complicated signals are represented with a large number of wavelets stitched together. Other transdimensional models have been used to describe instrumental noise and the population properties of gravitational-wave sources. We provide a few demonstrations of tBilby , including fitting the gravitational-wave signal GW150914 with a superposition of N sine-Gaussian wavelets. We outline our plans to further develop the tBilby code suite for a broader range of transdimensional problems.