Bayesian inference on gravitational waves -- The maths, the computation, and examples.

(Christian Roever)


Observatories are being set up around the world in order to detect gravitational 
radiation. Gravitational waves are predicted by general relativity theory, and 
their measurement would not only confirm general relativity, but also open a new 
window for interesting observations. Valuable information will be encoded in 
gravitational waves, about the processes generating them, or about cosmology in 
general.
In this talk I will present my work on a Bayesian analysis framework for a 
particular kind of signal, emitted by a pair of inspiralling stars or black 
holes. This includes the model setup, and the computational methods employed for 
the practical analysis. Over the course of this work, interesting insights were 
gained into the proper setup of the (parallel tempering) MCMC algorithm, and the 
original model was generalised to include the noise spectrum as an unknown, 
allowing to estimate it 'on the fly'.