LIGO Seminar

Searches for transient gravitational waves are typically thought of as two

distinct classes: "un-modeled" burst searches and template based searches.

But these are just two extremes in a continuum of possibilities that depend

on the strength of our prior knowledge signal. I will describe the BayesWave

algorithm, which is a flexible approach to gravitational wave data analysis

that is able to span the full continuum of models. I will then explain how a

model of the time-frequency evolution of a binary system can be used as a

parameterized signal prior that allows us to detect binary black hole

mergers and extract physical properties such as the masses and spins without

the need for waveform templates.

We plan to broadcast this talk using SeeVogh.