MONDAY, February 4, 2008

Speaker:       Richard Umstaetter (NASA, Jet Propulsion Laboratory)

Title:            Bayesian strategies for gravitational radiation data analysis

Abstract:       Gravitational waves are predicted by general relativity but so far  have not yet been directly observed. Around the world, interferometric          observatories are being set up in order to detect gravitational radiation, among which the Laser Interferometer Gravitational Wave Observatory (LIGO) with the highest sensitivity is hoped to soon detect gravitational waves. Alongside LIGO in the US, other observatories are operating in Italy (VIRGO), Germany (GEO), and Japan (TAMA) and a space based version, the Laser Interferometer Space Antenna (LISA), is scheduled to be launched within the next decade with a much higher sensitivity. Since such observatories are not pointed instruments but all-sky-monitors, the data analysis is based  on time series obtained over the detector's orientation sweep relative to potential cosmological or astrophysical sources, such as inspiralling neutron stars or black holes.

                I will give an overview of my interdisciplinary research within the       Bayesian framework that addresses the simultaneous estimation of parameters and detection probability of a gravitational wave signal emitted by a binary inspiral system by applying Bayesian model selection using the reversible jump Markov chain Monte Carlo (RJMCMC) method. Another application of a more comprehensive Bayesian model selection will be demonstrated by addressing the problem of source confusion in LISA data where an unknown number of densely packed signals need to be identified in number and their individual parameters.