Global analysis for space-based gravitational wave observatories

Abstract

The Laser Interferometer Space Antenna (LISA) is a space-based gravitational wave detector in development under a joint venture between ESA and NASA. LISA will be sensitive to a wealth of signals from a variety of sources--both astrophysical and instrumental. Since many of these signals will be overlapping we must carry out a global analysis where we model everything believed to be present in the data simultaneously. To analyze the data this way we must understand what types of signals we expect, develop fast signal generators, and develop data analysis algorithms to handle this problem. We must also be flexible to characterize signals that we do not expect such as instrumental glitches of unknown morphology, or exotic astrophysical sources. We employ the Markov Chain Monte Carlo algorithm to address these multiple facets of the global analysis problem through a Bayesian approach. We have developed fast models for a variety of sources, characterized what we can learn about the sources, and assessed the nature of LISA's global analysis problem.