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L. S. Finn (Center for Gravitational Physics and Geometry/Penn State)
LIGO --- The Laser Interferometer Gravitational-Wave Observatory --- is one of several large projects being undertaken worldwide to detect gravitational radiation. The LIGO detector output is a time series, consisting of a linear superposition of a noise component and, occasionally, a weak signal. The target sources are heterogenous: while most likely signal sources are cataclysmic, cosmological events (e.g., supernovae, compact binary mergers, black hole formation), these detectors will also be sensitive to weak continuous wave sources (e.g., radiation from rapidly rotating neutron stars) or a stochastic gravitational wave signal (arising principally from the confusion limited superposition of many weak and distant sources). In some cases the detailed time structure of the signal is known; however, in most cases it is not. The detector noise component will also include a number of instrumental and environmental artifacts, some of which we will have to identify and classify statistically.
The challenges of LIGO data analysis are thus those of time series analysis in the low signal-to-noise limit with rare, non-repeating signals. While the first analyses will focus on setting upper limits on event rate and signal amplitudes, the data will all be processed in real-time searching for the rare, strong event. In this talk I will discuss the data analysis problem, both for science analysis and for detector characterization.
The author(s) of this abstract have provided an email address for comments about the abstract: LSF5@PSU.Edu