UMD Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/3

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.

More information is available at Theses and Dissertations at University of Maryland Libraries.

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    Improving analytical templates and searching for gravitational waves from coalescing black hole binaries
    (2010) Ochsner, Evan Lee; Buonanno, Alessandra; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The Laser Interferometer Gravitational-wave Observatory (LIGO) and Virgo are taking data at design sensitivity. They will be upgraded to Advanced LIGO and Virgo within the next 5 years and the detection of gravitational waves will be very likely. Binaries of two compact objects which inspiral and coalesce are one of the most promising sources for LIGO and Virgo. Most searches have focused solely on the inspiral portion of the waveform, and are consequently limited to low total mass. Recent breakthroughs in numerical relativity allow one to construct complete inspiral-merger-ringdown waveforms and search for the whole signal. This thesis will review some of the basic characteristics of gravitational waves from compact binaries and methods of searching for them. Analytical template waveforms for such systems will be presented including a comparison of different families of analytical waveforms, a study on the inclusion of spin effects in such waveforms, and a study of inspiral-merger-ringdown waveforms with amplitude corrections and the importance of these effects for parameter estimation. The thesis will culminate with a presentation of the first gravitational wave search to use inspiral-merger-ringdown templates, which was performed on data from the fifth science run of LIGO.