Low-latency detection of gravitational waves for electromagnetic follow-up

[Truncated abstract] Existing ground-based gravitational wave detectors are currently being upgraded to their advanced con guration. When operational, the signi cant increase in sensitivity will likely guarantee detection of gravitational waves. With the imminent detection comes the question of what kind of electromagnetic counterparts gravitational wave sources will have. One example has the coalescence of neutron star binaries as a progenitor of short hard gamma-ray bursts. Observing the rapidly fading electromagnetic counterpart of such sources immediately after coalescence will provide information to verify astrophysical models and give greater insight to these highly energetic events. Observation of the prompt optical and radio emission of gamma ray bursts in real-time will require fast moving ground-based telescopes to respond to triggers generated from gravitational wave detector searches. This thesis describes the design, implementation and testing of a new search algorithm designed to detect the presence of gravitational waves from low-mass binary coalescence in advanced detector data in real-time and with near zero latency. An introduction to the field of gravitational waves is given in the first chapter, and specific gravitational wave data analysis techniques are described in explicit detail in the second. The new algorithm, based on the use of a bank of computationally efficient in nite impulse response lters to search for an approximation of the inspiral phase of the gravitational waveform, is presented in the third and fourth chapters. With a good choice of filter coefficients, the inspiral signals are shown to be approximated to greater than 99%. The method was implemented in LIGO's data analysis software library, and made available to the greater community. The fifth chapter describes a search pipeline based on the new algorithm that was applied to real detector data from LIGO's fth science run, both with and without simulated low-mass binary inspiral signals injected into the data. No significant loss in detection efficiency or parameter estimation using the new algorithm was found when compared to the theoretical limit. The sixth chapter demonstrates the ability of the algorithm to recover signals in real-time and with low-latency by searching for signals in LIGO's second engineering run...