A Study on the Characterization and Implementation of Tools for Advanced LIGO
Published in SMBHC Thesis Repository, 2016
The Laser Interferometer Gravitational Wave Observatory (LIGO) is aimed at directly detecting gravitational waves, small perturbations or ripples in the fabric of space-time. Because of their extreme sensitivity, the LIGO detectors are affected by many sources of non-astrophysical noise. In the first part of this thesis we test a pipeline designed for the identification of short-duration noise transients, called Omicron. We first inject simulated noise waveforms in engineering run data from the LIGO detector in Livingston, Louisiana and then determine Omicron efficiency by attempting to recover these injections. In the second part of this thesis, we present a novel method for the characterization of signals in LIGO data. Using data from LIGO’s sixth science run, we develop an algorithm to classify noise transients by their morphology, as well as other parameters such as signal-to-noise ratio, duration, and bandwidth. Two methods, the Kohonen self organizing feature maps and the discrete wavelet transform coefficients, are used to reduce the multidimensional trigger set into an easily readable two-dimensional format.