LIGO Document P1800233-v2
- This thesis explores multiple aspects of some of the noise sources and discusses various strategies to minimize their effect on both the day-to-day detector operation as well as on GW strain data. This involves designing & placement of optimal sensor arrays for NN cancellation, development of early earthquake warning systems based on accurate ground motion prediction and techniques for system identification using static and adaptive filters. We also look into non-astrophysical transients or glitches which trigger false alarms in various data analysis pipelines lowering the significance of true detections. In this thesis, we access the impact of such transients on the detector, use automated techniques to classify them, obtain their relative distribution in strain & auxiliary channels and probe the reason of origin for some of those glitch classes. Finally we describe the various machine learning tools that were developed to aid detector characterization and commissioning efforts at the sites.
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