Semester of Graduation

Summer 2023

Degree

Doctor of Philosophy (PhD)

Department

Physics and Asytonomy

Document Type

Thesis

Abstract

This thesis, titled ``Bridging the Gap Between Detector Characterization and Gravitational Wave Searches in LIGO'', investigates the complex interplay between detector noise, gravitational wave search algorithms in the operation of the Laser Interferometer Gravitational-Wave Observatory (LIGO) detectors. The non-Gaussian behavior of LIGO detectors' data can lead to numerous issues, ranging from causing the detector to lose operational state to misinterpretations of actual gravitational wave signals.

An introduction to the workings of current interferometric gravitational wave detectors and the characterization of their sources and noise is provided. The focus is then shifted to the GstLAL pipeline, its role, and the effects of inherent detector noise on its ability to discover gravitational waves. Our study compared candidates generated by the GstLAL Gravitational Wave search pipeline using simulated gaussian noise, and real data, and found that low to moderate mass regions exhibit the highest deviations in trigger parameters due to non-gaussian detector noise compared to idealized Gaussian data, with the regions searching for Neutron Star - Black Hole mergers contributing the most to the perceived non-Gaussianity of the detector.

Notable modifications to the GstLAL workflow for the 2023 observing period are discussed, specifically changes to the estimation of the $\xi^2$ parameter. By adopting a more robust estimate, we improved the calculation of the final likelihood ranking statistic and enhanced the pipeline sensitivity by 10-20\% across all mass ranges, solely via software modifications.

A significant effort was made to bridge the gap between Detector Characterization (DetChar) and searches for Compact Binary Coalescences (CBC). We analyzed characteristics of GstLAL triggers that were caused by glitches, discovering that certain glitches are more likely to produce highly unexpected triggers. This research underscores the importance of the synergy between DetChar and CBC searches and paves the way for future work on the analysis of trigger patterns pre-clustering to better identify glitches.

Overall, this thesis is an exploration of the challenges and advancements in the field of gravitational wave detection and data analysis, with a particular focus on improving the robustness and sensitivity of the GstLAL pipeline.

Date

7-12-2023

Committee Chair

Gabriela Gonzalez

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