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The Dawn of Multi-Messenger Astronomy: Neutron Star Mergers and Gravitational Waves

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Neutron star mergers instigate a wealth of observable astrophysical signals, offering key insights into interdisciplinary questions in stellar astronomy, nuclear physics, cosmology, and atomic physics. The coalescence of neutron stars and/or black holes produces gravitational wave emission, only recently accessible to ground-based laser-interferometric detectors. Additionally, these mergers can incite emission across the electromagnetic spectrum, including short-duration gamma-ray bursts and kilonova emission, where kilonovae are ultraviolet, optical, and infrared transients powered by the radioactive decay of heavy elements following a neutron star merger. In this thesis, I investigate three topics related to the joint detection of gravitational wave and electromagnetic signals from neutron star mergers. Throughout this work, I describe the production of sky localization maps from gravitational-wave detector data, with a focus on sky localization maps for binary neutron star (BNS) and neutron star – black hole (NSBH) binary systems. I present the first systematic study of sky localization for NSBH systems, finding a median sky localization of 60 deg^2 with three advanced ground-based interferometers which is reduced to 19 deg^2 and 11 deg^2 with four and five interferometers, respectively. Additionally, I present a case study in which the estimation of sky localization maps is hindered by the presence of an instrumental noise transient. In this case study, I describe methods of transient removal and verify that this excision process does not bias astrophysical parameter estimates. Lastly, I quantify the ability of 13 wide field-of-view instruments to detect kilonovae following a gravitational wave detection, leveraging a large grid of over 900 radiative transfer simulations. In the process, I provide a framework to infer kilonova ejecta properties following non-detections and explore variation in detectability with these ejecta parameters.

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