Date of Award

Winter 2025

Project Type

Dissertation

Program or Major

Physics

Degree Name

Doctor of Philosophy

First Advisor

Francois Foucart

Second Advisor

Samaya Nissanke

Third Advisor

Chanda Prescod-Weinstein

Abstract

Binary neutron star (BNS) mergers have recently become a tool to study extreme gravity, nucleosynthesis, and the chemical composition of the Universe in a new way. In order to accurately identify electromagnetic signals of neutron star mergers, both in the future and retroactively, better constraints on their merger signatures are required. Specifically, BNS outflow properties (such as the mass and composition) are particularly insightful, as they provide a link between the intrinsic properties (such as the stellar masses and radii) and observables. In this thesis, I put forth multiple ways of classifying uncertainties associated with BNS mass outflow models. First, I performed a comparative study of a suite of outflow models across a common merger parameter space so as to measure their level of agreement, finding that the functional form of the model has a strong impact on the amount of mass predicted, and that their quoted uncertainties are underestimates for regions of the parameter space for which there exist fewer simulations --- namely, very unequal mass ratios, and for extremely compact and extremely diffuse stars. I applied these models to a series of mock multimessenger BNS observations to ascertain whether current outflow models can be employed to constrain the NS equation of state, and found model uncertainties to be a limiting factor. For my next project, I studied how accurately the aforementioned suite of outflow models can be used to extract source properties (namely, the stellar masses and radii) from future electromagnetic observations using an ansatz kilonova light curve model. My Bayesian parameter estimation method demonstrated biases typically of the order of $\sim(0.1-0.2)M_\odot$ in mass and $\sim1$ km in radius, with recovery accuracy loosely correlated with total binary mass. Lastly, I establish a framework for a cross-model study with several kilonova models to identify how assumptions about outflow mass, geometry, and composition impact the recovery of intrinsic and outflow properties.

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