Date of Award

Fall 2025

Project Type

Dissertation

Program or Major

Physics

Degree Name

Doctor of Philosophy

First Advisor

Francois Foucart

Second Advisor

David Mattingly

Third Advisor

Elena Long

Abstract

Black hole–neutron star (BHNS) mergers are key sources for multimessenger astrophysics, offering insight into strong-field gravity and the behavior of matter at supranuclear densities. This dissertation presents three independent contributions to the study of BHNS systems using the Spectral Einstein Code (SpEC). First, a set of simulations spanning a range of mass ratios, black hole spins, and neutron star equations of state is used to map disruption thresholds and quantify remnant disk masses, unbound ejecta, and ejecta composition. These results are compared to predictions from remnant mass model FNH18, to assess its reliability in accurately predicting the resulting remnant masses from merger events across astrophysically relevant configurations. Second, gravitational waveforms are extracted at future null infinity and analyzed for numerical convergence, extrapolation uncertainty, and phase accuracy. These high-accuracy waveforms are used to evaluate the performance of existing BHNS-specific and BBH-calibrated models across multiple configurations. While most models exhibit strong agreement with numerical data, deviations near merger motivate targeted refinement. The results provide a benchmark dataset suitable for future surrogate modeling efforts, with the goal of enabling fast and accurate waveform generation for parameter estimation and detection pipelines. Finally, a light automation framework is developed to streamline the setup and evolution of BHNS simulations, enabling efficient parameter space exploration and opening new opportunities for educational and research engagement. Together, these results improve the physical modeling, numerical reliability, and educational accessibility of BHNS merger simulations.

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