Date of Award

Spring 2024

Project Type

Dissertation

Program or Major

Physics

Degree Name

Doctor of Philosophy

First Advisor

Francois Foucart

Second Advisor

Kai Germaschewski

Third Advisor

Mark McConnell

Abstract

Binary neutron star mergers are some of the most extreme events to happen in our universe. From observations of these mergers, we can obtain information about the properties of matter at densities much larger than those accessible within the solar system, as well on the origin of heavy elements. Studying these events poses challenges, so we use simulations to model the merger. State-of-the-art methods and models still have to make assumptions or simplifications, so new methods improving either the accuracy of the simulations, or reducing the computational cost are desired. My research contains three projects, aiming to improve simulations by approximating magnetohydrodynamical effects via a large-eddy formalism viscosity, testing the accuracy of a new description of dense matter in the neutron stars, and using a Monte-Carlo neutrino transport method.

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