Neutron Stars: Robust Constraints on Dense Matter from Astrophysics

Citation

Legred, Isaac Norman (2025) Neutron Stars: Robust Constraints on Dense Matter from Astrophysics. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/fzdw-w868. https://resolver.caltech.edu/CaltechTHESIS:06022025-165440282

Abstract

Neutron stars are exceptional astrophysical objects, harboring likely the densest matter in the universe outside of black holes.

However, uncertainty in the properties of matter at the densities achieved inside of neutron stars means that the structure of neutron stars cannot be fully understood from first principles.

Modern statistical and computational tools however, along with cutting-edge observational strategies have enabled the properties of neutron stars to be constrained using astrophysical data.

In this thesis, I will discuss work I have carried out examining what can be learned about neutron stars, and the dense matter inside of them, using electromagnetic and gravitational-wave observations of neutron stars.

In particular, I will discuss constraints on nonparametric models of the dense-matter equation of state, and why nonparametric models are an effective strategy for faithfully representing uncertainty.

I will also discuss the interplay between understanding the astrophysical channels for forming neutron stars, and the neutron-star matter equation of state, including how we can use our understanding of dense matter to classify objects.

Finally, I will discuss some considerations for simulating astrophysical neutron stars, which is necessary in order to interpret the full range of astrophysical observations of merging neutron stars, such as the neutron star merger GW170817.

Thesis Files