Thesis
Viability of constraining the neutron star equation of state through the tidal effects of black hole-neutron star mergers
Washington State University
Master of Science (MS), Washington State University
2018
Handle:
https://hdl.handle.net/2376/100838
Abstract
Observing gravitational waves from black hole-neutron star mergers can provide insight about the densest known matter in the universe. The neutron star structure is determined by its equation of state, which directly impacts the tidal deformability. Since tidal interactions are imprinted in the gravitational wave signal, we can utilize the tidal deformability as a proxy for constraining the neutron star equation of state. We examine constant tidal deformability curves along the parameter space of a piecewise polytropic neutron star equation of state family to study the variations of any additional equation of state dependent parameters. We find that softer equations of state lead to broader variations in the binding energy. Additionally, we utilize the numerical relativity code SpEC to perform multiple black hole - neutron star simulations. We hybridize the resultant waveforms with tidally corrected SpinTaylor-T4 post-Newtonian inspiral waveforms, and carry out comparison studies with two template waveform families LEA, and LEA+ to estimate the binary parameters including the tidal deformability. This results in obtaining reasonable parameter estimates for binary masses and BH, but only reasonable tidal deformability estimates for systems with low mass ratios and high black hole spin.
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Details
- Title
- Viability of constraining the neutron star equation of state through the tidal effects of black hole-neutron star mergers
- Creators
- Jesus Mireless Caro
- Contributors
- Matthew D. Duez (Degree Supervisor)
- Awarding Institution
- Washington State University
- Academic Unit
- Physics and Astronomy, Department of
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Publisher
- Washington State University; [Pullman, Washington] :
- Identifiers
- 99900525300201842
- Language
- English
- Resource Type
- Thesis