Abstract

One of the most extreme objects in the Universe, neutron stars are the remnants of supernova explosions. A usual neutron star has a mass in the range of 0.8 − 2.4M⊙ and a radius of about 10 km. Such small radii and high masses imply extreme densities, that exceed the nuclear density ρnuc . The extreme conditions of cold ultradense matter present inside the neutron star cannot be achieved in terrestrial laboratories, so the equation of state (EOS) of such matter is not well understood. Currently, there are many theoretical models of the EOS based on nuclear physics (Quantum Chromodynamics (QCD), chiral Effective Field Theory (EFT), etc) or on astrophysical observations (pulsar mass measurements, gravitational wave detections, X-ray observations, etc). Based on these models, researchers have described the behavior of binary neutron star mergers, the resulting gravitational wave signals, and the intrinsic parameters (mass, radius, spin, tidal deformability) corresponding to each model. Using the gravitational wave data from LIGO and Virgo, we can infer the EOS of neutron stars by comparing the observed signals with the theoretical models. For this purpose, we use the Rapid parameter inference on gravitational wave sources via Iterative FiTting (RIFT) code. This code utilizes Bayesian statistics to infer the intrinsic parameters of the neutron stars from the observed gravitational wave events. In this work, we expand the RIFT code to perform EOS inference using EOS tables from Legred et al 2021. To implement this feature, we calculate local ordering statistic S (corresponding to the tidal deformability Λ̃ for equal-mass binary) along with other intrinsic parameters at each step of the iterative process. Then, we use this parameter to pinpoint the most probable EOS model for each sample. This results in a posterior distribution of EOS models for the analyzed event which are linked to the tables of Pressure P vs Baryon density ρ and Mass M vs Radius R. Using the posterior samples generated by RIFT, we calculate 90% credible intervals for the P (ρ) and M (R) relations. The benefits of this update to the RIFT code are twofold: it allows fast and reliable EOS inference from GW events and it refines the regular RIFT analysis by ensuring the consistency of the parameter space with realistic EOS models. As a test case for this study, we repeat the analysis of the GW170817 event and compare the results with the previous studies (original LIGO parameter inference 2020 and Legred et. al 2021 EOS inference). We experiment with different approximations (assuming no spin, using high and similar mas ratio test cases) to assess the performance of our method under different conditions. Our results align well with the reference studies and show potential for further studies on other GW events.

Publication Date

7-24-2024

Document Type

Thesis

Student Type

Graduate

Degree Name

Astrophysical Sciences and Technology (MS)

Department, Program, or Center

Physics and Astronomy, School of

College

College of Science

Advisor

Richard O'Shaughnessy

Advisor/Committee Member

Joshua Faber

Advisor/Committee Member

Yosef Zlochower

Campus

RIT – Main Campus

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