Abstract

The extreme environment within neutron stars presents the opportunity to probe the nuclear equation of state at high densities and study the nature of stellar remnants near 1 solar mass. Parameter inference for the equation of state has received abundant attention in previous studies, but only a fraction of those have employed nontrivial population models in their priors. In this work, we introduce an upgrade to the generalized version of the popular RIFT algorithm known as HyperPipe, enabling the inclusion of flexible, user-provided priors within preexisting likelihood marginalization scripts that will facilitate joint inference of the equation of state and binary neutron star population hyperparameters. We demonstrate the utility of this pipeline framework with a comprehensive test involving data from double neutron star systems, massive galactic pulsars, isolated X-ray pulsars, and gravitational wave events, utilizing a truncated bivariate normal distribution as our population prior model. We assess the outcome of this inference and provide comparisons with previous results. iii

Publication Date

8-2026

Document Type

Thesis

Student Type

Graduate

Degree Name

Physics (MS)

Department, Program, or Center

Physics and Astronomy, School of

College

College of Science

Advisor

Richard O’Shaughnessy

Advisor/Committee Member

Yosef Zlochower

Advisor/Committee Member

Joshua Faber

Campus

RIT – Main Campus

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