Abstract

Accurate information from gravitational wave signals from coalescing binary neutron stars provides essential input to downstream interpretations, including inference of the neutron star population and equation of state. However, even adopting the currently most accurate and physically motivated models available for parameter estimation (PE) of binary neutron stars(s), these models remain subject to waveform modeling uncertainty: differences between these models may introduce biases in recovered source properties. In this work, we describe injection studies investigating these systematic differences between the two best waveform models available for BNS currently, NRHybSur3dq8Tidal and TEOBResumS. We demonstrate that for BNS sources observable by current second-generation detectors, differences for low-amplitude signals are significant for certain sources. Such mergers not only emit gravitational waves but can also be accompanied by electromagnetic radiation, depending on the nature of the remnant formed from the merger. Hence, rapid identification, characterization, and localization of gravitational waves from such mergers can enable well-informed follow-on multimessenger observations. In this work, we also investigate a small modification to the RIFT parameter inference pipeline to enable extremely low-latency inference, tested here for nonprecessing sources. Gravitational waves from inspiralling neutron stars carry information about matter at extreme gravity and density. The binary neutron star (BNS) event GW170817 provided, for the first time, insight into dense matter through this window. Since then, another BNS (GW190425) and several neutron star-black hole events have been detected, although the tidal measurements were not expected to be well-constrained from them. Collective information regarding the behavior of nuclear matter at extreme densities can be done by performing a joint population inference for the masses, spins, and equation-of-state to enable better understanding. This population inference, in turn, relies on accurate estimates of intrinsic parameters of individual events. In this study, we also investigate how the differences, if any, in parameter inference of BNS events using different waveform models can affect the eventual inference of the nuclear equation-of-state. We use the state-of-the-art model TEOBResumS with IMRPHENOMD NRTIDALV2 as a comparison model.

Publication Date

8-9-2024

Document Type

Dissertation

Student Type

Graduate

Degree Name

Astrophysical Sciences and Technology (Ph.D.)

Department, Program, or Center

Physics and Astronomy, School of

College

College of Science

Advisor

Richard O'Shaughnessy

Advisor/Committee Member

George Thurston

Advisor/Committee Member

Joshua Faber

Campus

RIT – Main Campus

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