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The Kilonovae at the End of the Binary Neutron Star Merger: A Multi-Messenger Bayesian Analysis of Fitting Formulae using Gravitational Waves

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dc.contributor.advisorBiscoveanu, Sylvia
dc.contributor.authorSzemraj, Lillie A.
dc.date.accessioned2026-07-08T15:14:49Z
dc.date.available2026-07-08T15:14:49Z
dc.date.issued2026-04-27
dc.description.abstractSince their first detection in 2015 by the LIGO, gravitational waves have revolutionized our understanding of compact objects. These dense stellar remnants such as neutron stars and black holes merge to generate gravitational waves. The merger of BNS can be accompanied by an electromagnetic signature of thermal emission called a "kilonova" at optical, near-infrared, and ultraviolet wavelengths. The BNS merger GW170817 led to the first detection of gravitational waves with electromagnetic radiation and the first confident detection of a kilonova. To date, only one multi-messenger BBH merger has been definitively detected. This contributes to large uncertainties in the relationship between binary parameters and properties of their kilonova counterparts, which are typically parameterized via fitting formulae. We attempt to place direct, data-driven constraints on the coefficients within the fitting formula through Bayesian analysis. We apply our framework to simulated BNS gravitational wave signals and their counterparts with a known model to place an independent constraint on the mapping between BNS parameters and kilonova properties. The constraint and this framework will demonstrate what will be possible with a population of many detected BNS mergers and counterparts in upcoming observing runs, given improved sensitivity.
dc.identifier.urihttps://theses-dissertations.princeton.edu/handle/88435/dsp01qv33s1133
dc.language.isoen_US
dc.titleThe Kilonovae at the End of the Binary Neutron Star Merger: A Multi-Messenger Bayesian Analysis of Fitting Formulae using Gravitational Waves
dc.typePrinceton University Senior Theses
dspace.entity.typePublication
dspace.workflow.startDateTime2026-04-28T03:55:28.672Z
pu.contributor.authorid920352382
pu.date.classyear2026
pu.departmentAstrophysical Sciences
pu.minorComputer Science

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