Skip navigation
Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01bn999975v
Title: Simulation Analysis of High-Mass X-Ray Binaries as Merging Binary Black Hole Progenitors
Authors: Liotine, Camille
Advisors: Bahcall, Neta
Department: Astrophysical Sciences
Certificate Program: Applications of Computing Program
Class Year: 2020
Abstract: Binary black holes (BBHs) as observed by the Laser Interferometer Gravitational–Wave Observatory (LIGO) and the Virgo Interferometer are thought to experience a high mass x–ray binary (HMXB) phase. However, at most 3 HMXBs observed in x–ray are predicted to be LIGO–Virgo BBH progenitors, and there are uncertainties regarding these predictions. The lack of x–ray observations of these progenitors raises the question of whether we expect to see such systems in standard models of stellar evolution. It also opens the possibility that we can constrain uncertainties in binary evolution through the absence of HMXB detections and determine if these systems could be targets for future x–ray surveys. We use the COSMIC population synthesis code to simulate a large population of double compact object systems at 1/10 Z _{\odot}, and find that 99.98% of LIGO–Virgo BBH progenitors achieve HMXB luminosities above the 10^{35} erg s^{−1} observable threshold. Most of these binaries emit above this threshold for 0.5-2.0 Myr, and their luminosities exceed 10^{37} erg s^{−1} for a majority of that time. We identify clear correlations between the peak luminosity, duration of observable emission, system mass, and binary separation for LIGO–Virgo BBH progenitors. Finally, we calculate that, at low metallicity, 41.8% of observable HMXBs will become LIGO–Virgo BBHs.
URI: http://arks.princeton.edu/ark:/88435/dsp01bn999975v
Type of Material: Princeton University Senior Theses
Language: en
Appears in Collections:Astrophysical Sciences, 1990-2020

Files in This Item:
File Description SizeFormat 
LIOTINE-CAMILLE-THESIS.pdf715 kBAdobe PDF    Request a copy


Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.