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Syracuse University

The detection and parameter estimation of binary black hole mergers

Abstract

dc:description.abstract

<p>In this dissertation we study gravitational-wave data analysis techniques for binary neutron star and black hole mergers. During its first observing run, the Advanced Laser Interferometer Gravitational-wave Observatory (Advanced LIGO) reported the</p> <p>first, direct observations of gravitational waves from two binary black hole mergers. We present the results from the search for binary black hole mergers which unambiguously detected the binary black hole mergers. We determine the effect of calibration</p> <p>errors on the detection statistic of the search. Since the search is not designed to precisely measure the astrophysical parameters of the binary neutron star and black hole mergers, we use Bayesian methods to develop a new parameter estimation analysis.</p> <p>We demonstrate the performance of the analysis on the binary black hole mergers detected during Advanced LIGO’s first observing run. We use the parameter estimation analysis to assess the ability of gravitational-wave observatories to observe a gap</p> <p>in the black hole mass distribution between 52 M and 133 M due to pair-instability supernovae. Finally, we use simulated signals added to the Advanced LIGO detectors to validate the search and parameter estimation analyses used to publish the</p> <p>detection of the astrophysical events.</p>

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy (PhD)
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Physics
Year
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Biwer, Christopher Michael
Contributors dc:contributor
  • Duncan Brown

Subjects

dc:subject × 1

Identifiers

dc:identifier.*
Repository record dc:identifier
https://surface.syr.edu/etd/791
OAI identifier oai:identifier
oai:surface.syr.edu:etd-1792

Chain of custody

source
Harvested from
Syracuse University
Base URL
surface.syr.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Biwer, Christopher Michael. The detection and parameter estimation of binary black hole mergers. Dissertation thesis, 2017. https://surface.syr.edu/etd/791