PhD Defense by Deborah Lynn Ferguson

*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************

Event Details
  • Date/Time:
    • Tuesday October 13, 2020 - Wednesday October 14, 2020
      3:00 pm - 4:59 pm
  • Location: REMOTE: BLUE JEANS
  • Phone:
  • URL: BlueJeans Link
  • Email:
  • Fee(s):
    N/A
  • Extras:
Contact
No contact information submitted.
Summaries

Summary Sentence: Strong-Field Numerical Relativity in the Era of Gravitational Wave Astronomy

Full Summary: No summary paragraph submitted.

Name:

Deborah Lynn Ferguson

 

Advisor:

Professor Deirdre Shoemaker

 

Date and Time:

Tuesday, October 13, 2020 at 3 p.m. Eastern 

 

BlueJeans Link:

https://bluejeans.com/547346190 

 

Thesis Title:

Strong-Field Numerical Relativity in the Era of Gravitational Wave Astronomy  

 

Committee Members:

Prof. Deirdre Shoemaker - School of Physics, Georgia Institute of Technology (advisor)

Prof. Tamara Bogdanovic ́ - School of Physics, Georgia Institute of Technology
Prof. Laura Cadonati - School of Physics, Georgia Institute of Technology
Prof. Pablo Laguna - Department of Physics, University of Texas at Austin

Prof. John Wise - School of Physics, Georgia Institute of Technology

 

Abstract:

The success of numerical relativity and gravitational wave detectors have paired to provide us with the opportunity to study Einstein’s theory of general relativity in the strongest gravitational regimes. With future detectors coming online with higher sensitivities, numerical relativity will need to continue to improve alongside the detectors. This dissertation addresses how numerical relativity can be used and improved to obtain the most scientific return from each gravitational wave observation. I first develop a new technique to use numerical relativity to better characterize the signals from current generation detectors by predicting the spin of the remnant black hole using only the information available from the gravitational wave during merger, the loudest part of a binary black hole coalescence. This gives a way of more accurately characterizing the remnant black hole when very little inspiral is observed, and provides a new general relativity consistency test using the remnant spin determined from each stage of the coalescence. I then shift my focus towards preparing numerical relativity to detect and understand signals from next generation gravitational wave detectors which will be much more sensitive with unique data analysis challenges. In order to produce waveform templates which are indistinguishable from true signals, numerical relativity simulations will need to be sufficiently well resolved. I construct a method to determine the necessary resolution of numerical relativity simulations as a function of signal-to-noise ratio. To accurately characterize gravitational wave signals, it is also crucial that the parameter space of binary black hole systems be densely populated with simulations. However, due to the high computational cost of numerical relativity, these simulations need to be chosen carefully. I develop methods to decrease the effective parameter space and to identify the optimal parameters for new simulations. The methods and techniques presented here help to maximize the scientific gain from each gravitational wave detection, for both present and future detectors.

Additional Information

In Campus Calendar
No
Groups

Graduate Studies

Invited Audience
Faculty/Staff, Public, Graduate students, Undergraduate students
Categories
Other/Miscellaneous
Keywords
Phd Defense
Status
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: Sep 29, 2020 - 10:06am
  • Last Updated: Sep 29, 2020 - 10:06am