Date of Award
5-2023
Degree Type
Thesis
Degree Name
Master of Science - Natural Sciences
Department
College of Science and Mathematics
First Advisor
Carl Ziegler, Ph.D.
Second Advisor
Hector Ochoa, Ph.D.
Third Advisor
Joseph Musser, Ph.D.
Fourth Advisor
Keith Hubbard, Ph.D.
Abstract
Exoplanets represent a young, rapidly advancing subfield of astrophysics where much is still unknown. It is therefore important to analyze trends among their parameters to learn more about these systems. More complexity is added to these systems with the presence of additional stellar companions. To study these complex systems, one can employ programming languages such as Python to parse databases such as those constructed by TESS and Gaia to bridge the gap between exoplanets and stellar companions. Data can then be analyzed for trends in these multi-star exoplanet systems and in juxtaposition to their single-star counterparts. This research was able to automate the data collection process and the findings generally concluded that most multi-star systems host stars similar in size to the sun that are cooler, less luminous and will therefore have a longer lifetime. In comparison to single star systems, more complex systems were observed to have slightly larger orbital periods, yet smaller planet radii and mass.
Repository Citation
Bailey, Katie E., "Identifying and Analyzing Multi-Star Systems Among TESS Planetary Candidates Using Gaia" (2023). Electronic Theses and Dissertations. 490.
https://scholarworks.sfasu.edu/etds/490
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Included in
Other Astrophysics and Astronomy Commons, Programming Languages and Compilers Commons, Stars, Interstellar Medium and the Galaxy Commons, Statistics and Probability Commons
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