Characterizing Kepler Occurrence Rates Using Approximate Bayesian Computation
Open Access
- Author:
- Hsu, Danley
- Graduate Program:
- Astronomy and Astrophysics
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- February 27, 2020
- Committee Members:
- Eric B Ford, Dissertation Advisor/Co-Advisor
Eric B Ford, Committee Chair/Co-Chair
Jason Thomas Wright, Committee Member
Suvrath Mahadevan, Committee Member
G. Jogesh Babu, Outside Member
Donghui Jeong, Committee Member
Randall Lee Mcentaffer, Program Head/Chair - Keywords:
- planets
exoplanets: statistics
population analysis
planet detection: transits - Abstract:
- The thousands of exoplanets identified over the past decade have enabled the study of exoplanet occurrence rates, which provide an important foundation for the characterization of exoplanets by reporting the average number of planets around stars. Previous occurrence rate studies have not only informed the astronomical community about the distribution of exoplanet characteristics but also provided constraints planet formation theories and design studies for future exoplanet surveys. The occurrence rate research presented in this dissertation improves on previous work by using the latest datasets, a comprehensive model for the detection process, and a Bayesian algorithm novel in the field of exoplanet research. To determine robust planet occurrence rates, I utilize the approximate Bayesian computation (ABC) technique that permits the estimation of model parameter posteriors for problems without an easily defined likelihood. To complement ABC, I use the ExoplanetsSysSim model framework for the hierarchical simulation of planetary systems and develop a forward model for catalogs of exoplanets detected via transits by the space-based Kepler mission. This model incorporates data products released alongside the final Kepler catalog of homogeneously identified exoplanet candidates (Kepler DR25) to translate simulated planetary systems into a catalog of observed exoplanet transit properties. Through verification and validation experiments, I confirm the accuracy of my ABC implementation and characterize the response and efficiency of the algorithm. Following these tests, I apply the full model to estimate occurrence rates over a 2-D orbital period-planet radius grid for two cleaned Kepler target star samples: sun-like (i.e. FGK spectral type) dwarf stars and cool (i.e. M spectral type) dwarf stars. I also estimate robust Earth-size habitable zone occurrence rates by integrating over several long-period, small-radius bins. The estimated occurrence rates confirm the abundance of small-to-intermediate size planets around all stars of the spectral types explored and indicate an elevated occurrence rate for exoplanets around M dwarfs compared to exoplanets around FGK dwarfs at a given orbital period. I conclude with a discussion of model limitations and potential future research, ranging from new exoplanet survey inputs to exploring planetary system architectures.