Dear Sir/Madam,

The following is the information about my defense.

Title and abstract:  Dynamics and Observational Implication of Close-in Exoplanet

  With more than five thousand exoplanets discovered, it unveiled significantly diverse orbital configurations, contrasting with those in our Solar Systems and confronting classical understanding of planet formation. For instance, the prevalence of observed close-in exoplanets that lie within the orbital of Mercury up to ~0.01 AU brings up questions about their formation, as their current orbits distances can be within or close to the dust sublimation zone. These planets could initially form at a further distance, and then migrate inward. However, why and how the configuration of these close-in systems differs from the Solar System is still puzzling. Investigating their dynamical and physical properties can help us gain deeper insights into the planetary system formation and evolution beyond the Solar System and better understand their habitability. Under this context, this thesis presents the characterization of the dynamics and the identification of the physical properties for close-in systems.

  In the first work, I focused on the dynamics of ultra-short-period planet (USP), which is defined as the planet orbiting its host star shorter than one day. The USP orbits in close proximity to their stars within the sublimation zone. This extreme object typically has a larger period ratio and higher mutual inclination with its outer companion, comparing to other systems without it.

 To characterize the dynamics of USP systems, I utilized secular simulations and developed an analytical method to investigate the mutual inclination evolution of the USP system. The stellar oblateness (J2) plays an important role in the dynamics. It can excite the mutual inclination between planets by precessing their orbital angular momentum at different rates, and it decreases with time due to magnetic braking. Therefore, I focused on the dynamical effects of J2. I successfully identified the formation channel of Kepler-653 system with different initial conditions. The result suggests that either USP planets formed early and needed significant inclinations or they formed late when their host stars rotated slower (smaller J2).

  In the second work, I characterized the physical properties of the close-in planets by employing deep learning techniques to predict the parameters of exoplanets. Most planets are discovered from transit method without the measurement of their masses. However, mass is important to better understand the composition and formation mechanism of planets. One way to determine the mass is through transit timing variation (TTV). The TTV encodes rich dynamical information as it is contributed by perturbations from planets, and provides a powerful method to estimate planetary masses and orbital parameters. The traditional Markov Chain Monte Carlo (MCMC) method incorporates TTV to predict the planetary properties, however, MCMC is computationally expensive, and highly sensitive to the prior distribution. Especially, when the system is with only one planet transit, the properties of non-transit planets are even harder to obtain. Deep learning techniques are able to tackle these challenges. It can predict the exact values of the properties and no need to consider the specific prior distribution. Therefore, I designed a deep learning model to determine the orbital parameters and mass of non-transit planet with transit information as input, focusing on the single transit planetary system. The deep learning model I trained gives an overall fractional error of ~ 1% on the predictions of the testing set. I also utilized the model to make the predictions on the real systems, Kepler-88. This work can contribute to the design of observational missions aiming to search companions of single transiting systems.

Defense Date, time, location: June 19, 2024, 12 pm, Ford ES&T L1114

Names of committee members: Gongjie Li (Advisor), Chunhui Du, James Wray,  Masatoshi Hirabayashi, Molei Tao