PublisherThe University of Arizona.
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AbstractWould finding exoplanets be more efficient if we had predictions of where they are likely to be in a planetary system? We now understand, at a population level, the physical and orbital parameters of planets in a given exoplanet system and beginning to grasp the intricacies of exoplanet system architectures. By combining models created from this population-leveldata with the specific yet incomplete observations of planetary systems, we developed the first integrative framework able to predict the most likely planet to exist in a given planetary system that has not yet been found, and specifically provide testable hypotheses as to the physical and orbital parameters of the additional predicted planet (Dietrich and Apai, 2020, Chapter 2). We tested this on the TESS multi-planet suite in 2020, and subsequent follow-up observations have confirmed the predictive power, with > 50% of the orbital period predictions and ∼ 75% of the planet radius predictions matching the discovered planets. The manuscript with these results is currently in preparation. In Chapters 3-5 (Dietrich and Apai, 2021; Dietrich et al., 2022; Basant et al., 2022), we used these unique and powerful analyses to predict planets in a range of individual systems. We studied tau Ceti (Chapter 3) to assess a system without any transiting planets, predicting a planet in the habitable zone and supporting the evidence towards the existence of uncertain or controversial planet candidates that have been difficult to confirm with the current set of observations. We assessed in detail the dynamical stability of the high-multiplicity HD 219134 system and the Solar System (Chapter 4), proving that dynamical stability plays an important role in understanding current planetary system architectures and their history. We also tested multiple planet candidate hypotheses for the e Eridani system (Chapter 5) and used a simple atmospheric model and albedo distribution to predict likely surface temperatures, showing that one planet candidate in the system likely has an Earth-likesurface temperature. With more data coming in searching for planets via both broad exoplanet surveys and targeted follow-up observations, we will expand and refine the statistical models to produce more accurate and precise predictions. Surveys like Project EDEN (Chapter 6; Dietrich et al., 2023), for example, help determine how planet formation occurs around different types of host stars, and how the lowest-mass stars may have less planets than slightly more massive stars. Using these predictions and observations, we learn how exoplanet systems form and evolve as a general process, and what makes certain systems unique and why they came to be that way. In the near future, we will contribute to streamlining the search for nearby temperate terrestrial worlds by determining which planetary systems are most likely to contain such a planet, in the hope of someday soon finding a planet harboring extraterrestrial life.
Degree ProgramGraduate College