Thesis (Ph. D.)--University of Washington, 2000. / Vita. Includes bibliographical references (p. 243-256).

Thesis (Ph. D.)--University of Hawaii at Manoa, 2004. / Includes bibliographical references. / Also available by subscription via World Wide Web / xxxiii, 335 leaves, bound ill. 29 cm

Thesis (Ph. D.)--University of Hawaii at Manoa, 2004. / Includes bibliographical references.

The goal of this study was to obtain photometry of three poorly studied close binary star systems. These observations were obtained at Lowell Observatory in Flagstaff, Arizona and the Ball State University Observatory. In both cases charged coupled device detectors were used. Light variations were detected in all three stars. For one of the binaries the temperatures of the component stars were found by fitting multi-color light curves with black body models. In addition, the temperature difference between the two hemispheres of the secondary star was found. This difference is believed to be the product of heating by the stellar companion. / Department of Physics and Astronomy

Rotational phase mapping of brown dwarfs allows exploration of different cloud and photospheric properties within the same atmospheres, allowing a separation of these parameters from global parameters, such as composition, surface gravity, and age. This work presents an in-depth characterization of high SNR light curves from the Spitzer Space Telescope with up to 13 hours of continuous monitoring of four dwarfs spanning the L3 to L8 spectral type. An exhaustive exploration of currently available state-of-the-art models explains the observed color changes for two of these dwarfs with a linear combination of two model cloudy surfaces differing in effective temperature, cloud opacity and vertical mixing. Using state-of-the-art purely radiative convective atmospheric models, we calculate basic radiative timescales for temperature perturbations in the atmosphere, and consider the effects of dynamics on these timescales. Along with dynamical atmospheric advection timescales, we discuss the relationships between model timescales and the observed light curve evolution.

Exomoons remain amongst the most elusive targets in observational astronomy. Nevertheless, these worlds stand to provide an unprecedented window into the formation and evolution of planetary systems. If the Solar System is any guide, we can expect exomoons will be geologically active and diverse, with the potential for hosting volatiles, atmospheres, and even life. Moreover, a thorough understanding of the population and occurrence rates of exomoons will help to place our own Solar System in a galactic context, speaking to the commonality of our own history. And though there are a variety of known pathways for moon formation, the discovery of exomoons may yet reveal heretofore unanticipated system architectures and defy easy explanation, thereby enriching our theoretical understanding of system formation. In this Dissertation I present a population study of exomoons in the Kepler data, finding an apparent dearth of Galilean-analog satellites orbiting planets between 0.1 and 1 AU. I then present evidence for a large exomoon orbiting Kepler-1625b -- potentially the first ever discovery of a transiting exomoon -- as suggested by a joint analysis of Kepler and Hubble Space Telescope data. The following chapter further investigates a number of alternative hypotheses relating to the candidate moon, though the conclusion that an exomoon best explains the data in hand remains unchanged. Finally, I present the results of an effort to identify candidate exomoon signals in the Kepler data by developing a convolutional neural network trained on O(10⁵) Kepler light curves injected with simulated planet and moon transit signals. The most promising exomoon candidates identified by the neural network are examined in detail, undergoing a full photodynamical model fit and Bayesian model selection. I conclude by discussing the outlook for the moon search, highlighting strategies for future work and myriad unanswered questions that should be pursued in the coming years.

In this investigation of near-contact binary stars, the author fit a synthetic light, computer generated, curve model to observations by adjusting various parameters of two near-contact binary pairs, CN Andromeda and TZ Draconis. By fitting asymmetries in the light curves using spotting parameters, the spotting activity for both stars can be determined. From the spotting parameters it is possible to compare the spotting activity of these two near-contact binaries to the spotting activity of 47 contact binaries (Csizmadia et al., 2004). The author determined that, for both TZ Dra and CN And, spots are located at positions that were previously not seen in other observations of contact binaries (Hill, 2007). / Department of Physics and Astronomy

In this Thesis, I explore transiting exoplanets: what we can learn from modeling their light curves, and what we can learn from their arrangement in planetary systems. I begin in Chapter 1 by briefly reviewing the history of transit modeling, from the earliest theoretical models of eclipsing binary stars to the models in current widespread use to model exoplanet transits. In Chapter 2, I model the transits of a sample of Kepler exoplanets with strong prior eccentricity constraints in order to derive correspondingly strong constraints on the density of their host stars, and find that the density constraints I derive are as precise as density constraints from asteroseismology if the transits are observed at high signal-to-noise. In Chapter 3, I apply the same methodology in reverse: using prior knowledge of the stellar density based on Gaia parallax measurements, I model the transits of twelve singly-transiting planets observed by K2 and derive constraints on their periods. In Chapter 4, I consider the general problem of deducing the shape of a transiting object from its light curve alone, which I term ``shadow imaging;'' I explore the mathematical degeneracies of the problem and construct shadow images to explain Dips 5 and 8 of Boyajian's Star. I next turn to multi-planet systems: in Chapter 5, I investigate the underlying multiplicity distribution of planetary systems orbiting FGK dwarfs observed by Kepler. I find that we can explain the multiplicities of these systems with a single Zipfian multiplicity distribution, without invoking a dichotomous population. In Chapter 6, I consider the arrangement of planets in those systems, and use neural networks inspired by models used for part-of-speech tagging in computational linguistics to model the relationship between exoplanets and their surrounding "context," i.e. their host star and sibling planets. I find that our trained regression model is able to predict the period and radius of an exoplanet to a factor of two better than a naive model which only takes into account basic dynamical stability. I also find that our trained classification model identifies consistent classes of planets in the period-radius plane, and that it is rare for multi-planet systems to contain a neighboring pair of planets from non-contiguous classes. In Chapter 7, I summarize these results and briefly discuss avenues for future work, including the application of our methods to planets and planetary systems discovered by TESS.

The quality and quantity of polarimetric data being collected for stellar sources creates new opportunities for studying stellar properties and evolution, and also leads to new challenges for modeling and interpreting such data. Inspired by fresh prospects for detecting the Hanle effect to study photospheric magnetic fields, we have focused attention on purely geometrical aspects for polarimetric variability in the example of oblique magnetic rotators. In the case of axisymmetric fields, we highlight two key facts: (a) polarimetric lightcurves necessarily exhibit a certain time symmetry with rotation phase, and (b) variations in the polarization position angle can be modeled based on geometrical projection effects, independent of the photospheric magnetic field. These conclusions also have general applicability, such as to Thomson scattering and the transverse Zeeman effect. The authors gratefully acknowledge that funding for this work was provided by the National Science Foundation, grant AST-0807664.

A light curve is a plot of brightness versus time of an object. Light curves are dependent on orbit, attitude, surface area, size, and shape of the observed object. Using light curve data, several analysis methods have been developed to derive these parameters. These parameters can be used for tracking orbital debris, monitoring satellite health, and determining the mission of an unknown spacecraft. This paper discusses the development, verification, and utilization of a tool that simulates light curve data. This tool models ground-based observations, space-based observations, self-shadowing geometry, tumbling debris, and controlled spacecraft. The main output from the tool is the pass prediction plot and the light curve plot. The author intends to publish the tool and supporting documents for future researchers to utilize. This will save researchers time developing their own models and the tool can act as a baseline for comparisons between analysis methods. For clarity, this paper does not develop nor implement a light curve analysis method, but rather creates a tool to simulate light curve observations and data. Each section of the tool was verified independently to ensure that the simulated light curves were correct. The tool was verified with STK, matlab, and simulink. It predicts the start and end times of passes, eclipses, and ground-site night cycles within 1% of the total event duration, when compared to STK. The attitude propagator predicts the attitude of the target with offsets less than 0.06 degrees on average and a maximum offset less than 0.6 degrees when compared to provided attitude code.