With the ability to observe the atmospheres of terrestrial exoplanets via transit spectroscopy on the near-term horizon, the possibility of atmospheric biosignatures has received considerable attention in astrobiology. While traditionally exoplanet scientists looking for life focused on biologically relevant trace gases such as O2 and CH4, this approach has raised the spectre of false positives. Therefore, to address these shortcomings, a new set of methods is required to provide higher confidence in life detection. One possible approach is measuring the topology of atmospheric chemical reaction networks (CRNs). To investigate and assess this approach, the ability of network-theoretic metrics to distinguish the distance from thermochemical equilibrium in the atmosphere of hot jupiters was tested. After modeling the atmospheres of hot jupiters over a range of initial conditions using the VULCAN modeling package, atmospheric CRNs were constructed from the converged models and their topology measured using the Python package NetworkX. I found that network metrics were able to predict the distance from thermochemical equilibrium better than atmospheric species abundances alone. Building on this success, I modeled 30,000 terrestrial worlds. These models divided into two categories: Anoxic Archean Earth-like planets that varied in terms of CH4 surface flux (modeled as either biotic or abiotic in origin), and modern Earth-like planets with and without a surface flux of CCl2F2 (to represent the presence of industrial civilizations). I constructed atmospheric CRNs from the converged models, and analyzed their topology. I found that network metrics could distinguish between atmospheres with and without the presence of life or technology. In particular, mean degree and average shortest path length consistently performed better at distinguishing between abiotic and biotic Archean-like atmospheres than CH4 abundance.

Most stars in our galaxy are M–dwarfs, much cooler and smaller than the sun. The ubiquitous nature of these stars is also paired with the formation of terrestrial exoplanets orbiting them. The strategic placement of M-dwarfs between main-sequence stars and brown dwarfs, their uniqueness as exoplanet analogs, and their dominating presence in the galactic stellar population make them priority targets for study. This work investigates outstanding questions, including the need to acquire constraints on their chemical compositions to decode formation processes, evolution, and interaction with companion objects. Chapter 1 lays out a broad background emphasizing the importance of studying the most populous star in the galaxy, their far-reaching implications, and primarily the numerous challenges in characterizing the atmospheres and environments of these stars. Chapter 2 investigates the influence of M-dwarf star spots propagating into spectra of transiting terrestrial planets, showing that inaccurate modeling of M-dwarf photospheres leads to significant bias when inferring atmospheric properties of companion exoplanets. These biases persist despite correcting M-dwarf spot signatures imprinted onto the exoplanetary spectra, even with high-fidelity JWST observations. This result emphasizes the need for improved stellar atmosphere models as the first step to improving our understanding of the companion planets. To address this, chapter 3 introduces SPHINX—a new stellar atmosphere model grid for M-dwarfs. SPHINX provides improved constraints on fundamental properties of benchmark M-dwarf systems (e.g., temperature, surface gravity, radius, and chemistry). The improvement is significant relative to the state-of-the-art stellar model grid available today. Chapter 4 expands this model, applying it to mid-to-late type M-dwarfs, and investigating chemical trends in their atmospheric properties. Using low-resolution observations, both archival data (from SpeX Prism Library Database) and from previous empirical studies; this chapter presents constraints on fundamental atmospheric properties of 71 low-mass, late-type M-dwarfs to understand spectroscopic degeneracies arising due to stellar activity, cloud/dust condensation and convection. With SPHINX models, the chemical properties of these stars are compared against main-sequence stars to acquire a more holistic understanding of M-dwarfs as a class—in the quest to ultimately characterize their companions.

White Dwarf stars are the stellar remnants of low mass stars which have completed their evolution. Nearly all stars will become white dwarfs. The interior of a white dwarf encapsulates its evolution history: unraveling a white dwarf’s internal structure constrains the physical events which occurred to construct its composition. Variable, or pulsating, white dwarfs emit pulsations which are sensitive to their internal stratification. Just as seismology reveals Earth’s interior, asteroseismology can reveal stellar interiors. The standard approach to construe an observed white dwarf’s chemical makeup is to match observed pulsation properties to theoretical stellar models. Observed white dwarf pulsation data has reached 6-7 significant digits of precision. As such, it is important for computational modeling to consider systematic offsets from initial conditions and theoretical uncertainties that are within the detectable threshold. By analyzing the magnitude of pulsation differences among various uncertainties from white dwarf models, one can place constraints on important theoretical uncertainties. In this thesis, I explore impacts on white dwarf pulsations that result from accounting for various uncertainties in computational models. I start by showing the importance of 22Ne, and its impact on the pulsations in Helium atmosphere white dwarfs. Next, I discuss how certain trapped modes of white dwarfs may yield a signal for the 12C(α,γ)16O reaction rate probability distribution function. This reaction occurs during the Helium core burning phase in stellar evolution, and chiefly determines the Carbon and Oxygen abundance of white dwarfs. Following this work, I show how overshooting impacts the pulsation signatures of the 12C(α, γ)16O reaction rate. I then touch on the analytical work I’ve done regarding educational research in the HabWorlds course offered at Arizona State University (ASU). I then summarize my conclusions from these efforts.

This thesis presents the results of a brown dwarf companion direct imaging survey. Over a total of 4 nights, 200 B and A stars were imaged using the Keck telescope and the Near Infrared Camera 2 (NIRC2). Presented here are preliminary results from the nights of 04 June 2014 and 17 December 2013. Brown dwarfs are partially degenerate objects that have masses between approximately 13 MJup and 75 MJup. Currently, the number of brown dwarf companions found around high mass stars is small. Finding brown dwarfs as companions to B and A stars will allow astronomers to study these objects when they are young and bright, giving key insights into their formation and evolution. \par A pipeline was written specifically for these data sets that includes dark subtraction, flat field correction, bad pixel correction, distortion correction, centering, filtering, and point spread function (PSF) subtraction. This subtraction was accomplished using the Karhunen-Loeve Image Processing (KLIP) algorithm which employs principal component analysis and Karhunen-Loeve (KL) transforms to subtract out starlight and artifacts from the images and allow for easier detection of a candidate companion. \par Only candidate companions from the night of 04 June 2014 were analyzed, with 95 candidate companions found around 22 stars. Due to a lack of some necessary images, 91 companions around 20 stars were analyzed and their masses were found to be approximately 6 MJup to 150 MJup with projected separations from the host star of approximately 100AU to 900AU. An upper limit of 6.6% was placed on stellar companion frequency and an upper limit of 93% was placed on brown dwarf companion frequency. This survey achieved a median sensitivity of ΔK of 12.6 at 1" and a ΔK of 15.1 at 3.6". Further observations will be required to determine whether the candidates found are true co-moving companions or background stars not bound to the host star.

The 78 secondary eclipse depths for a sample of 36 transiting hot Jupiters observed at 3.6- and 4.5 μm using the Spitzer Space Telescope is here reported. Eclipse results for 27 of these planets are new and include highly irradiated worlds such as KELT-7b (Kilodegree Extremely Little Telescope), WASP-87b (Wide Angle Search for Planets), WASP-76b, and WASP-64b, and important targets for the James Webb Space Telescope (JWST) such as WASP-62b. WASP-62b is found to have a slightly eccentric orbit (ecosω=0.00614±0.00058), and the eccentricities of HAT-P-13b (Hungarian Automated Telescope Project) and WASP-14b are confirmed. The remainder are individually consistent with circular orbits, but there is statistical evidence for eccentricity increasing with orbital period in this range from 1 to 5 days. Day-side brightness temperatures (Tb) for the planets yield information on albedo and heat redistribution, following Cowan and Agol (2011). Planets having maximum day side temperatures exceeding ∼2200 K are consistent with zero albedo and distribution of stellar irradiance uniformly over the day-side hemisphere. The most intriguing result is a detection of a systematic difference between the emergent spectra of these hot Jupiters as compared to blackbodies. The ratio of observed brightness temperatures, Tb(4.5)/Tb(3.6), increases with equilibrium temperature by 98±26 parts-per-million per Kelvin, over the entire temperature range in the sample (800K to 2500K). No existing model predicts this trend over such a large range of temperature. This may be due to a structural difference in the atmospheric temperature profile between the real planetary atmospheres as compared to models.

The pace of exoplanet discoveries has rapidly accelerated in the past few decades and the number of planets with measured mass and radius is expected to pick up in the coming years. Many more planets with a size similar to earth are expected to be found. Currently, software for characterizing rocky planet interiors is lacking. There is no doubt that a planet’s interior plays a key role in determining surface conditions including atmosphere composition and land area. Comparing data with diagrams of mass vs. radius for terrestrial planets provides only a first-order estimate of the internal structure and composition of planets [e.g. Seager et al 2007]. This thesis will present a new Python library, ExoPlex, which has routines to create a forward model of rocky exoplanets between 0.1 and 5 Earth masses. The ExoPlex code offers users the ability to model planets of arbitrary composition of Fe-Si-Mg-Al-Ca-O in addition to a water layer. This is achieved by modeling rocky planets after the earth and other known terrestrial planets. The three distinct layers which make up the Earth's internal structure are: core, mantle, and water. Terrestrial planet cores will be dominated by iron however, like earth, there may be some quantity of light element inclusion which can serve to enhance expected core volumes. In ExoPlex, these light element inclusions are S-Si-O and are included as iron-alloys. Mantles will have a more diverse mineralogy than planet cores. Unlike most other rocky planet models, ExoPlex remains unbiased in its treatment of the mantle in terms of composition. Si-Mg-Al-Ca oxide components are combined by predicting the mantle mineralogy using a Gibbs free energy minimization software package called Perple\_X [Connolly 2009]. By allowing an arbitrary composition, ExoPlex can uniquely model planets using their host star’s composition as an indicator of planet composition. This is a proven technique [Dorn et al 2015] which has not yet been widely utilized, possibly due to the lack of availability of easy to use software. I present a model sensitivity analysis to indicate the most important parameters to constrain in future observing missions. ExoPlex is currently available on PyPI so it may be installed using pip or conda on Mac OS or Linux based operating systems. It requires a specific scripting environment which is explained in the documentation currently stored on the ExoPlex GitHub page.