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- Creators: Arizona State University
- Creators: Butler, Nathaniel
Description
The distribution of galaxies traces the structure of underlying dark matter, and carries signatures of both the cosmology that evolved the universe as well as details of how galaxies interact with their environment and each other. There are many ways to measure the clustering of galaxies, each with unique strengths, uses, theoretical background, and connection to other physical concepts. One uncommon clustering statistic is the Void Probability Function (VPF): it simply asks, how likely is a circle/sphere of a given size to be empty in your galaxy sample? Simple and efficient to calculate, the VPF is tied to all higher order volume-averaged correlation functions as the 0$^{\text{th}}$ moment of count-in-cells, and encodes information from higher order clustering that the robust two-point correlation function cannot always capture. Using simulations of Lyman-alpha emitting galaxies across either redshift history or the epoch of reionization, this work asks: how powerful is the VPF itself? When can and should it be used for galaxy clustering? What unique constraints or guidelines can it give for the pacing of reionization, in the Lyman-$\alpha$ Galaxies in the Epoch of Reionization (LAGER) narrowband survey or across the Roman Space Telescope grism? This work provides practical guidelines for creating and carrying out clustering studies using the the VPF, and motivates the use of the VPF for reionization. The VPF of LAEs can complement LAGER constraints for the end of reionization, and thoroughly inform the timing and pace of reionization with Roman.
ContributorsPerez, Lucia Alexandra (Author) / Malhotra, Sangeeta (Thesis advisor) / Butler, Nathaniel (Thesis advisor) / Groppi, Christopher (Committee member) / Scannapieco, Evan (Committee member) / Rhoads, James E (Committee member) / Arizona State University (Publisher)
Created2022
Description
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.
ContributorsFisher, Theresa Mason (Author) / Walker, Sara I (Thesis advisor) / Hartnett, Hilairy (Committee member) / Line, Michael (Committee member) / Shkolnik, Evgenya (Committee member) / Okie, Jordan (Committee member) / Arizona State University (Publisher)
Created2023
Description
Planets are generally believed to form in protoplanetary disks within a few million years (Myr) to several hundred Myr. But planetary embryos or protoplanets likely exist before disk gas dissipates (in three to ten Myr), capturing H2 -rich primary atmospheres from the nebula. Exploring these primordial atmospheres of planets provides a pathway to understanding the origins and the diversity of planets in the solar system and beyond. In this dissertation, I studied the primary atmospheres by modeling their formation, their impacts on planet formation, and determining methods to characterize them on exoplanets.
First, I numerically investigated the flow structures and dynamics of the primary atmospheres accreted on Earth-sized planets with eccentric orbits. Such planets can generate atmosphere-stripping bow shocks, as their relative velocities to the gas are generally supersonic. The atmospheres are three to four orders of magnitude less massive than those of planets with circular orbits. Hydrodynamic simulations also revealed large-scale recycling gas flow in the post-shock regions. This study provides important insights into the impacts of migration and scattering on primary atmospheres.
Second, I looked into how the presence of the primary atmosphere affects the trajectories of chondrule precursors passing through a planetary bow shock. To determine what magnetic fields chondrules were exposed to as they cooled below their Curie points, I computed the gas properties and magnetic diffusion rates in the bow shock region of a planet with and without the primary atmosphere. I concluded that, if melted in planetary bow shocks, most chondrules were cooled in the far downstream and they probably recorded the background nebular field.
Last, I studied the characterization of cloudy primary atmospheres on exoplanets using a Bayesian retrieval approach. I focused on obtaining bulk cloud properties and the impact of clouds on constraining various atmospheric properties through transmission spectroscopy using the James Webb Space Telescope (JWST). Most key atmospheric and cloud inferences can be well constrained in the wavelength range (0.6 – 11 µ m) but there are different optimal wavelengths for constraining atmosphere or cloud parameters. Other results including degeneracies among cloud parameters can also serve as a guideline for future observers.
First, I numerically investigated the flow structures and dynamics of the primary atmospheres accreted on Earth-sized planets with eccentric orbits. Such planets can generate atmosphere-stripping bow shocks, as their relative velocities to the gas are generally supersonic. The atmospheres are three to four orders of magnitude less massive than those of planets with circular orbits. Hydrodynamic simulations also revealed large-scale recycling gas flow in the post-shock regions. This study provides important insights into the impacts of migration and scattering on primary atmospheres.
Second, I looked into how the presence of the primary atmosphere affects the trajectories of chondrule precursors passing through a planetary bow shock. To determine what magnetic fields chondrules were exposed to as they cooled below their Curie points, I computed the gas properties and magnetic diffusion rates in the bow shock region of a planet with and without the primary atmosphere. I concluded that, if melted in planetary bow shocks, most chondrules were cooled in the far downstream and they probably recorded the background nebular field.
Last, I studied the characterization of cloudy primary atmospheres on exoplanets using a Bayesian retrieval approach. I focused on obtaining bulk cloud properties and the impact of clouds on constraining various atmospheric properties through transmission spectroscopy using the James Webb Space Telescope (JWST). Most key atmospheric and cloud inferences can be well constrained in the wavelength range (0.6 – 11 µ m) but there are different optimal wavelengths for constraining atmosphere or cloud parameters. Other results including degeneracies among cloud parameters can also serve as a guideline for future observers.
ContributorsMai, Chuhong (Author) / Desch, Steven SD (Thesis advisor) / Line, Michael ML (Committee member) / Patience, Jennifer JP (Committee member) / Li, Mingming ML (Committee member) / Shkolnik, Evgenya ES (Committee member) / Arizona State University (Publisher)
Created2020