Optimal Reconstruction of Cosmological Density Fields

A key objective of modern cosmology is to determine the composition and distribution of matter in the universe. While current observations seem to match the standard cosmological model with remarkable precision, there remains tensions between observations as well as mysteries relating to the true nature of dark matter and dark energy. Despite the recent increased availability of cosmological data across a wide redshift, these tensions have remained or been further worsened. With the explosion of astronomical data in the coming decade, it has become increasingly critical to extract the maximum possible amount of information available across all available scales. As the available volume for analysis increases, we are no longer sample variance limited and existing summary statistics (as well as related estimators) need to be re-examined. Fortunately, parallel with the construction of these surveys there is significant development in the computational techniques used to analyze that data. Algorithmic developments over the past decade and expansion of computational resources allow large cosmological simulations to be run with relative simplicity and parallel theoretical developments motivate increased interest in recovering the underlying large scale structure of the universe beyond the power spectra.The detailed study of this large scale structure has the potential to shed light on various unanswered questions and under-constrained physical models for the dark sector and the nature of gravity. As we reach higher redshifts with statistically significant samples, the large scale structure can serve as a link between local observations and the cosmic microwave background. These surveys rely on a variety of biased probes, including the lensing and distribution of galaxies, imprints of large scale structure in secondary anisotropies of the CMB, and absorption lines in the spectra of high redshift quasars. These observations are complementary; they probe different scales, have different sources of astrophysical and observational uncertainties, have unique degenercies in parameter space, and require their own methods to extract cosmological parameters from.In this thesis, I discuss a number of new developments in the analysis of these diverse cosmological datasets. After introductory material, I discuss work re-examining the lensing of the Cosmic Microwave Background by cluster-sized objects and implement techniques for accurate mass estimation. I demonstrate that this analysis is optimal in the low noise, small scale limit. In the second part, I develop a maximum likelihood formalism for linear density fields, applicable for reconstructing underlying signal from a variety of cosmological probes including projected galaxy fields and cosmic shear, showing that effects of anisotropic noise and masking can be mitigated. Finally, I extend this work to nonlinear observables by using a forward modeling approach for Lyman Alpha forest tomography, finding more accurate cosmic web reconstruction verses existing techniques. The unifying theme of all these works is revisiting existing matter density reconstruction techniques with a critical eye and using new statistical and computational techniques to efficiently perform an unbiased, lower variance, estimate. Included is discussion of the possible impacts of these methods to improve constraints of cosmological parameters and/or astrophysical processes

Enabling III-V-based optoelectronics with low-cost dynamic hydride vapor phase epitaxy

Silicon is the dominant semiconductor in many semiconductor device applications for a variety of reasons, including both performance and cost. III-V materials have improved performance compared to silicon, but currently they are relegated to applications in high-value or niche markets due to the absence of a low-cost, high-quality production technique. Here we present an advance in III-V materials synthesis using hydride vapor phase epitaxy that has the potential to lower III-V semiconductor deposition costs by orders of magnitude while maintaining the requisite optoelectronic material quality that enables III-V-based technologies to outperform Si. We demonstrate the impacts of this advance by addressing the use of III-Vs in terrestrial photovoltaics, a highly cost-constrained market. The emergence of a low-cost III-V deposition technique will enable III-V electronic and opto-electronic devices, with all the benefits that they bring, to permeate throughout modern society.Comment: pre-prin

Family Surveillance by Algorithm: The Rapidly Spreading Tools Few Have Heard Of

The latest reckoning with structural racism in the United States has involved critical reflection on the role of the criminal justice system, education policy, and housing practices in perpetuating racial inequity. But another area long overdue for collective reexamination is the child welfare system and the algorithms working behind the scenes. That's why the ACLU has conducted a nationwide survey to learn more about these tools.This report examines how many jurisdictions across the 50 states, D.C. and U.S. territories are using one category of predictive analytics tools: models that systematically use data collected by jurisdictions' public agencies to attempt to predict the likelihood that a child in a given situation or location will be maltreated

Aggregation Behavior And Chromonic Liquid Crystal Properties Of An Anionic Monoazo Dye

X-ray scattering and various optical techniques are utilized to study the aggregation process and chromonic liquid crystal phase of the anionic monoazo dye Sunset Yellow FCF. The x-ray results demonstrate that aggregation involves pi-pi stacking of the molecules into columns, with the columns undergoing a phase transition to an orientationally ordered chromonic liquid crystal phase at high dye concentration. Optical absorption measurements on dilute solutions reveal that the aggregation takes place at all concentrations, with the average aggregation number increasing with concentration. A simple theory based on the law of mass action and an isodesmic aggregation process is in excellent agreement with the experimental data and yields a value for the bond energy between molecules in an aggregate. Measurements of the birefringence and order parameter are also performed as a function of temperature in the chromonic liquid crystal phase. The agreement between these results and a more complicated theory of aggregation is quite reasonable. Overall, these results both confirm that the aggregation process for some dyes is isodesmic and provide a second example of a well-characterized chromonic system

Web 2.0 Use and Knowledge Transfer: How Social Media Technologies Can Lead to Organizational Innovation

The concept of Web 2.0 has gained widespread prominence in recent years. The use of Web 2.0 applications on an individual level is currently extensive, and such applications have begun to be implemented by organizations in hopes of boosting collaboration and driving innovation. Despite this growing trend, only a small number of theoretical perspectives are available in the literature that discuss how such applications could be utilized to assist in innovation. In this paper, we propose a theoretical model explicating this phenomenon. We argue that organizational Web 2.0 use fosters the emergence and enhancement of informal networks, weak ties, boundary spanners, organizational absorptive capacity, which are reflected in three dimensions of social capital, structural, relational, and cognitive. The generation of social capital enables organizational knowledge transfer, which in turn leads to organizational innovation. Based on this model, suggestions for organizations to facilitate this process are also provided, and theoretical implications are discussed

The Misuse of AUC: What High Impact Risk Assessment Gets Wrong

When determining which machine learning model best performs some high impact risk assessment task, practitioners commonly use the Area under the Curve (AUC) to defend and validate their model choices. In this paper, we argue that the current use and understanding of AUC as a model performance metric misunderstands the way the metric was intended to be used. To this end, we characterize the misuse of AUC and illustrate how this misuse negatively manifests in the real world across several risk assessment domains. We locate this disconnect in the way the original interpretation of AUC has shifted over time to the point where issues pertaining to decision thresholds, class balance, statistical uncertainty, and protected groups remain unaddressed by AUC-based model comparisons, and where model choices that should be the purview of policymakers are hidden behind the veil of mathematical rigor. We conclude that current model validation practices involving AUC are not robust, and often invalid