VictorJuiz/thesis huggingface dataset:
Monte Carlo Radiation Transport Simulations of Asymmetric Neutron Star Mergers

The merger of two neutron stars produces a neutron-rich outflow of >0.01 solar masses. This ejecta is a prime site for r-process nucleosynthesis, which will produce a range of radioactive heavy nuclei. Within a second of merger, an accretion disc forms around the central remnant. Material from this disc accretes onto the central compact object, launching a relativistic jet. The disc is also the source of a mildly-relativistic radioactive wind. Heating by r-process decays can accelerate accelerate portions of this wind by ~0.1c. Within a few hours, emission from the radioactive material gives rise to an ultraviolet, optical, and infrared transient: a kilonova. These ejecta are not expected to be spherically symmetric, so the emission will depend on the multi-dimensional ejecta structure as well as the viewing angle of the observer. Calculating this emission requires solving the time-dependent equation of radiation transport. To do so, I use Sedona, a parallel multi-dimensional, multi-frequency Monte Carlo radiation transport code. I analyze the parallel structure and performance of Sedona on modern supercomputers and discuss the performance and usability improvements I have made to the code. I use the endstates of a suite of 2D relativistic hydrodynamic simulations of jet-ejecta interaction as initial conditions for Sedona calculations, producing viewing angle-dependent light curves and spectra starting at 1.5 h after merger. I find that on this time-scale, jet shock heating does not affect the kilonova emission for the jet parameters surveyed. However, the jet disruption to the density structure of the ejecta does change the light curves. The jet carves a channel into the otherwise spheroidal ejecta, revealing the hot, inner regions, and making polar emission brighter and bluer. The winds launched from post-merger accretion discs are also aspherical. I continue a 3D general relativistic magnetohydrodynamic simulation of a disc wind in 2D hydrodynamics, and follow it until the flow is self-similar. I find that the inclusion of r-process heating doubles the mass-weighted median velocity, making the light curves brighter and bluer at ~1 d post-merger.

Advisor: Quataert, Eliot
Towards Ubiquitous Serverless Computing: Fast Large-Scale Machine Learning and Optimal Pricing for the Cloud

Serverless computing platforms represent the fastest-growing segment of cloud services and are predicted to dominate the future of cloud computing. However, the real-world applications of serverless systems are somewhat constrained due to several inherent bottlenecks such as their stateless nature, frequent occurrence of stragglers, naive resource allocation and pricing of computing resources, etc. The broader aim of this dissertation is to propose techniques to mitigate such bottlenecks and make the use of serverless computing ubiquitous. In particular, we focus on four applications that relate to large-scale serverless computing and describe them as follows./nTotal time for end-to-end distributed computation in such systems suffers due to a subset of slower workers, also referred to as stragglers. First, we propose straggler mitigation schemes for large-scale numerical linear algebra on serverless systems. Serverless systems allow users to massively scale the number of workers, but the total computation time is further exacerbated by high-communication latencies and the stateless nature of Function-as-a-Service (FaaS) platforms. Second, we further propose algorithms for large-scale convex optimization that are amenable to serverless systems. Recently, serverless computing --- due to its elasticity, scale, and ease of management --- has garnered significant traction from the industry and academia as a platform to train deep neural networks. Third, we further propose algorithms for massive scale non-convex optimization for training deep neural networks that take advantage of the scale of the serverless platform while mitigating communication costs. Finally, any ubiquitous platform is not viable until it serves the needs of the masses. In game-theoretic terms, a commercial platform should provide the required quality of services to customers while maximizing their utility (or satisfaction). Fourth, we propose principled yet practical schemes for allocating and pricing resources in serverless platforms.

Advisor: Ramchandran, Kannan
Courtade, Thomas
From networks to neurons: A multilevel investigation of experience-dependent improvement in prey capture behavior in the larval zebrafish

Understanding the neural mechanisms that guide behavior is one of the biggest quests in neuroscience. This question is tackled at different levels of analysis, from studying whole-brain blood oxygenation levels in humans, to minuscule receptor movements in cells. In this dissertation, I describe work aiming to explore the neural basis of behavioral improvement in the larval zebrafish from the network level, across brain areas, to the neuron level, looking at specific neuronal ensembles.In chapter one, I introduce the study of experience dependent changes in behavior through history and describe the advantages of using the ethologically relevant prey capture behavior in larval zebrafish as a model. In chapter two, in collaboration with Claire Oldfield, I studied how experience hunting live prey affects prey capture behavior and the underlying neural activity. I show that previous experience with live prey improves hunting performance compared to larvae that have been fed with inert fish flakes. Consequently, looking at whole-plane neural activity, I observed no differences in the neural representations of prey in the visual areas, however, experienced fish showed increased correlations between output neurons of the tectum and the forebrain, and an increased probability for visual activity to evoke motor action. This led to the hypothesis that experience may lower the threshold for visual information transfer to motor areas, via an increase of activity in the forebrain. To test this hypothesis, I specifically ablated cells in the habenula, one of the forebrain structures, and observed a reduction in eye convergences and prey consumption. These findings show the involvement of the forebrain in experience-dependent improvement of prey capture for the first time. In chapter three, I describe our attempts to study experience-dependent changes in forebrain activity and network dynamics between visual areas and the forebrain at a single-cell resolution, using multi-plane two-photon imaging. This project is still at its beginnings, but I describe the adaptation of the behavioral paradigm to the two-photon microscope, and the potential of recording large populations of neurons at cellular level during a naturalistic behavior.

Advisor: Isacoff, Ehud Y
Mechanistic basis of gating in potassium two-pore domain ion channels

Potassium two-pore domain (K2P) family ion channels are increasingly appreciated as important electrogenic sensors that are used by diverse cell types including neurons, cardiomyocytes, and epithelial cells. The activity of these channels can be activated up to one-hundred fold by diverse physical and chemical stimuli including pH, intracellular calcium, temperature, phospholipids and fatty acids, volatile anesthetics, and membrane tension. In addition to this “stimulus gated” activity, channels in this family also have a basal “leak gated” activity that drives the cellular resting membrane close to the potassium ion reversal potential in the absence of their respective stimuli. While the structural basis of closed states and certain “stimulus gated” open states have been previously determined, the structural basis of a “leak gated” open state in K2P channels is unknown. Here, we show the physical basis for basal “leak gated” activity of the mechanosensitive K2P family ion channel TRAAK, and propose a gating model that includes both “leak gated” and “stimulus gated” openings. Next, we identify the structural basis of intracellular and extracellular alkaline pH “stimulus gated” activation in the acid-sensitive K2P family ion channel TASK2. We observe structural similarities between the “leak gated” structure of TRAAK and other K2P channel structures, including TASK2. This observation supports a general mechanism for “leak gated” activity in K2P family ion channels.

Advisor: Brohawn, Stephen
Synthesis approaches to quantifying biodiversity change, tools and applications

Understanding the impacts of anthropogenic change on the world's biodiversity is a fundamental goal of ecology. Assessing broad-scale patterns in biodiversity is especially critical for appropriately allocating limited conservation resources amid the ongoing biodiversity crisis. Recent advances in data availability and computational tools have made synthesis an increasingly powerful approach for exploring these patterns, allowing us to assess previously intractable continental and global scale questions. However, controversy over the use of synthesis methods is ongoing due to limitations in data and tools. Further, synthesis largely focuses on species-based approaches, leaving unaddressed other critical dimensions of biodiversity./nOver three chapters, I discuss the powerful opportunity synthesis represents and address the critical need for improved methodology for understanding biodiversity change. In chapter 1, I lay out a road map for overcoming limitations of biodiversity synthesis. I advocate for improved metadata for constituent studies to facilitate better inclusion of ecological context in synthesis work, adoption of best practices in code development and sharing, and more explicit statements of inference grounded in data scope. In chapter 2, I present my contribution to synthesis software, the R package `taxadb`, a tool for reconciling taxonomic discrepancies. `taxadb` uses a local database to interface with taxonomic data providers allowing quick resolution of species names to taxonomic ID's. In chapter 3, I perform the first broad-scale synthesis of temporal functional diversity trends. Bridging 1000's of assemblage time series and functional trait data, I assess general patterns of functional change. I find evidence of maintenance of functional structure across communities, regardless of taxon, climate, or realm.

Advisor: Boettiger, Carl
A novel STING-activating vaccine for M. tuberculosis induces pathogen-specific Th17 cells and provides significant IL-17-dependent protection against infection

Before the emergence of SARS-CoV-2 and the ensuing COVID-19 pandemic, the pathogenic bacteria Mycobacterium tuberculosis was the world’s leading infectious disease killer. In 2020, an estimated 1.6 – 1.8 million people worldwide died of tuberculosis (TB) disease, comparable to the ~1.9 million lives claimed by COVID-19. However, while highly effective vaccines were rapidly developed for COVID-19, the sole approved TB vaccine, Bacillus Calmette-Guérin (BCG), is only moderately effective at blocking infection and has not prevented the TB pandemic despite 100 years of use and more widespread distribution that any vaccine in history. This highlights the urgent need for improved vaccines to prevent TB, which begins with a more complete understanding of the protective immune response to TB and the development of new strategies to effectively induce this immune response in patients. Here, we demonstrate a novel TB vaccine strategy using small molecule cyclic di-nucleotide (CDN) adjuvants to activate the STING pathway of the innate immune system. Subcutaneous administration with a CDN adjuvanted protein subunit vaccine for TB leads to protection in mice that is equivalent to that afforded by BCG. This protective efficacy is STING-dependent but Type I IFN-independent and correlates with a significant population of Th17 cells that are not present in the lungs of unvaccinated mice. Similarly, intranasal immunization leads to a multifaceted pathogen-specific CD4 T cell response characterized by both Th1 and Th17 cells, as well as a non-classical Th1-Th17 population that co-expresses IFN-γ and IL-17. Intranasally vaccinated mice also benefit from enhanced CD4 T cell localization to the lung parenchyma and homing to granulomatous lung lesions compared to unvaccinated mice. This distinct CD4 T cell response leads to protection against infection that is significantly greater than BCG and is more effective than any protein subunit vaccine tested against M. tuberculosis in mice to date. Full protective efficacy after intranasal immunization is dependent on both IFN-γ and IL-17 and, in contrast to subcutaneous administration, relies on Type I IFN signaling. Importantly, intranasal immunization with a CDN vaccine is also capable of boosting BCG-mediated immunity. These results demonstrate that stimulation of the STING pathway is sufficient to induce a protective CD4 T cell response to an intracellular pathogen and contribute to our knowledge of CD4 T cell subsets that can mediate protection against M. tuberculosis infection.

Advisor: Stanley, Sarah A
Expanding the Reach of Fuzz Testing

Software bugs remain pervasive in modern software systems. As software becomes increasingly intertwined in all aspects of our lives, the consequences of these bugs become increasingly severe. Since the mid-2010s, several important security vulnerabilities have emerged from basic correctness bugs in software. Modern fuzz testing or fuzzing tools have greatly helped reduce the consequences of these bugs. These fuzzing tools can automatically find inputs revealing bugs in large-scale software. Arming developers with these tools allows them to find bugs more rapidly, before they have significant security impacts./nHowever, even the most sophisticated modern fuzzing algorithms remain restricted in the software quality problems they solve. Most of the bugs they find automatically are memory mismanagement issues typical of C/C++ programs---like out-of-bounds array reads---and most of these bugs lie in the shallower parsing stages of programs. Further, in spite of the impressive search algorithms underlying modern fuzzing tools, they have only really been applied to this test-input generation problem. This thesis presents several algorithms which adapt fuzzing to new testing domains, and even looks at applying these algorithms to the problem of program synthesis. Taken as a whole, these algorithms provide a view of the promise of modern fuzzing algorithms, and how to alter these algorithms to solve diverse software quality problems./nThis thesis finds that three key components of modern fuzzing algorithms must be extended in order to solve broader software quality problems. First, this thesis presents a generalized notion of feedback-directed fuzzing, which can be used to automatically find different types of bugs, including algorithmic complexity bugs, extreme memory allocations, and to target recently-modified code. Second, this thesis explores how well-structured mutations are key to enabling mutational fuzzers to explore deeper program states, and find bugs beyond those in parsers. Finally, this thesis shows that viewing random input generators as a specification of a search space, and adjusting the sampling distribution of these generators automatically, enables effective blackbox validity fuzzing and program synthesis for large APIs.

Advisor: Sen, Koushik
The Political Economy and Economic Effects of Large-Scale Public Policies

This dissertation studies the implementation of large-scale public policies in developing countries. Chapter I focuses on how collective action can shape public policy. In particular, I study how organized groups of workers affected the land reform implemented by Salvador Allende ́s government in 1970 in Chile. Using an event-study design, we find that the local political action of workers - proxied by land invasions - affected the intensity and location of expropriations. In Chapter II, I change time and location and study how political favoritism affected the expansion of the electric grid in Kenya around the 2013 and 2017 presidential elections. While the aggregate political bias we estimate is meaningful, it is smaller in magnitude than that documented previously, suggesting that increasingly active independent media scrutiny as well as increasingly robust democratic institutions, expanding constraints on executive power, and donor oversight may have partly curbed favoritism. Finally, in Chapter III I study the effects on welfare of a large-scale public investment: the expansion of the subway network in Santiago, Chile between 2002 and 2020. We find that when workers receive access to the subway network, they start taking jobs further away. We see an increase in wages for benefited workers, including those workers who do not switch firms, suggesting a reduction in the labor market power firms have over workers. Our model estimates suggest incorporating labor market power can make an important difference in welfare estimations.

Advisor: Card, David
Strongly Correlated Two-dimensional van der Waals Materials: Characterization and Manipulation

The interplay between charge, spin, and orbital degrees of freedom in many-electron solid systems results in a large variety of strongly correlated phenomena. Correlation of electrons lies in the heart of the strongly correlated physics, but also masks the essential physics leading to a certain observed phenomenon. The quest of a minimal model material and clean manipulation method is sometimes regarded as the key to solve problems in the field. Even though layered properties of certain strongly correlated materials have been known for decades, methods of preparation and manipulation of atomically thin materials have to wait until recent years. The last two decade have witnessed the booming of research in two-dimensional van der Waals materials and various methods have been developed for layered materials. The current development in this area allows the application of these methods into more complicated systems in order to search for the essential physics covered in the bulk compounds. In this dissertation, we explore the application of these techniques in the study of strongly correlated physics in $1T$-TaSe\textsubscript{2}, and Fe\textsubscript{3}GeTe\textsubscript{2}. The fabrication of high-quality samples enables the detection of intrinsic physics in these systems. Disentangling the in-plane and out-of-plane physics through mechanical exfoliation provides a minimal model of a bulk material and helps solve the mystery of metallic properties in bulk $1T$-TaSe\textsubscript{2}. The flexibility in the formation and tuning of various heterostructures provides not only interesting systems to study, but also useful tools to characterize and manipulate electronic states in layered strongly correlated systems. We use a novel Kondo heterostructure to probe monolayer magnetic properties in $1T$-TaSe\textsubscript{2}, which is challenging for bulk sensitive detection methods. On the other hand, due to their special layered structure, two-dimensional strongly-correlated systems may exhibit novel properties not present in the bulk, as in the case of Fe\textsubscript{3}GeTe\textsubscript{2} nanoflakes. We have discovered unusual magnetotransport properties in this system. Easy access of properties in two dimensional systems allows for a thorough diagnosis of this phenomenon. We hope to provide new perspectives from the study of constituents of complicated bulk materials.

Advisor: Zhang, Xiang
Designing Interaction-aware Prediction and Planning Models for Autonomous Driving

The ability to interact with other road participants is essential for autonomous vehicles in order to navigate under highly complex or critical driving scenarios. It is an extremely challenging task to enable autonomous vehicles interactively predict behaviors of others, and plan safe and high-quality motions for themselves. In fact, designing interaction-aware prediction and planning models is of great importance for autonomous vehicles to achieve full autonomy./nWhen designing a model, it is essential to consider our expectations for the model, which can be derived through two perspectives: 1) From the perspective of evaluation metrics (i.e. backward design); 2) From the perspective of task and user preferences (i.e. forward design). In this dissertation, a combination of forward and backward design process is proposed and it is argued that a model should be designed based on desired model properties inferred from metrics, tasks, and user preferences. A total of seven properties are covered in this dissertation: uncertainty, multi-modality, interpretability, flexibility, generalizability, reliability, and efficiency. The fundamental research question we addressed in this dissertation is: how to design interaction-aware prediction and planning models under different autonomous driving settings in order to achieve desired model properties./nThis dissertation is divided into two parts. In Part I, we focus on the design of two-agent interaction models, which involves fundamental explorations of how certain model property can be achieved through algorithm design by taking the advantage of relatively low-complexity settings. Part II is concerned with the design of multi-agent interaction models, which includes comprehensive analysis and design for each desired model property under more complicated driving scenarios. In each part, we consider different prediction and planning related problems, and motivate our design by identifying desired model properties that correspond to each problem. By utilizing the proposed model design process under different problem settings, we demonstrate that our models are able to not only achieve desired properties, but also have great performances in terms of various evaluation criteria.

Advisor: Tomizuka, Masayoshi
Some results on arithmetic aspects of K3 surfaces and abelian varieties

The thesis is divided into three parts. We consider the essential dimension of algebraic stacks, and compute the essential dimension of moduli stack of polarized K3 surfaces in part 1. In part 2 we concentrate on the period index problems. More precisely, we show that if C is an algebraic curve of genus 1 over a field k of characteristic 0 then the index of C, defined to be the greatest common divisor of the degrees of its closed points, is equal to the index of the Brauer class defined by the G_m-gerbe given by the Picard stack of degree 0 line bundles on C. We also relate this number to the essential dimension. In the last part we give a new proof of the finiteness of abelian varieties over finite fields using the Tate conjecture. This result was first proved by Zarhin.

Advisor: Olsson, Martin