VictorJuiz/thesis huggingface dataset:
Generalized polylogarithms in perturbative quantum field theory [electronic resource]

This thesis examines the mathematical structure of scattering amplitudes and correlation functions in perturbative quantum field theory. The focus is on maximally supersymmetric N=4 super Yang-Mills theory, though the techniques presented here should be applicable in other contexts as well. Multi-loop Feynman integrals typically do not evaluate to classical functions, but in many cases they can be expressed in terms of certain types of iterated integrals that generalize classical polylogarithms. I show throughout this thesis how certain analytic properties of these functions can be used in conjunction with physical constraints to produce highly efficient methods of calculation. In the first half of this work, I focus on quantities in N=4 super Yang-Mills theory that can be expressed in terms of polylogarithmic functions of two variables, presenting results for the multi-Regge kinematical limit of six-point amplitudes and for the four-point correlation function of stress-tensor multiplets. In the second half of this work, I extend the analysis to functions of three variables in order to calculate the six-point remainder function, which describes the scattering of six gluons in planar N=4 super Yang-Mills theory. I present analytical results for the remainder function at three and four loops.

Keywords: Physics.
Advisor: Dixon Lance Jenkins
Kallosh Renata advisor. Thesis advisor
Peskin Michael Edward
Generous purpose during early adolescence [electronic resource] : the roles of school generosity and relational spirituality

Purpose, especially in its generous form, may serve as a critical catalyst on the path to thriving for adolescents. However, while there is a growing amount of research about purpose, less of it focuses on ways in which purpose might be supported by both individual and contextual variables. Spirituality and schools are two such variables. The primary hypotheses of this study posited that both school generosity and relational spirituality would positively predict generous purpose. The secondary hypotheses of this study are better understood as exploratory. Specifically, I hypothesized that some relation would be found between school generosity and relational spirituality, but did not speculate about the exact nature of this relation. I also hypothesized that the spiritual context of the school would be associated with differences in relations among school generosity, relational spirituality and generous purpose, but did not speculate about the specific nature of those differences. In order to test these hypotheses, survey data was collected from ninth grade students (n = 253) at three high schools of varying stated spiritual contexts twice during the ninth grade year. The schools included a Catholic school, a Waldorf-methods school, and a community-centered charter school. Correlation and linear regression analysis led to the following results. School generosity among students and relational spirituality were both shown to be statistically significant, positive predictors of generous purpose in ninth grade students. In addition, school generosity and relational spirituality were also related to each other. First, school generosity was shown to predict relational spirituality. Second, when both were included in a regression equation predicting generous purpose, only relational spirituality remained a significant predictor of generous purpose. School-level results were more mixed, with only weak evidence found for the role of the spiritual context of the school. These results are interpreted in a positive youth development framework, pointing to the importance of peers and of school environments that provide a good fit for early adolescents. Implications for both PYD theory and education are discussed.

Keywords: Education.
Advisor: Damon William
Obradović Jelena (Education professor) advisor. Thesis advisor
Pope Denise Clark
Genetic probing of the origin of alveolar myofibroblasts and bronchopulmonary dysplasia, a disease of alveolar development [electronic resource]

Alveolarization, the final stage of lung development, promotes gas-exchange by dividing the sac-like terminal airspaces of the lung into thin-walled pockets. Myofibroblasts are found at sites of septation, and mouse mutants in PDGFR alpha signaling lack myofibroblasts and air sacs fail to septate, suggesting that myofibroblasts play a role in septation. Further, a similar arrest in alveolarization is observed in diseases like bronchopulmonary dysplasia (BPD), a disease of premature infants that twin studies implicate may have important genetic contributions. In this thesis, I explore the developmental origins of myofibroblasts in mouse and the genetic basis of BPD. I first describe a novel protocol developed to extract DNA from dried blood spots taken from newborn infants that can be used in genotyping and genome-wide association studies (GWAS). I then describe an agnostic exploration of the genetic basis of BPD. Finally, I describe the use of genetic lineage tracing in mice to identify airway smooth muscle cells as a source of ductal myofibroblasts during lung development.

Keywords: Biochemistry.
Advisor: Krasnow Mark
Brown Patrick O'Reilly
Spudich James A.
A genome-wide siRNA screen identifies a novel, 7 transmembrane protein that mediates amino acid signaling to mTORC1 [electronic resource]

Cells have an evolutionarily conserved mechanism to sense and integrate nutrient information for optimal growth and survival. The signaling network that is central to receiving nutritional inputs and translating them to effects on anabolic and catabolic activities of the cell consists of a large serine/threonine kinase known as mTOR. mTOR signaling is crucial for many important cellular processes such metabolism, growth, proliferation and differentiation. It is able to integrate diverse inputs including growth factors, cytokines, energy, oxygen and stress in addition to nutrients and regulate diverse outputs including translation, ribosome biogenesis, lipid biogenesis and autophagy. It is also an important therapeutic target and its inhibitor Rapamycin is currently being used or tested for a wide range of diseases including cancers and neurodegenerative diseases. Amino acids are arguably the most important regulators of mTOR and a long standing mystery in the field is the identity of the amino acid sensor and the mechanism of sensing. Using RNAi, we systematically screened through the human genome for candidate genes regulating amino acid signaling. We confirm that the mitochondria and the lysosomes are the two key sensing organelles, with amino acid metabolism and the RagGTPases being important for signal transduction. We identify a novel lysosomal 7 transmembrane protein that mediates signals upstream the RagGTPases and binds mTORC1-RagA in an amino-acid dependent manner. We also demonstrate that increasing levels of this protein enables cells to recruit mTOR to lysosomes and activate its kinase activity in the absence of amino acids. We show that GPR137B, mTORC1 and RagA form an amino acid sensitive, high-affinity binding complex at the lysosome. We propose a model of sensing where the 7-transmembrane protein, which we renamed to MORTOR, forms a tight complex with mTORC1-RagA in the presence of amino acids, resulting in the persistent lysosomal recruitment and activation of mTORC1. In addition to identifying novel regulators, this systematic study has also generated testable hypotheses about systems level properties of mTORC1 signaling, thus providing the foundation to understand mTOR signaling as a network. The discovery of the novel 7 transmembrane protein and its GPCR-like characteristics also has the potential to lead to new classes of therapeutics and targets for this important pathway.

Keywords: Chemical and Systems Biology.
Advisor: Meyer Tobias primary advisor. Thesis advisor
Brunet Anne
Ferrell James Ellsworth advisor. Thesis advisor
Geometric algorithms in modeling biological evolution [electronic resource]

Evolutionary biology is a field that studies the change of a species over time. Mathematical models can provide hypotheses to explain the observed phenomena and predict what type of changes will occur in the future. From a computational perspective, there are three main challenges: The first challenge is the data, which in general comes from two different types of sources. With computer simulation, people are able to study conformational changes at very detailed level. In this case, we often have very large data sets and would like to understand dynamics at more macroscopic level. On the other hand, data from real experiment is more expensive and thus very limited. We present methods to extract useful information when the data is too much, and to synthesize data when it is too little. The second challenge is the distances between configurations in the data set. Since we are modeling evolution, it is more important to measure their kinetic similarity rather than structural similarity. We define distance functions that incorporate kinetic information and develop efficient clustering algorithms. The third challenge is the correspondences between identities in different configurations. They may have one-to-one, partial, or even no correspondence in various settings. We show biological examples in each case and present ways to compare configurations with both distinct and indistinct identities.

Advisor: Guibas Leonidas J. primary advisor. Thesis advisor
Pande Vijay advisor. Thesis advisor
Plotkin Serge A. advisor. Thesis advisor
A geostatistical approach to quantifying rainfall uncertainty in Southern Africa using terrain characteristics [electronic resource]

Rainfall is the most important driver of hydrologic response predicted by models. By improving estimates of rainfall, improved estimates of streamflow may be possible. There has been little comprehensive research regarding the relative importance of ancillary terrain data for improving rainfall estimates. This research focuses on using geostatistical techniques to generate improved rainfall estimates using gridded ancillary terrain data. In addition, a geostatistical approach is used to estimate ensemble rainfall fields, which could be used to stochastically drive a rainfall-runoff model. The field sites for this research are (1) the 31,200 sq km Inkomati Water Management Area (IWMA) in northeastern South Africa, and (2) the more data-sparse 185,100 sq km Central-North Regional Water Administration (ARACN) in Mozambique. Monthly rainfall data for the year 1970 were analyzed. This study found that, for this time period, the most important pieces of ancillary data for improving the estimation of rainfall fields in IWMA and ARACN are elevation (20km resolution) and slope. Distance to long-term annual rainfall maximum and distance to coast also helped to improve rainfall estimation.

Keywords: Civil and Environmental Engineering.
Advisor: Freyberg David L. advisor. Thesis advisor
Germanium-tin (GeSn) Technology [electronic resource]

Semiconducting germanium-tin (GeSn) alloy is a versatile material system that is attracting significant research interest due to its several unique and beneficial properties, such as the ability to show a direct band gap and the compatibility with conventional Si technology. GeSn alloy system is also predicted to exhibit high electron and hole mobilities, making it an ideal material platform for co-integration of Si compatible photonics and high speed CMOS devices. This thesis discusses a very broad range of topics pertinent to GeSn, beginning with a detailed theoretical study of electronic properties of GeSn using both first principles and empirical methods. Challenges in obtaining high quality epitaxial GeSn thin films are addressed. Innovations in GeSn material processing and device fabrication are presented. Applications of the GeSn technology thus developed to high performance logic devices, Si-compatible photonics and 3-dimensional integrated circuits are discussed.

Keywords: Electrical Engineering.
Advisor: Saraswat Krishna primary advisor. Thesis advisor
Harris J. S. (James Stewart)
Nishi Yoshio
Global Ends and Local Means: Lessons about Filipino Youth Activism and Civic Engagement in Anakbayan

This study sought to explore what participants learned and valued about civic engagement through their involvement with Anakbayan, a Filipino youth-led, grassroots organization that fights for the welfare of its local communities as well as the need for genuine social change and democracy in the Philippines. With such a unique group operating within the context of the United States, the research aimed to explore what members’ experiences might contribute to contemporary understandings of civic engagement. The study found that members gained a greater awareness of both their civic identity and civic context, most typically shown by how members located themselves and their experiences within the group’s political discourse (i.e., how they saw themselves in relation to the issue of immigration). Moreover, members also gained new means of imagining and constructing community within the context of a specific type of community organizing. Members adapted a notion of community that included both local and global contexts which then influenced how they approached taking action and engaging with Anakbayan’s larger civic mission. Variation occurred based on the degree to which participants demonstrated internalization of the relationship between local and global contexts.

Keywords: civic engagement
Filipino
youth
Anakbayan
social change
youth movement
community organizing
Thesis
Advisor: Antonio Anthony
Goodness-of-fit tests for parametric specification of diffusion coefficients [electronic resource]

With wide range of models for volatility in continuous-time finance, we propose a test for the parametric specification of local volatility models. We provide two approaches to this problem with a focus on a few key properties for the tests. Our first approach is based on deriving an asymptotically independent and identically distributed (IID) sequence through a variance stabilizing transformation. We analyze and employ the generalized runs tests of Cho and White (2011) for testing the IID hypothesis to derive a statistic with universal limit law regardless of estimation method for the parametric volatility function. We perform a simulation study to evaluate the finite sample performance of the test. Our second approach is a variations-based test using the existing limit theory for variations processes and functionals of normalized increments of observed diffusion processes covered in Jacod and Protter (2012). We utilize a local normalization and introduce an orthogonality condition which leads to a unified framework for a universal limit law in univariate and multivariate models. This avoids the necessity for a bootstrap procedure that reduces performance and leads to complications associated with the structure of the diffusion process. The test has good finite sample performance as we demonstrate in numerical simulations and extends to multivariate diffusions as well.

Advisor: Giesecke Kay primary advisor. Thesis advisor
Glynn Peter W. advisor. Thesis advisor
Lai T. L. advisor. Thesis advisor
Green-Marl [electronic resource] : a domain specific language for graph analysis

Graph is a fundamental data structure that captures arbitrary relationship between data entities. In recent years, the importance of efficient and scalable processing of large graph instances has been growing due to emerging applications such as social network services and computational biology, where large graph data-sets are heavily used. Fortunately, recent proliferation of parallel (e.g. multi-core CPUs and GPUs) and distributed (e.g. Amazon's EC2) computing environment has provided ways to exploit inherent parallelism in large graph data processing. However, it is still burdensome for a single programmer to implement graph algorithms correctly and efficiently while exploiting parallelism in a different way for each parallel or distributed environment. In this thesis, we present how this burden can be lightened up by the means of a Domain-Specific Language (DSL). First, we introduce Green-Marl, a domain specific language which allows the users to program their graph algorithms in an intuitive manner. However, the language is also designed in such a way that the underlying data-parallelism in the given graph analysis program is easily exposed to the Green-Marl compiler. Then, I will explain how the compiler can exploit such high-level semantic information to optimize the given user algorithm and to produce an efficient parallel implementation out of it. Experimental results show that the compiler-generated codes are as efficient as hand-coded versions in parallel graph libraries. Next, we explain how the Green-Marl compiler can produce an implementation for a distributed environment from the same Green-Marl program. Again the Green-Marl compiler uses high-level semantic knowledge to transform the given Green-Marl program into another one which is based on completely different programming model. Again the performance of compiler-generated code closely matches with hand-coded version. In summary, I show that the Green-Marl DSL can provide benefits of productivity, performance and portability to the users in the domain of large graph analysis.

Keywords: Electrical Engineering.
Advisor: Olukotun Oyekunle Ayinde primary advisor. Thesis advisor
Kozyrakis Christoforos
Leskovec Jurij advisor. Thesis advisor
The group-lasso [electronic resource] : two novel applications

In the first application, we introduce a method for learning pairwise interactions in a manner that satisfies strong hierarchy: whenever an interaction is estimated to be nonzero, both its associated main effects are also included in the model. We compare our method with existing approaches on both simulated and real data, including a genome wide association study, all using our R package glinternet. The second application is about recovering neural source activity in the visual cortex using non-invasive electroencephalography (EEG) recordings from sensors placed around a subject's head. We show that the group-lasso outperforms the widely-used minimum norm inversion, and that the group-lasso performance improves with the number of subjects. We also show that averaging the estimated source activity within appropriately defined regions of interest (ROIs) in the visual cortex across multiple subjects is able to dramatically boost the performance of both the minimum norm and group-lasso solutions, and also improves with the number of subjects.

Keywords: Statistics.
Advisor: Hastie Trevor primary advisor. Thesis advisor
Taylor Jonathan E. advisor. Thesis advisor
Tibshirani Robert advisor. Thesis advisor
Guaranteeing safe online machine learning via reachability analysis [electronic resource]

Reinforcement learning has proven itself to be a powerful technique in robotics, however it has rarely been employed to learn in a hardware-in-the-loop environment due to the fact that spurious training data could cause a robot to take an unsafe (and potentially catastrophic) action. This thesis proposes a method for overcoming this limitation known as Guaranteed Safe Online Learning via Reachability (GSOLR), in which the control outputs from the reinforcement learning algorithm are wrapped inside another controller based on reachability analysis that seeks to guarantee safety against worst-case disturbances. After defining the relevant backwards reachability constructs and explaining how they can be calculated, the thesis formalizes the concept of GSOLR and shows how it can be used on both a simple simulated inverted pendulum example and a non-simulated target tracking problem, in which an observing quadrotor helicopter must keep a target ground vehicle with unknown (but bounded) dynamics inside its field of view at all times, while simultaneously attempting to build a motion model of the target. Extensions to GSOLR are then presented, which allow the safety of the system to automatically become neither too liberal nor too conservative, thus allowing the machine learning algorithm running in parallel the widest possible latitude while still guaranteeing system safety. These extensions are also demonstrated on the inverted pendulum example as well as a practical example, namely that of safely learning an altitude controller for a quadrotor helicopter. These examples demonstrate the GSOLR framework's robustness to errors in machine learning algorithms, and indicate its potential for allowing high-performance machine learning systems to be used in safety-critical situations in the future.

Advisor: Tomlin Claire J.
Fedkiw Ronald P.
Latombe Jean-Claude advisor. Thesis advisor
G-valued flat deformations and local models [electronic resource]

We construct resolutions of G-valued local Galois deformation rings by moduli spaces of Kisin modules with G-structure when l = p. This generalizes Mark Kisin's work on potentially semi-stable deformation rings. In the case of flat deformations, we prove a structural result about these resolutions which relates the connected components of G-valued flat deformation rings to the connected components of projective varieties in characteristic p, which are moduli spaces of linear algebra data. As a key step in the study of these resolutions, we prove a full faithfulness result in integral p-adic Hodge theory. We also generalize results of Pappas and Zhu on local models of Shimura varieties to groups arising from Weil restrictions.

Keywords: Mathematics.
Advisor: Conrad Brian
Vakil Ravi advisor. Thesis advisor
Venkatesh Akshay