VictorJuiz/thesis huggingface dataset:
Scrambling, pulses, and networks in quantum information theory

Quantum information theory is a project to quantize the mathematical theory of information. In this thesis we establish a few results. The first evaluates a proposal for an information-theoretic definition of scrambling in quantum systems, including systems of interest in quantum gravity and quantum many-body physics. In particular, this definition quantifies scrambling, and we prove what this quantity says about a quantum system. The second establishes how much information can be transmitted by a quantum channel per unit cost, where the cost may not be time but something else, for instance energy or number of photons. We provide protocols to communicate at the optimal cost efficiency using pulses. The third gives achievable information rates in a quantum communication network. We prove this result using a recent theorem on quantum joint typicality and demonstrate its use by attaining achievable rates for the quantum relay channel.

Keywords: Applied Physics.
Advisor: Hayden Patrick (Patrick M.)
Mabuchi Hideo 
Safavi-Naeini Amir H.
Scripting Social Learning: Investigating Students’ Perceptions of Social Constructivist Learning in Minerva’s Online Learning Environment

This thesis investigates the tension between promoting accessibility and utilizing social constructivist pedagogies to produce insights about effectively scripting collaboration in a computer-supported collaborative learning environment. Through the lens of student perceptions, I explore the educational model of Minerva Schools at KGI, a new blended higher education institution which uses a proprietary platform to deliver small discussion-based classes while requiring students to live together in residential cohorts. Minerva’s classes employ “active learning” pedagogies which use tracked and graded collaborative participation to actively engage students in class sessions. I assessed 67 students’ perceptions of the presence of social constructivist pedagogy in Minerva’s platform using the Constructivist On-Line Learning Environment Survey. Further, critical incident interviews offered insight into the experiences of 20 students learning on the platform with particular attention paid to productive and unproductive social learning incidents. Findings indicate that though students perceived a strong learning community overall, they perceived social distance and artificiality in the online learning environment specifically. Strict collaborative scripting offers partial explanation for this disconnect. However, students also reported that scripting improved the classroom discourse at times by creating opportunities to participate in class for students who otherwise would not participate. Results can inform the direction of future research in the evaluation of CSCL environments as well as the design of collaborative scripts which both scale and accommodate underrepresented students.

Keywords: social constructivism
computer-supported collaborative learning (CSCL)
scripting collaborative learning
active learning
higher education
accessibility
Graduate School of Education
Thesis
Advisor: Pea Roy
Willinsky John
Harrison Monique
Search for optimal CNN architectures incorporating heterogeneous inputs for short-term solar PV forecasting

Cloud movement makes forecasting output from solar photovoltaic (PV) panels extremely challenging. This is a growing source of concern for electricity grid operators, responsible for ensuring that supply meets demand at every instant. A better solar PV forecast can realize value for commercial and industrial customers with solar assets. In this study, we aim to build a Convolutional Neural Network (CNN) based model to forecast power output from solar PV panels 15 minutes into the future. The inputs to the model are the power output history from PV panels and ground-based sky images for the past 15 minutes.
The key challenge is ensuring that due importance is given to each type of input. A stack of 16 historical sky images with 64 x 64 spatial resolution and 3 color channels contains 196,000 numbers while 16 historical power outputs are simply 16 numbers. If these heterogeneous inputs are not carefully integrated, the prediction error obtained by using two sources of inputs can be worse than using just one of them. Also, with deep learning architectures, there are many independent variables to tune. Limited computing time and resources prevent us from conducting an exhaustive search across all possible combinations.
In this study, we explore 28 total architectures for combining heterogeneous data inputs. We do so while devising and following a simple, yet systematic, design of experiments & analysis pipeline. Through a three-stage “funnel” approach we narrow our search to the most promising of the 28 architecture options. We find four best-in-class architectures, one for each of four major methods for heterogeneous data fusion. We test these methods on a larger dataset and find that a two-step model based on autoregressive (AR) forecasts has the best performance. This architecture has a forecast skill of 17% relative to smart persistence on the test set comprising of 9 complete sunny days and 11 complete cloudy days spread across a year. We hope our general process will be generalizable to machine learning applications beyond solar forecasting.

Keywords:  Energy Resources Engineering
School of Earth Energy &amp; Environmental Sciences
Energy Resources Engineering
Solar forecasting
Convolutional Neural Networks
Machine Learning
Deep Learning
Thesis
Advisor: Brandt Adam
Search of the Higgs boson produced through vector boson fusion decaying to a pair of bb with the ATLAS detector

This thesis presents the search of the Higgs boson produced by Vector Boson Fusion (VBF) and decaying to bottom quarks. A search using the ATLAS detector was performed with 2016 proton-proton collision data. The multi-variate analysis measured the signal strengths of both the inclusive Higgs production and the vector-boson fusion production relative to the Standard Model prediction. This analysis led to the observation of Higgs coupling to b-quarks in the summer of 2018. Furthermore, potential improvements of the analysis techniques using complex neural networks are investigated. In order to understand better the Quantum Chromodynamics (QCD) backgrounds of the Higgs search, the characteristic variables of the gluon splitting vertex are measured.

Keywords: Physics.
Advisor: Tompkins Lauren Alexandra
Schwartzman Ariel G.
Su Dong
Searching For Stability Amid Residential Instability: Exploring the Role of Resilience and Social Capital in Higher Education Attainment for Homeless Adolescent Youth

This study explores the experiences of homeless adolescent youth and the factors that allowed them to achieve positive educational outcomes through a strengths-based resilience and social capital framework. This study aims to 1) understand how students who have been subject to homelessness and attend highly-selective colleges perceive the impact of residential instability on their educational experiences during adolescence and 2) uncover the strategies and resources homeless adolescents may employ to successfully achieve access to higher education.
The sample population is comprised of Stanford students who have experienced homelessness in their adolescence, as they represent extremely at-risk, yet resilient youth that were still able to gain admission to a selective university that primarily admits and serves students from backgrounds of extreme wealth, education, and stability. Using a qualitative approach, data were collected through semi-structured in-person interviews that were conducted with a final sample of 9 undergraduate Stanford students who have experienced homelessness in their adolescence. Through evaluating the narratives and perceptions of formerly homeless students that were able to successfully gain admission to a selective university, I found that educational motivation, sense of stability, and positive social capital are key factors in a homeless youth’s ability to achieve positive educational outcomes. The stability and agency found in their education pushed these students to find non-traditional ways to access resources and knowledge through their social relationships, which afforded them the ability to navigate their educational paths, giving them an advantage over other residentially insecure students who remained vulnerable to the risks associated with homelessness. In addition to highlighting the need to support homeless youth in their educational goals and importance of increasing access to higher education, these findings demonstrated a continued need of academic, mental, and social support for formerly homeless youth when they enter college.

Keywords: Graduate School of Education
Stanford University
homeless youth
housing instability
access to higher education
social capital
educational resilience
first-generation and/or low-income
FLI
first-generation college student
educational equity
Thesis
Advisor: Padilla Amado
Sedimentology, Stratigraphy and Provenance at Bolsa Point, Pigeon Point Formation, California, USA

The Cretaceous Pigeon Point Formation (PPF) outcrops for about 16 km along the San Mateo County coast in central California, southwest of the San Andreas Fault. The PPF has been interpreted to have been deposited by a combination of high- and low-density turbidity currents, debris flows, and slumps and slides and is thought to represent a submarine canyon and fan complex. This study focuses on a section of the PPF exposed north and south of Bolsa Point that has been interpreted to represent a shallow-marine depositional setting and the youngest strata in the PPF. The objective of this study has been to determine the depositional processes, age and environment of deposition of the outcrops at Bolsa Point. The outcrops of the PPF exposed at Bolsa Point are mostly fine-grained sandstone beds which are dominated by current structures, burrowed intervals and hummocky cross-stratification. Fossils found at Bolsa Point in addition to the observations mentioned above indicate that this section of the PPF was indeed deposited in a shallow, perhaps storm-dominated submarine setting. Additionally, we evaluated petrography and geochemistry to determine the composition and provenance of Bolsa Point member. Turbidite sequences often act as reservoir rocks for hydrocarbons. Although no hydrocarbon is present in this area, gaining a better understanding of the PPF will contribute to worldwide petroleum exploration.

Keywords: Geological sciences
sedimentology
stratigraphy
Pigeon Point
California
geology
shallow marine
Thesis
Advisor: Lowe Donald
Seismic full waveform inversion : nonlocal similarity, sparse dictionary learning, and time-lapse inversion for subsurface flow

I present three topics in the area of theoretical development and application of Full Waveform Inversion (FWI). The first topic or contribution describes a learning-based adaptive and sparsity promoting regularization method to improve the accuracy of traditional FWI results with the prior knowledge of nonlocal similarity in geological structures. Such a priori is realized by multi-class orthogonal dictionary learning. The second topic extends the learning-based regularization to elastic waves and applies the approach to a field dataset to estimate P-wave and S-wave velocities. This topic highlights the importance of data pre-processing and modification of the FWI algorithm to accommodate field data issues such as radiation pattern estimation, wavelet estimation, and amplitude scaling. The aim of this part is high-resolution reservoir characterization, which is not only an extension of the technique in the first part but also serves as a preparation for the time-lapse inversion in the third part. In the third topic, I describe a framework for using FWI to estimate hidden parameters that are important to geophysical processes such as fluid flow in porous media. This framework extends the power of FWI beyond seismology to other geophysical problems such as reservoir engineering and hydrology by combining seismic observations, rock properties modeling, and flow modeling. This third topic represents a PDE-constrained inverse problem that I solve with an intelligent automatic differentiation method. The method provides three levels of user control with (1) built-in differentiable operators from modern deep-learning infrastructures, and customized operators that can either (2) encapsulate analytic adjoint gradient computation or (3) handle the forward simulation and compute the corresponding gradient for a single time step. This intelligent strategy strikes a good balance between computational efficiency and programming efficiency and would serve as a paradigm for a wide range of PDE-constrained geophysical inverse problems.

Keywords: Geophysics.
Advisor: Harris Jerry M. 
Biondi Biondo
Mukerji Tapan
Selecting and sequencing clonally expanded CD8+ T cells

The immune system is tasked with detecting and neutralizing infectious organisms to maintain homeostasis and prevent disease. This defense is managed by complex coordination of many cell types. CD8+ T cells are responsible for recognizing infected cells and killing them. To permit the recognition of antigens, T cells generate a vast diversity of T cell receptor (TCR) sequences. Upon binding of the TCR to an antigen-MHC complex, T cells clonally expand to establish an immune response. To study antigen-specific T cell clonality, we have developed a method that allows selection of rare cells, based on RNA expression, prior to in-depth scRNA-seq (named SELECT-Seq). We applied SELECT-Seq to collect both TCR sequences and then transcriptomes from single cells of peripheral blood lymphocytes activated by a Mycobacterium tuberculosis (Mtb) lysate. TCR sequence analysis allowed us to preferentially select expanded conventional CD8+ T cells as well as invariant natural killer T (iNKT) cells and mucosal-associated invariant T (MAIT) cells. The iNKT and MAIT cells have a highly similar transcriptional pattern, indicating that they carry out similar immunological functions, and differ considerably from conventional CD8+ T cells. While there is no relationship between expression profiles and clonal expansion in iNKT or MAIT cells, highly expanded conventional CD8+ T cells downregulate the interleukin-2 (IL-2) receptor alpha (IL2RA, or CD25) protein and show signs of senescence. This suggests inherent limits to clonal expansion that act to diversify the T cell response repertoire.

Keywords: Genetics.
Advisor: Steinmetz Lars 
Davis Ronald W. (Ronald Wayne)
Montgomery Stephen
Snyder Michael
Self-Defense in Microbiology: The Interplay Between Vaccines and Antimicrobial Resistance

As with all organisms, humans and microbes must adapt to changing environments to survive. Microbes achieve alarmingly high rates of evolution due to their strength in numbers, leading to a phenomenon known as antimicrobial resistance. Vaccines represent a form of “artificial evolution” that allows humans to compete with these microbes. Vaccines possess the ability to offer a more long-term solution to combatting infectious diseases via herd immunity and eradication (e.g. global eradication of smallpox). This thesis will investigate the relationship between vaccines and antimicrobial resistance through an analysis and synthesis of scientific articles, policy reports, news reports, academic works, and in-person interviews. Through a case study of my own research and development of a vaccine against a virulence factor of Pseudomonas aeruginosa (a bacterium recently declared a critical priority pathogen by the World Health Organization due to antibiotic resistance), this thesis will highlight the feasibility and efficacy of developing a vaccine against an antibiotic-resistant pathogen. By doing so, the case study will lead into an analysis of the existing sociological, political, and economic barriers that are preventing the wide-scale research and development of vaccines against antimicrobial resistant pathogens. The discussion will conclude with propositions for research-, policy-, and education-based reforms that will allow vaccines to more effectively address antimicrobial resistance. This thesis intends to shift the global conversations regarding antimicrobial resistance to incorporate the research and development of vaccines as a crucial component to targeting resistance.

Keywords:  Technology
Infectious Diseases
Vaccines
Antimicrobial Resistance
Antibiotic Resistance
Microbiology &amp; Immunology
Biomedical Ethics
Sociology of Medicine
The Program in Science Technology and Society
Thesis
Advisor: Dr. Sandra S. Lee
Dr. Kyoko Sato
Dr. John Willinsky
Joo Ae Chu
Emily Van Poetsch
Rose Davis
Ipshita Sengupta
Servers and Sovereignty: Explaining the Rise of Data Localization Laws

As lives around the world become increasingly digital, governments are seeking new ways to control and commercialize the new wealth of available information. One manifestation of these efforts are data localization laws, which require that data be stored on servers within national borders. While over thirty countries around the world enforce data localization policies of some form, research indicates that data localization often does not achieve its stated objectives to facilitate economic growth, protect against foreign surveillance and make data more secure. Given the scholarship that suggests data localization does not fulfill these economic and security motives, why are states still using territory as a means of dictating where information should physically be located? This thesis presents a unique analysis of the motivations behind data localization, with a focus on democracies. I argue that a threat to state sovereignty, provoked by foreign ownership over data, motivates states to consider data localization. However, these laws are more likely to pass in states seeking to consolidate domestic power. Analysis of policies in Brazil, India, Indonesia, Vietnam and Canada provide support for this theory. The membership of domestic policymaking bodies and the economic influence of a state are two other notable factors identified in the research that can affect the success of proposals to localize data. Overall, this research suggests that while data localization has serious implications for the international economy and human rights, anti-data localization efforts need to better account for the sovereignty concerns of states considering these policies.

Keywords: Center for International Security and Cooperation
cyber
data
human rights
internet policy
international relations
Thesis
Advisor: Grotto Andrew
Cohen David
Sex positive political theory : pleasure, power, public policy and the pursuit of sexual liberation

Liberal political theorists, most notably Jeremy Bentham and John Stuart Mill, often frame sexual liberties as negative liberties. Negative liberties are construed as freedoms from external interference. As it pertains to sexual freedoms, negative liberty holds that consenting adults should be free to do what they want with their sexual capacities as long as no one is harmed. This position lays an important foundation for the protection of sexual rights for those in LGBTQ+ communities and other sexually marginalized groups. Negative liberty is often contrasted with what Isaiah Berlin calls positive liberty, which emphasizes giving people the freedom to pursue certain ends free from internal constraints. From the perspective of political institutions, promoting positive liberty involves governments giving the opportunities and resources necessary to exercise certain freedoms. In this dissertation I argue that sexual freedom should be considered as both negative and positive liberties. In particular, I identify two cases where negative liberty is insufficient to guarantee the meaningful enjoyment of sexual freedoms: sexuality education for minors and sexual health for people with disabilities who are capable of sexual consent. I show that in both cases, political institutions should treat sex and sexuality in terms of both positive and negative liberty. I further develop a conception of sexual equality whereby all individuals are entitled to be treated as sexual beings whose consensual sexual preferences and identities are worthy of respect and affirmation.

Keywords: Political Science.
Advisor: Satz Debra 
McQueen Alison (Alison E. J.) 
Reich Rob 
Segura Gary M.
Shared control of automated vehicles : supporting handovers of control

Road transport is central to maintaining our modern way of life. Currently, human drivers are responsible for almost all of the transport of goods and people on roads. However, recent advances in sensing, processing power and algorithms now support the possibility of automating all or part of the task of driving. No commercially available autonomous system is capable of handling all road situations and environments yet. Until such a system becomes available, drivers will need to be involved, at least occasionally, in the task of driving. Shared control of automation is a concept where a driver and an automated system simultaneously exert control over the vehicle. Such a system could be useful as a step towards fully automated driving, or as a method to support transitions of control to or from full automation. In this thesis, I survey the current literature on shared control systems and on handovers of control from automation to a driver. Then, I describe a series of studies investigating driver behavior during handovers of control and while using a shared control system. These studies investigate shared control over the lifetime of the handover - before, after and during it. I also describe the prototyping, development, and evaluation of multiple systems that support driver-automation cooperation. I introduce `Anticipatory Control', a steering system for automated vehicles that informs drivers of the steering plans of the automated system in advance, by moving the steering wheel before the road wheels. I show that this is useful in improving driver responses to automation failure. I describe a study that found that shared control improves driver performance after a handover. Finally, I describe and evaluate an implementation of Shared Control during a handover -- this system mediates a handover from automation by supporting the driver and making a real-time performance evaluation to determine driver readiness to take over. These studies lay the foundation for the use of shared control during transitions, and might in the future enable safer and more efficient handovers, improving road transport during society's transition to full automation.

Keywords: Mechanical Engineering.
Advisor: Ju Wendy
Leifer Larry J. 
Cutkosky Mark R.
Silicon photocathodes for dielectric laser accelerators

Particle accelerators are powerful tools with numerous scientific, industrial, and medical applications. Broad adoption of these systems is limited by the size and cost of conventional RF accelerator technology. Dielectric laser accelerators (DLA) are a nascent technology for charged particle acceleration with applications ranging from compact light sources, ultrafast electron imaging, therapeutic radiation generation, and semiconductor processing. Taking advantage of mature semiconductor fabrication techniques, DLA devices consist of dielectric nanostructures that use intense electromagnetic fields from ultrafast laser pulses to accelerate particles at gradients more than an order of magnitude larger than those of conventional RF cavities. Of considerable importance is the generation of electron beams with sufficiently small emittance and duration such that they can be coupled into the narrow vacuum channels of the DLA and closely matched to the laser pulse length for efficient acceleration. In this dissertation, the development of such photocathode sources using silicon nanofabrication methods for use in the first full DLA system here at Stanford is discussed

Keywords: Electrical Engineering.
Advisor: Solgaard Olav
Byer R. L. (Robert L.)
Harris J. S. (James Stewart)