VictorJuiz/thesis huggingface dataset:
Graphical processing unit accelerated state-averaged complete active space self-consistent field for large-scale quantum dynamics simulations [electronic resource]
Keywords: Chemistry.

Photochemical reactions typically occur under nonequilibrium conditions on the femtosecond to picosecond timescale. In many cases, the nonequilibrium dynamical behavior of the system has a significant impact on the reaction, and statistical and reaction path methods are unreliable for their study. As a result, nonadiabatic dynamics simulations are important for the study of photochemistry. The most generally applicable and flexible approach is based on ab initio molecular dynamics, where the electronic Schrödinger equation is solved alongside the dynamics to obtain the required potential energy surfaces and nonadiabatic couplings as needed. However, these ab initio nonadiabatic dynamics simulations are computationally expensive. In particular, the necessary electronic structure calculations are the computational bottleneck, exhibiting both a high prefactor and unfavorable scaling behavior. This scaling is especially unfavorable for systems that cannot be well described by a single electronic configuration, and the multiconfiguration/multireference methods needed to describe these electronic excited states have been limited to small molecular systems. We alleviate this problem by implementing graphical processing unit (GPU) accelerated state-averaged complete active space self-consistent field (SA-CASSCF). Our algorithms are ~10-100x faster than the nearest competitive code and exhibit effective scaling of O(N^2), versus formal scaling of O(N^4). We will show how SA-CASSCF response properties, including nuclear gradients and nonadiabatic coupling vectors, can be efficiently computed for arbitrary, tractable active spaces. To demonstrate the utility of this development to nonadiabatic dynamics simulations, we have applied GPU accelerated SA-CASSCF coupled to ab initio multiple spawning (AIMS) to unravel the photodynamics of provitamin D3, the largest simulation of its kind. Finally, we will discuss how empirical corrections can be employed to bring SA-CASSCF simulations into close agreement with more sophisticated, but computationally intractable, multireference electronic structure methods, further expanding the utility of the SA-CASSCF method.
Hard to Judge: Deception and Trust in Virtual Representation Media
Keywords:  Department of Communication
Virtual reality
avatars
deception
lies
trust
presence
Thesis

How do people deceive one another in virtual reality? This question is not easily answered, for virtual reality has only recently been studied, and interactivity within virtual reality has yet to be perfected. A great deal of work has been done to understand how human beings lie to and trust one another, and researchers have sought to understand how mediated communication affects this deception and trust. To explore how users would likely deceive one another in virtual reality, this paper examines theories of computer-mediated communication (CMC), as well as studies of deception and trust across different forms of media. Drawing on these theories and findings, analysis suggests that virtual reality functions both as real life and as an avatar-mediated form of communication. With an adequate level of presence within the medium, users act as human beings in real life, relying on nonverbal and social cues, all while using the shield of anonymity behind their virtual avatars.
Hebbian-LMS algorithm and its application to clustering [electronic resource]
Keywords: Electrical Engineering.

The Hebbian-LMS algorithm is a new unsupervised learning algorithm of an artificial neuron. It comes from the combination of two important concepts: Hebbian learning in neurobiology, and the Least Mean Square algorithm in signal processing. Hebbian learning is widely accepted as a basic theory of synaptic plasticity, which is essential for learning and memory in the human brain. The Least Mean Square algorithm is also widely used in many engineering areas, such as channel equalization or machine learning. The Hebbian-LMS algorithm is simpler and more biologically plausible than other training algorithms of artificial neural networks because the training of each artificial neuron takes place locally following Hebbian learning theory. Thanks to the simplicity, it is easy to apply the Hebbian-LMS algorithm to complicated artificial neural network structures, and the Hebbian-LMS clustering algorithm is introduced on multiple-layer artificial neural networks. It is shown that more artificial neurons and more layers improve the result of the Hebbian-LMS clustering algorithm. Furthermore, the Hebbian-LMS clustering algorithm is tested for various synthetic and real datasets to show that it is a decent clustering algorithm.
High brightness electron beams for fourth generation light sources [electronic resource]
Keywords: Physics.

In this dissertation, we examine the production and preservation of high brightness electron beams for fourth generation light sources. The relentless push toward brighter photon pulses from Free Electron Lasers (FELs) has been facilitated by an increase in the brightness of the driving electron beam. One method of increasing this brightness is to provide an electron beam which is pre-bunched at the FEL wavelength, thereby providing a fully coherent seed for the lasing process. We explore the technique of Echo-Enabled Harmonic Generation (EEHG) to seed the electron beam at a high harmonic wavelength of a conventional, fully coherent laser pulse. We build on the previous work at the Next Linear Collider Test Accelerator (NLCTA) to extend the harmonic up-conversion via EEHG to the 75th harmonic and demonstrate the ability to create multi-color, tunable bunching spectra using a chirped electron beam and the EEHG technique. We also examine with detailed numerical simulations the interplay between the microbunching instability and EEHG. Additionally, we develop a theoretical model for a novel source of emittance degradation due to a stochastic addition to the standard Coherent Synchrotron Radiation field. This effect is found to grow with both electron beam energy and density, potentially limiting the ultimate brightness of some electron beams. Physically, the effect is found to be due to the stochastic scattering of electrons off the narrow-angle synchrotron radiation cones of other electrons as they traverse a bend magnet. This novel effect is another manifestation of the difficulties posed as the electron beam brightness is continually increased.
High Fidelity: Virtual Avatar Interaction
Keywords:  Department of Communication
High Fidelity Avatar
Stanford University Virtual Human Interaction Lab
virtual space
avatar interaction
linguistics
communication
Thesis

In a high fidelity virtual space, two random paired participants were placed in one of three scenarios varying in levels of immersion. Some participants had control of the avatar's hands, while others did not. After the avatar interaction, participants recorded responses about their experience. These recordings were transcribed and analyzed via LIWC (Linguistic Inquiry and Word Count). The means and standard deviations of word count, affect, positive emotion, and negative emotion from the responses were examined. According to this data, there does not appear to be a direct relationship between avatar control and user affect and emotion.
High-efficiency low-jitter silicon-based single photon avalanche diodes (SPADs) [electronic resource]
Keywords: Electrical Engineering.

Single-photon detectors are known for high sensitivity and picoseconds timing resolution (i.e., low jitter). They have been widely used to push the frontiers in both academic research and industrial products for depth sensing (e.g., LiDAR), quantum key distribution, single-molecule fluorescence, and bio-medical imaging. Among single-photon detectors, Si-based SPADs have gained interest due to their low cost, compact form factor, ease of integration, and compatibility with standard CMOS fabrication techniques. However, in the near-infrared regime of interest (750 nm to 1 μm wavelength), these devices suffer from a clear trade-off between the detection efficiency and jitter due to low optical absorption in silicon. In order to break this trade-off, a Si-SPAD with light trapping effect is demonstrated to significantly improve efficiency at a small jitter. The working principle is to make photons propagate horizontally within the device layer to increase the absorption length. This dissertation mainly focuses on prototyping of light trapping SPADs. After an overview of motivation and physics behind Si-SPADs, we model the SPAD performance in a Monte Carlo simulation to validate and optimize the design. Then, we discuss the fabrication processes starting from material epitaxy. Since nano-structures on SPAD surfaces are a critical component to induce light trapping, we have developed techniques (photoresist reflow and TMAH wet etch) to create nano-structures in a low-cost and CMOS-compatible method. Following fabrication, single photon characterization is performed. We have achieved a 2.5-fold improvement of detection efficiency in the near infrared regime (32% at 850 nm wavelength), while the jitter remains 25 ps. The result proves that we successfully break the current trade-off of Si SPADs. In addition, we have improved efficiency of Si-SPADs in the ultraviolet wavelength regime by creating a gradient doping profile to better collect carriers generated close to surface. The doping profile is achieved by boron vapor phase doping in our epitaxy chamber. After this, an imaging application for Si SPADs is demonstrated, where we record the transient images of light propagating within objects on a 300 ps time scale.
High-frequency thermoacoustic engines [electronic resource]
Keywords: Electrical Engineering.

Thermoacoustic engines are devices capable of converting external heat sources into acoustic power, which in turn can be converted to mechanical or electrical power. Thermoacoustic engines typically operate at frequencies of 100 Hz or lower; however, power density scaling suggests that arrays of smaller, high-frequency engines can be an attractive heat engine technology. This work presents several advances towards the design and optimization of high-frequency thermoacoustic engines. A 400 Hz piezoelectric-thermoacoustic engine is comprehensively modeled using Navier-Stokes and linear acoustics codes, with results in good agreement with experimental data. A piezoelectric diaphragm allows the complete thermoacoustic engine system to convert energy with no moving parts. A model for bulk viscosity is presented, and values from the model allow both Navier-Stokes and lattice Boltzmann solvers to accurately capture acoustic attenuation due to molecular relaxation effects across a broad range of frequencies. Molecular relaxation effects are the dominant attenuation source at higher frequencies; it is shown that relaxation has reduced effect in the thermoacoustic cycle, but can affect attenuation in other acoustic components. The geometry of a 25 kHz engine is presented, and optimization of the engine for geometry, pressure, bulk viscosity attenuation, and thermoacoustic core construction is performed using a combined Navier-Stokes and linear thermoacoustics framework. A 3D printed 3 kHz thermoacoustic engine is designed and constructed, with corresponding experimental results.
Hippocampal CA2 Place Cell Remapping and Cell Firing Field Modifications in Response to a Social Stimulus
Keywords:  Department of Biology
Biology
neurobiology
hippocampus
CA2
place cell
Thesis

The CA2 region of the hippocampus plays a vital role in the storage and recall of social memory in mice, but the neural mechanism for this memory storage remains unknown. While the CA2 region remained largely unstudied for years, recent findings give evidence that this region is necessary for social memories to form, and CA2 pyramidal cells contain the machinery necessary to function in social memory. Place cells are a specific type of pyramidal cell found in the CA2 of the hippocampus, and previous research links them to involvement in social memory. This study’s goal was to investigate if place cells are responsible for the CA2’s role in social memory and to identify specific mechanisms that place cells may use to store this information. To analyze the properties and changes that occur in place cells in the presence of a social stimulus, tetrodes, small wire-devices used to record from live cells, were implanted into the mice hippocampi to record from CA2 place cells while the mice underwent controlled-environment, social-stimulus behavioral experiments. This research revealed that in social situations CA2 place cells coherently remap as subpopulations and reduce the mean firing field size. These data reveal that place cells in the CA2 of the hippocampus do, in fact, respond to social stimuli in a way that is typical for hippocampal cells encoding memory in mice and gives insight into how these cells may function in storing this social information. In addition to expanding our knowledge of the CA2 region of the hippocampus, a better understanding of social memory can lead to a better understanding of diseases that affect social memory or cause damage to the hippocampus, such as Autism.
Holistic strategies for prediction uncertainty quantification of contaminant transport and reservoir production in field cases [electronic resource]
Keywords: Energy Resources Engineering.

In this dissertation, it aims to tackle prediction uncertainty reduction and quantification in complex subsurface problems. Examples of such problems are reactive contaminant transport prediction or reservoir production prediction using time lapse (4D) seismic data. Strategies developed within this dissertation will help practitioners to answer the following questions: (1) what field data to acquire at initial stage and how to determine that; (2) how to build appropriate prior model set, falsify such prior and validate posterior prediction; (3) what is an effective method to build statistical relationships between spatial data and prediction variables. Strategies are applied to a uranium remediation problem in a real field case and a reservoir management problem involving time lapse seismic data. Firstly, a sensitivity-based method is introduced to determine informative data to acquire before going to the field. It is demonstrated in the pre-field data assessment step in both the uranium remediation and reservoir prediction application. Secondly, a model scenario falsification method using spatial data, such as time lapse seismic data, is demonstrated. This method is also used to evaluate appropriate distance measures for distance based sensitivity analysis. The analysis of different distance is demonstrated in a synthetic reservoir case. In addition, this thesis introduces two novel dimension reduction techniques for spatial variables, which are crucial steps in scenario falsification and sensitivity analysis. Lastly, strategies are deployed in two field cases to demonstrate their efficacies.
Holographic duality and random tensor network [electronic resource]
Keywords: Physics.

Holographic duality is a proposed correspondence between quantum many-body systems living on the conformal boundary of an asymptotically anti-de Sitter space and the quantum gravity living in one higher dimension in the bulk. A particularly interesting aspect of this duality is played by the quantum entanglement. According to the Ryu-Takayanagi formula, the entanglement entropy of a boundary region corresponds to the area of the minimal surface bounding this region, which agrees with the entropy properties of the tensor network states. This dissertation aims to build concrete relations between the holographic duality and the tensor networks. We first propose the concept of the bidirectional holographic code, which means all the boundary states can be represented in the bulk while the states within a constrained code subspace play the role of "classical geometries". We implement the bidirectional holographic code explicitly using the random tensors, which generates a class of solvable tensor network models that reproduce many properties of the holographic duality. We further generalize the random tensor network approach to allow quantum superposition of di erent spatial geometries, which moves one step towards the quantum description of the gravity theory. Lastly, we study the dynamical properties in the holographic duality using the tensor networks and find that the quantum error correction properties bridge the light-cone structure in the bulk and the buttefly velocity (i.e. the speed of chaos propagation) on the boundary.
Honor and Tyranny: A Theoretical Analysis of Contemporary Russia's Objectives in the Middle East
Keywords:  Center for Russian Eastern European and Eurasian Studies
Center for Russian Eastern European and Eurasian Studies
Stanford University
Putin
Russia
Middle East
Iran Iraq War
Political Philosophy
Plato
Aristotle
Thucydides
Xenophon
National Security
American Foreign Policy
Middle East
Global Studies
Thesis

This thesis analyzes contemporary Russian Middle Eastern statecraft, for the purposes of American foreign and national security policy, within the framework of ancient Athenian discourse concerning political philosophy. It lays out its fundamental theoretical assumptions provided classical thought, seeks to define what exactly Putin's regime is on those terms, and then applies that analysis to Russian Near Eastern policy. It posits that, according to these theoretical premises, the basis of politics and political life is ethical, not ideological. Thus grasping the ethical basis of any given political regime is essential to understanding how and why it interacts with other regimes. Provided those assumptions it seeks to determine what the ethical basis of Putin's regime is on classical terms. It determines that in the classical understanding of political life, Putin's regime is a tyranny that justifies its claim to rule by its pursuit of honors, national greatness and victory. It argues that in the classical sense, Putin's is a very particular form of statesmanship. When applied to foreign policy, this inquiry determined that Russia's recent aggressiveness in the Middle East is driven first and foremost by its regime's need to challenge the Post Cold War international system, and specifically, to thwart the reach, influence and policies of the United States. Stated succinctly, Putin's regime regards the Middle East as a theater in which it can effectively discredit the authority of the Post Cold War international system, and specifically, American leadership of it. This analysis argues that this is the preeminent reason that Putin's regime has taken such an interest in the region. In addition to establishing its theoretical bases, this analysis also engages in a historical analysis by drawing a comparison between contemporary Russian Middle Eastern foreign policy, and that of the Soviet Union during the Iran Iraq War. It concludes with a recommendation to US policymakers and officials to regard the intent behind Russian foreign policy in this part of the world as specifically inimical to their interests and their policies.
Host-rock deformation around magmatic dikes [electronic resource] : integrating field observations and mechanical models
Keywords: Geological Sciences.

Dikes are the dominant form of magma transport within the earth's shallow crust. At basaltic volcanoes, dikes commonly initiate at a central magma reservoir and propagate laterally for distances that are much greater than their heights. Because vertical propagation is more limited, most dike intrusions fail to reach the surface (Klein, 1982; White et al., 2006). Dikes that do intersect the surface feed eruptions through fissures, or linear volcanic vents. Fissure eruptions tend to be relatively short-lived (hours, days) because magma flow through sheet-like conduits is thermally unfavorable (Delaney and Pollard, 1982). However, flow in fissures commonly localizes into discrete vents that eventually form a cylindrical-shaped conduit known as a volcanic plug, at which point the eruption can sustain significantly greater volumetric flow rates and can persist for longer periods of time (months, years) (e.g. Richter et al., 1970). Therefore, in order to assess the volcanic hazard of a dike intrusion event, it becomes necessary to know first whether the dike will propagate to the surface and initiate an eruption, and then whether the fissure eruption will be short-lived or sustained through a larger conduit. The physical processes that govern dike propagation to the surface and the transition of fissures into volcanic plugs all involve deformation of the surrounding rocks that host the dike or fissure. This dissertation integrates geologic observations with physics-based models to gain new insight about deformation and the state of stress in host rocks as they relate to dike propagation and the evolution of conduit geometry.
The house of tudor [electronic resource] : a diversity of functionally critical arginine methylation sites in endogenous RNA interference
Keywords: Genetics.

The discovery of RNA interference (RNAi) was a doubly significant event in that it not only ushered in a new era of technical capability to specifically silence genes in a wide range of experimental contexts, but it also opened a new field of inquiry: the endogenous function of RNAi factors. Many of these functions have now been well characterized, but others remain stubbornly obscure and even controversial. In recent years, the discovery of the CRISPR bacterial and archaeal immune systems has had a dual impact on the biological sciences comparable to RNAi. Dramatically improved genome editing with CRISPR-derived techniques has been accompanied by a flurry of studies concerning the mechanism of CRISPR-based immunity. The ability to edit the genome of an organism is one of the most potent experimental tools in genetics. The rapid spread of CRISPR technology has enabled a profusion of highly precise genetic experiments in a wide variety of organisms. However, while the technology is powerful and efficient, it has limitations. A third development in the modern era that has revolutionized biology is the advent of next generation sequencing technologies. These methods make possible a large variety of assays, and in particular, they allow sequencing and characterization of small RNA populations that participate in endogenous RNAi. Here, I present my work to develop and improve CRISPR/Cas9 genome editing in Caenorhabditis elegans, as well as subsequent studies using the method, in conjunction with small RNA-seq, to elucidate the enigmatic endogenous role of RNAi.
How large scale cell-phone (and other) non-probability polling, big data, and advanced algorithms can inform our understanding of vote intention [electronic resource]
Keywords: Communication.

Response rates for representative telephone surveys are in decline, at the same time, face-to-face surveys are increasingly difficult and expensive to conduct. This dissertation makes a case for the usability of non-representative survey data. Chapter 1 gives some background on the history of political polling, and highlights the advantages of newer modes of non-representative data collection - mobile, online, or via gaming systems. Chapter 2 introduces survey data collected via mobile applications, and highlights the numerous advantages this data brings to the table with a focus on ambient data, specifically location data. Chapter 3 documents how this mobile data can be used to forecast the Presidential elections in 2016 accurate. Chapter 4 makes use of the scale and time-granularity non-representative polling data allows researchers to consider by investigating the causal effect of ad spending on vote intention at the more meaningful aggregate level, finding that ad spending in the last six weeks, when the campaign is in full swing, backfires. In concluding, I highlight the advantages of survey data collected via non-representative means for (campaign) practitioners and academics alike.