VictorJuiz/thesis huggingface dataset:
Probing quantum criticality in an iron-based superconductor with symmetry-breaking strain
Keywords: Applied Physics.

In this thesis, I study the effect of the symmetry-preserving strain and the orthogonal antisymmetric strain to the critical temperature of the nematic phase transition (Ts) in a prototypical iron-based superconductor, BaFe2As2. The result establishes both strains as effective tuning parameters. This perspective is the utilized to systematically study the effect of these strain to Ts in the cobalt-doping series of BaFe2As2. A power-law behavior of the critical temperature was observed as a function of the combined tuning parameters, which is a linear combination the strains and the cobalt concentration. This provides the first clear evidence for power-law behavior of the critical temperature as a function of non-thermal tuning parameters. Lastly, I proposed an experiment that permits the measurement of the nematic susceptibility while continuously tuning the critical temperature with strain
Projection-based model order reduction for model predictive control of a descending aircraft
Keywords: Aeronautics and Astronautics.

The landing of an aircraft is one of the most important aspects of flight, and also one of the most difficult. This challenge is only amplified in the context of aircraft carrier landings, particularly in adverse flight conditions such as rough seas. Improving the quality of landing motivates the utilization of autonomy and therefore advanced methods for real-time control that account for uncertainty, as this would allow for better and more precise actions to be executed. Unfortunately, current autonomous landing methods are often based on low-fidelity computational models and do not account for non-ideal environmental factors, which limits their applicability. Model predictive control (MPC) methods informed by higher-fidelity computational models that are grounded in computational fluid dynamics (CFD), computational structural dynamics (CSD), and account for fluid-structure interaction (FSI), have a strong potential for significantly improving the technology of autonomous landing in adverse flight conditions. However, materializing this potential requires first addressing the issue that high-fidelity computational models are typically high-dimensional, and therefore impractical for real-time MPC. This thesis rises to the challenge by developing a computational framework for developing a real-time FSI computational technology grounded in CFD, CSD, and projection-based model order reduction. Specifically, the thesis proposes a two-level, data-driven concept for the autonomous landing of aircraft. It features a robust approach for model predictive control; and an innovative, real-time, computational model for FSI and flight dynamics to inform it. The latter is based on the linearization about a pre-designed glideslope trajectory of a high-fidelity, viscous, CFD-CSD-based computational model for flight dynamics; and its projection onto a low-dimensional approximation subspace to achieve real-time performance, while maintaining accuracy. Unlike static lookup tables or regression-based surrogate models based on steady-state wind tunnel data, the proposed real-time computational model allows MPC to be informed by a truly dynamic flight model, rather than a less accurate set of steady-state aerodynamic force and moment data points. While all this work assumes some simplifications, it paves the way for a new approach for achieving autonomous aircraft landing
Prospects of High Precision Fiber for Gravitational Wave Detection
Keywords:  Department of Physics
gravitational wave detection
optical fiber
optical fiber technology
Thesis

All current gravitational wave (GW) detectors, such as those of the Laser Interferometer Gravitational-wave Observatory (LIGO) and Virgo, are precision optical interferometers with sub-attometer displacement sensitivity. Free space propagation of the optical beams of LIGO requires large (meter diameter and kilometers of length) evacuated stainless steel beam tubes that come with sizable manufacturing and operational costs. A fiber-based detector – with the free space beams of present schemes replaced by concentrated fiber spools – could mitigate these costs while simultaneously offering a more compact experimental setup. This thesis proposes a design for and carries out the strain calculations for a hypothetical Michaelson Morley fiber interferometer over a wide frequency range. Limits on thermoconductive, thermomechanical, and shot noise sources are established and compounded to arrive at an estimate of the overall noise floor. Considering an interferometer arm length comparable to that used in the current generation of detectors, we estimate the strain sensitivity at 1 kHz to be around 10^(−16)√Hz. Advanced cooling strategies, the novel fiber technologies mentioned above, and parameter tuning in the thermal noise are all potential options for improving on this baseline sensitivity. The thesis concludes by summarizing the major developments in each area, and the long-term outlook of using such detectors for detecting gravitational waves.
Pyongyang in Ink and Concrete: North Korean Urban Modernism in Kim Il Sung Period Fiction, 1967-1994
Keywords:  Stanford Global Studies
Korea (North)
Fiction
Literature, Modern
City planning
Korea (North) > Pʻyŏngyang
Text
Thesis

This research fills a lacuna in the research on North Korean official culture by elucidating North Korean urban modernism of the Kim Il Sung period (1967-1994), a period which has been framed in extant research as a move away from, rather than toward modernity. I explore the urban modernism of capital construction fiction, that is, North Korean fiction which portrays the construction of the North Korean capital Pyongyang from the perspectives of manual labourers, architects, urban planners, managers, party functionaries and the Leader (Kim Il Sung/Kim Jong Il). Capital construction fiction first emerged as a genre during this period and is intimately connected with both the personality cult of the Leaders, and a unique vision of urban modernism. This research explores Ch’oe Haksu’s Pyongyang Time (1976), the seminal work of capital construction fiction and one of the most important novels in the canon of Juche literature, and two other examples of capital construction fiction. I analyze the way in which this body of literature presents its own version of the city strolling flâneur, how it prizes urban planning, and how it frames its own picture of urban modernism in contradistinction to the capitalist city. The picture of North Korean urbanism that emerges is one that is decisively modernist: North Korean flânerie is in evidence and calls on characters to participate in construction. Urban planning allows for the compression of time, enabling Pyongyang to speed its way into new stages of teleological development as part of an ever-accruing schema of progress. Marked differences to capitalist urban modernism result from it being a form of Asian, anti-Western alternative modernity in its self-conception, with grounding in “ethnic form”—but this is not traditionalism. If modernism is defined according to belief in progress, North Korean urban modernism may even be hypermodernist.
Quantification and minimization of energy loss mechanisms in microelectromechanical resonators
Keywords: Mechanical Engineering.

This work focuses on quantifying and minimizing energy loss in encapsulated capacitive microelectromechanical (MEM) resonators. This is important to reduce phase and frequency noise in the output signal of these resonators. Improving upon these metrics creates accelerometers, gyroscopes, and timing references that have more resolution and higher stability. Energy loss of a MEM resonator is measured by its quality factor, which is the ratio of the energy stored in the resonator to the energy lost per cycle of motion. The common energy loss mechanisms that affect the quality factor of MEM resonators are thermoelastic dissipation (TED), gas damping, Akhiezer damping, and anchor damping. This work quantities energy loss of these loss mechanisms using the different temperature dependence of each mechanism. Insight from quantifying these energy loss mechanisms in different resonator designs is used to design a resonator with a quality factor that is limited by the material loss limit of silicon, which is the highest possible quality factor that a capacitive resonator can achieve, resulting in an fxQ product of 2.2x10^13 Hz. Of all of the energy loss mechanisms, anchor damping is the least understood for resonant frequencies below 100 MHz. Anchor damping occurs because mechanical energy leaks out of the resonator at the attachment point, or anchor, to the substrate. This work experimentally explores how factors including outer packaging, substrate thickness, anchor placement, and anchor design affect anchor loss. Anchor damping in a bulk mode resonator was reduced by almost an order of magnitude by removing the silver paste adhering the die to the chip carrier. Thinning the substrate enhances the quality factor by a factor of 1.5x. The placement of anchors at two nodes on the edge of a ring resonator is has a 2x greater quality factor than that of a ring resonator with a center anchor. A more compliant anchor reduces anchor damping by an order of magnitude in bulk mode resonators. These results initiate an understanding of the mechanism by which anchor loss occurs in MEM resonators below 100 MHz. Lastly, this thesis presents a variant of the Epi-Seal encapsulation fabrication process where small and large transduction gaps can be fabricated for resonators without etch-holes. The traditional Epi-Seal process uses epitaxial silicon to seal devices at the wafer level in an oxide-free, particle-free, low pressure environment, creating resonators with long term stability. This new variant is important because it increases the design space for capacitive MEM resonators to include large etch-hole free masses and large and small transduction gaps with all the advantages of the original process
Quantification of aging and rejuvenation interventions on the neurogenic niche using single cell transcriptomics
Keywords: Genetics.

Aging is the gradual deterioration of molecular, cellular, and organismal function that occurs over a lifetime. Half of the global adult disease burden is driven by diseases with incidence rates that scale quadratically with age. Understanding and countering the many mechanisms of aging has the potential to reduce or postpone the onset of many diseases simultaneously. However, we are still early in the process of understanding aging and rejuvenating mechanisms, and the tools to achieve this are rapidly improving. In this dissertation I present the work I have undertaken to leverage recent advances in single cell transcriptomics to quantify aging and rejuvenating interventions at the cellular level. I focus on the subventricular zone of the mammalian brain which provides a window into how aging impacts neurogenesis and glial cells critical to brain function. In the second chapter I concentrate on age-associated tissue composition changes; in the third chapter I concentrate on cell type-specific effects. The primary finding I present in the second chapter is the discovery of brain infiltrating CD8+ T cells in the aged neurogenic niche. These T cells are clonally expanded and secrete interferon gamma which negatively impacts the neurogenic potential of the niche. In chapter three, I describe my work building a suite of cell type-specific transcriptomic aging clocks that accurately predict chronological and biological age. I use these clocks to quantify and compare the rejuvenating effects of heterochronic parabiosis and exercise on SVZ cell types. Doing so reveals the particularly striking transcriptomic rejuvenation that young blood exposure imparts on aged neural stem cells. Together, these chapters demonstrate the power of single cell transcriptomics and computational analysis to illuminate processes of aging and their reversal
Quantifying degradation in lithium-metal and lithium-ion batteries
Keywords: Chemistry.

Batteries are a key technology for electrifying transportation and implementing a reliable, sustainable energy grid. A major limitation to the implementation and utilization of batteries in electric vehicles is the lower energy density compared to gasoline and their degradation over time. In this work, I investigate degradation in both next-generation battery materials and commercially available batteries on the market today. Lithium-metal negative electrodes provide a pathway to high specific-energy density. Multiple degradation pathways, including electrolyte reduction, lithium corrosion, and the formation of dead lithium, contribute to these losses, but few methods of characterization can distinguish the various modes of degradation. Here, I have developed a method of quantifying the amount of lithium metal in the electrode via operando X-ray diffraction (XRD). Through this method, how much lithium actively cycles and how much is lost to the three degradation mechanisms noted above can be separated and quantified. Additionally, the operando XRD experiments provide a unique measure of the corrosion current of electrodeposited lithium metal. The measurements reveal that lithium corrodes when electrically connected to the copper current collector as well as in the form of dead Li metal. Corrosion of the dead, electronically disconnected lithium provides new insight into corrosion mechanisms in lithium metal batteries. Additionally, I present an approach to electrochemically measure the active material and lithium capacity in commercial cells. This work complements a dataset of 400+ commercially available battery cells. Through fitting of the cells' charge/discharge voltage curves, the capacity of cyclable lithium and active material on both electrodes can be extrapolated throughout cell lifetime. The methods presented here validate the extrapolated values through electrochemical testing of the separated electrodes, which can be applied to confirm the understanding of predominant degradation modes in different cycling protocols. The approaches here address the quantification of capacity losses and a more complete understanding of degradation mechanisms, both of which can aid in the design of long-lasting batteries
Quantifying methane emissions from oil and gas operations in the New Mexico Permian Basin
Keywords:  Energy Resources Engineering
methane emissions
oil and gas
aerial survey
super-emitters
Thesis

Methane leakage from point sources in the oil and gas industry is a major contributor to global greenhouse gas emissions. The majority of such emissions come from a small fraction of ``super-emitting" sources. The characteristics and the prevalence of these relatively rare super-emitting events cannot be thoroughly explored with conventional surveys that sample a small subset of the oil and gas asset population. This study analyzes methane emissions from the upstream and midstream oil and gas sector in the New Mexico part of the Permian Basin, by taking advantage of a population-level dataset from aerial surveys. The mean loss rate estimate of 9.4\% (+3.6\%/-3.2\%, 95\% CI) from our analysis is significantly higher than the 2.2\% national average loss rate in the upstream and midstream O\&G sectors. Part of the reason for the discrepancy is New Mexico Permian Basin specific. With the rapid development and the low price environment, the tools and incentives for operators to cut methane emissions are limited in this region. Secondly, the conventional ground-based surveys tend to have fewer than enough representative super-emitters in the sample and underestimate the total emissions, given the underlying heavy-tailed distribution of emission sizes.
Compared to estimates from satellite observation-based inversion modeling, our emission estimate is also higher. In addition to the conservative inversion modeling approach, the discrepancy can also be attributed to the observations from satellites with constant afternoon overhead times that are not representative of daily-average methane enhancement caused by emissions. The aerial survey finds that emission incidences vary across the day, with morning surveys more likely to see emissions than afternoon surveys. One possible explanation is that more well operations and maintenance work tend to happen in the morning in the Permian Basin to avoid the high afternoon temperatures often found in the region.
Quantum Algorithm for Vector Interpolation
Keywords:  Department of Physics
quantum algorithm
vector interpolation
black box query
Thesis

We study the functions that can be learned through the polynomial interpolation quantum algorithm designed by Childs et al. This algorithm was initially intended to find the coefficients of a multivariate polynomial function defined on finite fields F_q. We extend its scope to vector inner product functions of the form O_s(v) = s · v where the goal is to find the vector s in F_q. We examine the necessary conditions on the domain V of O_s and prove that the algorithm is optimal for such functions. Furthermore, we show that the success probability approaches 1 for large q and large domain order |V|. Finally, we provide a conservative formula for the number of queries required to achieve this success probability.
Quantum algorithms for learning and learning algorithms for quantum
Keywords: Applied Physics.

Machine learning has established itself as one of the most successful computational paradigms of the 21st century. Quantum computation is attempting to be the next one. What algorithmic and theoretical insights can each of these fields gain from the other? We first apply the tools of machine learning and its theoretical counterpart, computational learning theory, to a famously resource-intensive operation at the heart of quantum experiments: quantum state tomography. It is the following task: given many identically-prepared copies of the same n-qubit quantum state, output an approximation of its density matrix, which has 2^n numbers. We consider performing adaptive measurements on the state. We design a neural network that 'learns to learn' the correct measurement, which also speeds up a previous proposal for adaptive Bayesian updates in tomography by a factor of a million for a realistic situation. Theorists have also considered relaxing the requirement, in tomography, to output an approximation of the full density matrix -- and have proposed learning models in which, the learner need only predict the state's acceptance probability on measurements. We show that many of these "reduced" learning models are information-theoretically related. Finally, we switch gears: instead of applying the lessons of learning theory to quantum mechanics, we do the reverse. We develop a quantum algorithm for what is considered the "quantum" version of Bayes' rule -- the Petz recovery channel. As a byproduct, we also obtain an algorithm for implementing pretty-good measurements. Ours is the first systematic prescription to implement these ubiquitous theoretical tools in quantum error correction and quantum algorithms on a quantum computer
Quantum engineering by Rydberg dressing in a cold atomic gas
Keywords: Physics.

We are witnessing remarkable progress in building large and controllable quantum systems. At the forefront of this development are laser-cooled atoms, which can be used as atomic clocks, sensitive measurement probes or quantum computing platforms. A necessary ingredient of many computation and metrology schemes is the ability to have local and dynamical control of interactions between atoms. In this thesis, I present a platform based on highly excited Rydberg states of cesium atoms. We realize long-range optically controlled Ising interactions in a cloud of cold cesium atoms by coupling the atomic ground state to a Rydberg state. By adding a microwave coupling between the clock states of cesium, we emulate a transverse-field Ising model and detect dynamical signatures of the paramagnetic-ferromagnetic phase transition. I present work on producing spin-squeezed states, in which quantum correlations enable higher measurement precision than possible with an uncorrelated state. I show the first measurement of spin squeezing with the local Ising interactions, demonstrating a factor $\xi^2=\num{0.80(7)}$ reduction in phase variance below the projection noise limit. I present prospects for improving spin squeezing in this system, by minimizing sources of loss, trapping atoms in a regular array and utilizing the transverse field. Finally, I propose an application of optically controlled Ising interactions to the computational problem of number partitioning, where a hardware-efficient encoding in a central spin system enables solutions to be found via Grover's algorithm. The simulated performance of the algorithm exhibits a quantum speedup in a system of Rydberg-dressed atoms, paving the way for demonstrations in near-term experiments
Racial and socioeconomic inequality in educational opportunity and access
Keywords: Education.

This dissertation investigates inequality in the educational system and comprises three distinct but interrelated studies that focus on inequality and stratification in education. The first paper is a comprehensive assessment of the sources of the Black gender gap in educational attainment using a decomposition approach. The second paper explores misperceptions of economic school segregation and parents' personal and policy preferences using a survey experiment. The third paper investigates the causal impact of district secessions on racial and economic achievement gaps using a difference-in-differences approach. Taken together, these studies can inform understandings of the sources of inequality in educational opportunities and outcomes, and illustrate how structural inequality, parental preferences, and policy changes are related to educational disparities
Radiation-balanced silica fiber lasers and amplifiers
Keywords: Electrical Engineering.

In optically pumped lasers, the quantum defect generates heat that causes detrimental fluctuations in the output mode, frequency, and power. Common heat-mitigation techniques use bulky mechanical coolers that introduce vibrations, leading to laser frequency and amplitude noise. Anti-Stokes fluorescence (ASF) cooling is a promising vibration-free alternative that involves pumping the laser's active ions above their mean fluorescence wavelength. Ultimately, this enables the creation of "radiation-balanced lasers", in which the heat generated from lasing is negated by cooling due to ASF. This form of cooling was first demonstrated in 1995 and, since then, there has been extensive research on cooling in crystals and other bulk samples. ASF cooling in fibers, however, remained largely unexplored. This work presents a thorough investigation of ASF cooling in fibers and demonstrates that fibers are viable candidates for applications to practical radiation-balanced fiber lasers. We start by demonstrating cooling in various Yb-doped fiber hosts including silica, which was previously regarded as a highly improbably host for cooling. We then use the best performing silica fiber to make a 22-dBm amplifier with no net heating along the length of the fiber. Then, finally, we present a radiation-balanced silica fiber laser with 115 mW of output power. By eliminating the need for conventional coolers, this result will enable fiber lasers with lower relative intensity noise and greater temporal coherence than possible until now