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The Propagation and Amplification of Surface Waves
Get PDFThe observation of surface waves from cross-correlations of ambient noise has proven to be an invaluable tool for the recovery of seismic travel times. Such techniques allow the construction of 3D velocity models and subsequent geologic interpretations in regions where tomography would otherwise be difficult due to the paucity of seismicity and short seismic array deployment times. One such model is developed here for offshore southern California using an array of Ocean Bottom Seismometers to better understand the tectonic history of the region.
However, for accurate hazard evaluation, characterizations of the spatial variability of ground motion amplitudes are also desired. Unfortunately, the amplitudes from noise cross-correlations are systematically biased by the spatial-, frequency- and temporal variability of noise sources. We demonstrate in this thesis that an ambient-noise based wavefront tracking technique using an array of stations can recover site-amplification and attenuation estimates successfully and robustly. This is applied on two different scales: to a very dense array of more than 5,000 geophones in the city of Long Beach, CA, and in a broader, continental scale to instruments from the USArray.
Finally, we discuss the propagation of surface waves in relation to seismic hazard and site characterization. We point out that the amplitude response and peak frequency of ground motion will be different for a given site, depending on the type of wave being considered. This work should be considered by any future seismic hazard evaluation where surface waves may cause damage.</p
Unobserved Heterogeneity in Observational Studies of Political Behavior
Get PDFThis dissertation comprises three chapters dealing with unobserved heterogeneity in observational studies. In Chapters 2 and 3, I develop new estimators that deal with unobserved heterogeneity in the cases in which panel data is not available or the outcome of interest is binary, respectively. In Chapter 4, I analyze the effect of parties' contacting voters on the extent of tactical voting in the 2015 and 2017 United Kingdom General Elections, applying the estimator developed in Chapter 3.
In Chapter 2, I develop a semi-parametric two-step estimator for linear models with unobserved individual level heterogeneity that can be applied on a series of Repeated Cross-Sections, when panel data is unavailable. I show that this estimator provides consistent and asymptotically normal estimates of the parameters of interest. Identification relies on a restriction that requires the conditional expectation of the unobserved individual-level heterogeneity on observed characteristics to be continuous. Using Monte Carlo simulations, I show that this estimator typically outperforms other available alternatives. In particular, it typically has a smaller Root Mean Squared Error, and a relatively small bias that disappears for moderate sample sizes. Furthermore, it is robust to mild violations of the continuity assumption. Finally, I also show that this estimator can recover sensible estimates compared to those from an real panel.
In Chapter 3, I propose a method for estimating binary outcome models with panel data in the presence of unobserved heterogeneity, called the Penalized Flexible Correlated Random Effects (PF-CRE) estimator. I show that this estimator produces consistent and efficient estimates of the model parameters. PF-CRE also provides consistent estimates of partial effects, which cannot be calculated with existing consistent estimators. Using Monte Carlo simulations, I show that PF-CRE performs well in small samples. To demonstrate that accounting for unobserved heterogeneity has important consequences for empirical analysis, I use PF-CRE in three studies of voting behavior: tactical voting during the 2015 British Election, support for the Brexit referendum of 2016, and vote choice in the 2012 U.S. Presidential election. In all three cases, I find that ignoring the unobserved heterogeneity leads to an overestimation of the effects of interest, and that PF-CRE is a valid approach for the analyses.
In Chapter 4, I apply the PF-CRE estimator developed in Chapter 3 to the study of tactical voting in the United Kingdom General Elections of 2015 and 2017. In particular, I study the effect that party contacts during the electoral campaigns has on the probability that voters decide to cast a tactical vote for a less preferred party when their most preferred party is out of the race. I show that these effects are of moderate size, but substantively important. For example, during the 2017 election, contact by the most preferred party discouraged tactical voting by 7.02%, while contact by the most preferred viable party encouraged it by 13.41%. Combining counterfactual simulations with Multilevel Regression and Poststratification I estimate the effect that party contact has on the seat distribution in Westminster through tactical voting. My results show that between 9 and 18 seats change hands, depending on the election. Importantly, the Conservative party would have obtained a majority in 2017 had non-viable parties given up contacting their supporters.</p
Understanding Galaxy Formation and Evolution with Realistic Simulations
Get PDFUnderstanding the formation and evolution of galaxies from the Big Bang to the present day is one of the most important questions in modern astronomy. The tremendous amount of observational data accumulated in the past decade that probe various properties of galaxies across cosmic time demand a more detailed theoretical understanding of galaxy formation and evolution.
In this thesis, I will investigate several open question in this field using state-of-the-art cosmological hydrodynamic zoom-in simulations of galaxy formation from the Feedback in Realistic Environments (FIRE) suite. These high-resolution simulations (10-104M⊙, 0.1-10pc) include realistic models of the multi-phase ISM, star formation, and stellar feedback and explicitly capture gas cooling down to 10 K, star formation in dense clumps in giant molecular clouds, and feedback coupling on the smallest resolved scales. These simulations are powerful tools for studying the key physics governing galaxy formation and evolution and understanding the detailed observations of galaxy properties.
The first half of this thesis presents three studies on galactic chemical evolution. Chapter 2 focuses on the origin and evolution of the galaxy mass-metallicity relation (MZR), one of the fundamental properties of galaxies. I will show that the FIRE simulations broadly agree with the observed galaxy MZR from z = 0-3. The slope of the MZR is mainly driven by the metal retention fraction in low-mass galaxies, while the amount of redshift evolution of the MZR is mostly determined by the star formation histories of galaxies. Chapter 3 attempts to understanding the diversity of gas-phase metallicity gradients found in intermediate-redshift (z ~ 0.6-3) galaxies. I will show that the metallicity gradient in a galaxy varies on small timescales driven by bursty star formation and feedback cycle at early times, naturally resulting in the observed diversity of metallicity gradients in z ~ 2 galaxies. The metallicity gradient only reflects the instantaneous dynamics of a galaxy. Chapter 4 will study the structure, stellar age and metallicity gradients, and formation history of Milky Way (MW)-like disk galaxies. At high redshift, star formation happens in a chaotic, bursty mode, which eventually forms a nearly spherical structure by z = 0. Since z ≾ 1, a stable gas disk emerged and stars formed in that disk thereafter. The thickness of the gas disk decreases with time due to lowering gas fraction. Stars formed earlier in this disk are kinematically heated to a thicker, flaring disk. Such a formation history leads to the age and stellar metallicity gradients consistent with what observed in the MW disk.
The second half of this thesis focuses on galaxy formation in the first billion years of the Universe, known as the reionization era. Chapters 5 and 6 study the escape fraction of ionizing photons from galaxies at z ≥ 5, which is an important, yet poorly constrained parameter for understanding the reionization history. Most ionizing photons are emitted by the youngest stellar populations in the galaxy, which are usually embedded in their 'birth clouds'. Stellar feedback is required to clear these clouds in a few Myr before ionizing photons are allowed escape. In the meanwhile, the ionizing photon budget decreases rapidly as the most massive stars start to die. The competition of timescales between feedback and stellar evolution is thus the most important physics determines fesc. I will show that canonical single-star stellar population models such as STARBURST99 generally yield a fesc far below what is required for cosmic reionization. Binary models, in contrast, produce more ionizing photons at late times than single-star models and thus lead to a much higher fesc. Chapter 7 presents a new suite of high-resolution cosmological zoom-in simulations of z ≥ 5 galaxies that contains thousands of halos at any time in all zoom-in regions. I will present the stellar mass-halo mass relation, SFR-Mhalo relation, stellar mass-magnitude relation, stellar mass functions, and multi-band luminosity functions at z = 5-12. These prediction agree well with current observational constraints and can be further tested by future observations with the James Webb Space Telescope. Using these new simulations, Chapter 8 studies the morphology and size evolution of galaxies at z ≥ 5. I will show that the rest-frame UV light from z ≥ 5 galaxies is usually dominated by one or several star-forming clumps that are intrinsically bright and small. Current observations with moderate surface brightness limits tend to only pick up the intrinsically small galaxies or individual clumps but miss the diffuse light in the galaxies. Such a selection effect is likely to result in the extremely small sizes claimed for the faint galaxies in the Hubble Frontier Fields.</p
Macro Mars to Micro Mars: Mapping Minerals and Magnetization
Get PDFCombination of remote sensing data with in-situ measurements provides a fuller understanding of Mars phenomena. This dissertation focuses on integrating macroscopic and microscopic scales of measurement with regard to spectroscopy and magnetization. In the first chapter high resolution orbital spectroscopy (~18 m/px) and imagery (~30 cm/px) are used to identify potential sources for some of the sedimentary rocks investigated by the Curiosity rover and expand the accessible stratigraphy. While we find mineralogies in common outside and inside the crater as well as transport mechanisms, we conclude that additional sedimentary sources and/or modification after transport are required to explain chemical differences and that strata point to multiple episodes of a lake in Gale crater. In the third chapter we conducted a laboratory photometric study on candidate calibration target materials for the Mars-2020 rover. We characterized these target materials for proper calibration and monitoring of the Mastcam-Z instrument to enable mineral identification through reflectance spectroscopy. The fourth and fifth chapters focus on the microscopic magnetizations found within Martian meteorite ALH84001. Chapter four reports on paleomagnetic experiments conducted on isolated carbonate crystals which contain magnetite previously reported to be biogenic. We compare paleomagnetic test results which distinguish between biogenic and abiogenic origin hypotheses and find that the magnetization within the carbonates is most consistent with a shock processes. In chapter five we analyzed the distribution of dipoles within slices of ALH84001 and determined that they lie in a girdle distribution which could be interpreted as resulting from a true polar wander event on Mars. Looking at kilometer scale observations outside of Gale enlightened observations made along the rover transverse path. A high resolution laboratory analysis of calibration materials will enable future multispectral mineralogical explorations. Microscopic analyses of magnetization inform ancient surface processes on Mars and hint at large-scale global change. In each of these chapters our results were only made possible or greatly enhanced by the combination of data sources and scales.</p
The ABCs of the Color Code: A Study of Topological Quantum Codes as Toy Models for Fault-Tolerant Quantum Computation and Quantum Phases Of Matter
Get PDFThis thesis is devoted to studying a class of quantum error-correcting codes — topological quantum codes. We explore the question of how one can achieve fault- tolerant quantum computation with topological codes. We treat quantum error-correcting codes not only as a compelling ingredient needed to build a quantum computer, but also as a useful theoretical tool in other areas of physics. In particular, we explore what insights topological codes can provide into challenging questions, such as the classification of quantum phases of matter.
In this thesis, we focus on a family of topological codes — color codes, which are particularly intriguing due to the rich physics they display and their computational power. We start by introducing color codes and explaining their basic properties. Then, we show how to perform fault-tolerant universal quantum computation with three-dimensional color codes by transverse gates and code switching. We later compare the resource overhead of the code-switching approach with that of a state distillation scheme. We discuss how to perform error correction with the toric and color codes, as well as introduce local decoders for those two families of codes. By exploiting a connection between error correction and statistical mechanics we estimate the storage threshold error rates for bit-flip and phase-flip noise in the three-dimensional color code. We finish by showing that the color and toric code families in d dimensions are equivalent in a sense of local unitary transformations and explore implications of this equivalence.</p
Engineering Novel Rhodopsins for Neuroscience
Get PDFThe overarching goal of my PhD research has been engineering proteins capable of controlling and reading out neural activity to advance neuroscience research. I engineered light-gated microbial rhodopsins, primarily focusing on the algal derived, light-gated channel, channelrhodopsin (ChR), which can be used to modulate neuronal activity with light. This work has required overcoming three major challenges. First, rhodopsins are trans-membrane proteins, which are inherently difficult to engineer because the sequence and structural determinants of membrane protein expression and plasma membrane localization are highly constrained and poorly understood (Chapter 3-5). Second, protein properties of interest for neuroscience applications are assayed using very low throughput patch-clamp electrophysiology preventing the use of high-throughput assays required for directed evolution experiments (Chapter 2, 5-6). And third, in vivo application of these improved tools require either retention or optimization of multiple protein properties in a single protein tool; for example, we must optimize expression and localization of these algal membrane proteins in mammalian cells while at the same time optimizing kinetic and functional properties (Chapter 5-6). These challenges restricted the field to low-throughput, conservative methods for discovery of improved ChRs, e.g., structure-guided mutagenesis and testing of natural ChR variants. I used an alternative approach: data-driven machine learning to model the fitness landscape of ChRs for different properties of interest and applying these models to select ChR sequences with optimal combinations of properties (Chapters 5-6). ChR variants identified from this work have unprecedented conductance properties and light sensitivity that could enable non-invasive activation of populations of cells throughout the nervous system. These ChRs have the potential to change how optogenetics experiments are done. This work is a convincing demonstration of the power of machine learning guided protein engineering for a class of proteins that present multiple engineering challenges. A component of the novel application of these new ChR tools relies on recent advances in gene delivery throughout the nervous system facilitated by engineered AAVs (Chapter 7). And finally, I developed a behavioral tracking system to monitor behavior and demonstrate sleep behavior in the jellyfish Cassiopea, the most primitive organism to have this behavior formally characterized (Chapter 8).</p
Dynamic Modeling and Control of Spherical Robots
Get PDFIn this work, a rigorous framework is developed for the modeling and control of spherical robotic vehicles. Motivation for this work stems from the development of Moball, which is a self-propelled sensor platform that harvests kinetic energy from local wind fields. To study Moball's dynamics, the processes of Lagrangian reduction and reconstruction are extended to robotic systems with symmetry-breaking potential energies, in order to simplify the resulting dynamic equations and expose mathematical structures that play an important role in subsequent control-theoretic tasks. These results apply to robotic systems beyond spherical robots. A formulaic procedure is introduced to derive the reduced equations of motion of most spherical robots from inspection of the Lagrangian. This adaptable procedure is applied to a diverse set of robotic systems, including multirotor aerial vehicles.
Small time local controllability (STLC) results are derived for barycentric spherical robots (BSR), which are spherical vehicles whose locomotion depends on actuating the vehicle's center of mass (COM) location. STLC theorems are introduced for an arbitrary BSR on flat, sloped, or smooth terrain. I show that STLC depends on the surjectivity of a simple steering matrix. An STLC theorem is also derived for a class of commonly encountered multirotor vehicles.
Feedback linearizing and PID controllers are proposed to stabilize an arbitrary spherical robot to a desired trajectory over smooth terrain, and direct collocation is used to develop a feedforward controller for Moball specifically. Moball's COM is manipulated by a novel system of magnets and solenoids, which are actuated by a "ballistic-impulse" controller that is also presented. Lastly, a motion planner is developed for energy-harvesting vehicles. This planner charts a path over smooth terrain while balancing the desire to achieve scientific objectives, avoid hazards, and the imperative of exposing the vehicle to environmental sources of energy such as local wind fields and topology. Moball's design details and experimental results establishing Moball's energy-harvesting performance (7W while rolling at a speed of 2 m/s), are contained in an Appendix.</p
Reconstruction and Estimation of Flows Using Resolvent Analysis and Data-Assimilation
Get PDFA flow reconstruction methodology is presented for incompressible, statistically stationary flows using resolvent analysis and data-assimilation. The only inputs necessary for the procedure are a rough approximation of the mean profile and a single time-resolved measurement. The objective is to estimate both the mean and fluctuating states of experimental flows with limited measurements which do not include pressure. The input data may be incomplete, in the sense that measurements near a body are difficult to obtain with techniques such as particle image velocimetry (PIV), or contaminated by noise. The tools developed in this thesis are capable of filling in missing data and reducing the amount of measurement noise by leveraging the governing equations. The reconstructed flow is capable of estimating fluctuations where time-resolved data are not available and solving the flow on larger domains where the mean profile is not known.
The first part of the thesis focuses on how resolvent analysis of the mean flow selects amplification mechanisms. Eigenspectra and pseudospectra of the mean linear Navier-Stokes (LNS) operator are used to characterize amplification mechanisms in flows where linear mechanisms are important. The real parts of the eigenvalues are responsible for resonant amplification and the resolvent operator is low-rank when the eigenvalues are sufficiently separated in the spectrum. Two test cases are studied: low Reynolds number cylinder flow and turbulent channel flow. The latter is studied by considering well-known turbulent structures while the former contains a marginally stable eigenvalue which drowns out the effect of other eigenvalues over a large range of temporal frequencies. There is a geometric manifestation of this dominant mode in the mean profile, suggesting that it leaves a significant footprint on the time-averaged flow that the resolvent can identify. The resolvent does not provide an efficient basis at temporal frequencies where there is no separation of singular values. It can still be leveraged, nevertheless, to identify coherent structures in the flow by approximating the nonlinear forcing from the interaction of highly amplified coherent structures.
The second part of the thesis extends the framework of Foures et al. (2014), who data-assimilated the mean cylinder wake at very low Reynolds numbers. The contributions presented here are to assess the minimum domain for successfully reconstructing Reynolds stress gradients, modifying the algorithm to assimilate mean pressure, determining whether weighting input measurements contributes to improved performance, and adapting the method to experimental data at higher Reynolds numbers. The results from data-assimilating the mean cylinder wake at low Reynolds numbers suggest that the measurement domain needs to coincide with the spatial support of the Reynolds stress gradients while point weighting has a minimal impact on the performance. Finally, a smoothing procedure adapted from Foures et al. (2014) is proposed to cope with data-assimilating an experimental mean profile obtained from PIV data. The data-assimilated mean profiles for an idealized airfoil and NACA 0018 airfoil are solved on a large domain making the mean profile suitable for global resolvent analysis. Data-assimilation is also able to fill in missing or unreliable vectors near the airfoil surface.
The final piece of the thesis is to synthesize the knowledge and techniques developed in the first two parts to reconstruct the experimental flow around a NACA 0018 airfoil. Preliminary results are presented for the case where α = 0° and Re = 10250. The mean profile is data-assimilated and used as an input to resolvent analysis to educe coherent structures in the flow. The resolvent operator for non- amplified temporal frequencies is forced by an approximated nonlinear forcing. The amplitude and phase of the modes are obtained from the discrete Fourier-transform of a time-resolved probe point measurement. The final reconstruction contains less measurement noise compared to the PIV snapshots and obeys the incompressible Navier-Stokes equations (NSE). The thesis concludes with a discussion of how elements of this methodology can be incorporated into the development of estimators for turbulent flows at high Reynolds numbers.</p
Measuring the Polarization of the Cosmic Microwave Background with BICEP3
Get PDFInflation, a period of accelerated expansion in the early Universe, is postulated to answer the horizon, flatness and monopole problems in the standard model of the Universe. This inflationary scenario generically predicts the existence of primordial gravitational waves, which would leave an unique B-mode polarization pattern in the Cosmic Microwave Background. Detection of the primordial B modes at degree angular scales would be a direct evidence for inflation; and the amplitude, parametrized by the tensor-to-scalar ratio r, would allow us to probe the energy scale at 10-35 second after the Big Bang.
The Bicep/Keck Array experiment is a series of telescopes located at the Amundsen-Scott South Pole Station designed to measure the CMB polarization at degree angular scales. The latest result in Bicep/Keck Array, using data collected up to 2015, and combined with other external data, set upper limits on r < 0.06 at 95% confidence. Bicep3 is the latest addition in the experiment, deployed to South Pole in 2015, and started science observation in 2016. It is a 520 mm aperture, compact two-lens refracting telescope at 95 GHz. With 2500 detectors, it achieved instantaneous sensitivity of 9.1μK√s and 7.3μK√s for 2016 and 2017, respectively. After two year of observations, Bicep3 is estimated to reach a map depth of 3.8μK-arcmin. This is the most sensitive polarization measurement at 95 GHz to date.
This dissertation provides an overview of the Bicep3 instrument design. In particular, the performance of the sub-Kelvin focal plane structure, antenna-coupled transition edge sensor and time domain multiplexing SQUID readout system. We discuss various calibration methods used to probe instrument sensitivity and systematics. Finally, we review the analysis pipeline, and some preliminary results from Bicep3.</p
Elucidating the Mechanism of mRNA Export Regulation by the Nuclear Pore Complex
Get PDFThe nuclear pore complex (NPC) is one of the largest and most complex protein assemblies in eukaryotic cells, and it facilitates and regulates the bidirectional transfer of molecules between the nucleus and cytoplasm. One of the essential functions of the NPC is to directly regulate the export of mature mRNAs, but the mechanism is not well understood, especially in humans. Export of mRNA is completed at the cytoplasmic side of the NPC, where ATPase activity of the DEAD-box helicase DDX19 is specifically activated by the NPC components Gle1, Nup42, and Nup214. The mRNA export factor Gle1 is an essential nucleoporin, and Gle1 dysfunction has been linked to human diseases. We show that the Gle1-Nup42 interaction is highly conserved with X-ray crystal structures and that the thermostability of Gle1 is highly dependent on Nup42. We also find that disease-linked mutants of Gle1 show strongly altered thermostability. Analysis of DDX19 steady-state ATPase activity reveals a novel mode of activation by Gle1 in humans. Structural studies of DDX19 complement the biochemical characterization of DDX19, and we have proposed a working model for the DDX19 catalytic cycle. An outstanding question remains in this model, as the details of DDX19-mediated removal of the export factor NXF1-NXT1 from mRNA are unknown. We describe a method for large-scale purification of retroviral constitutive transport element (CTE) RNA, which hijacks NXF1-NXT1 to be exported through the NPC, for X-ray crystallographic studies of a NXF1-NXT1-CTE complex. Together, these results provide a detailed structural and functional description of mRNA export regulation by the NPC and a framework for understanding the molecular basis of human disease linked to Gle1 and viral proliferation