12023 research outputs found
Sort by
The Astrophysics of Strongly Interacting Systems
Get PDFThis thesis presents investigations in four areas of theoretical astrophysics: the production of sterile neutrino dark matter in the early Universe, the evolution of small-scale baryon perturbations during the epoch of cosmological recombination, the effect of primordial magnetic fields on the redshifted 21-cm emission from the pre-reionization era, and the nonlinear stability of tidally deformed neutron stars.
In the first part of the thesis, we study the asymmetry-driven resonant production of 7 keV-scale sterile neutrino dark matter in the primordial Universe at temperatures T >~ 100 MeV. We report final DM phase space densities that are robust to uncertainties in the nature of the quark-hadron transition. We give transfer functions for cosmological density fluctuations that are useful for N-body simulations. We also provide a public code for the production calculation.
In the second part of the thesis, we study the instability of small-scale baryon pressure sound waves during cosmological recombination. We show that for relevant wavenumbers, inhomogenous recombination is driven by the transport of ionizing continuum and Lyman-alpha photons. We find a maximum growth factor less than ≈ 1.2 in 107 random realizations of initial conditions. The low growth factors are due to the relatively short duration of the recombination epoch.
In the third part of the thesis, we propose a method of measuring weak magnetic fields, of order 10-19 G (or 10-21 G if scaled to the present day), with large coherence lengths in the inter galactic medium prior to and during the epoch of cosmic reionization. The method utilizes the Larmor precession of spin-polarized neutral hydrogen in the triplet state of the hyperfine transition. We perform detailed calculations of the microphysics behind this effect, and take into account all the processes that affect the hyperfine transition, including radiative decays, collisions, and optical pumping by Lyman-alpha photons.
In the final part of the thesis, we study the non-linear effects of tidal deformations of neutron stars (NS) in a compact binary. We compute the largest three- and four-mode couplings among the tidal mode and high-order p- and g-modes of similar radial wavenumber. We demonstrate the near-exact cancellation of their effects, and resolve the question of the stability of the tidally deformed NS to leading order. This result is significant for the extraction of binary parameters from gravitational wave observations.</p
Coulomb Drag and Tunneling Studies in Quantum Hall Bilayers
Get PDFThe bilayer quantum Hall state at total filling factor νT=1, where the total electron density matches the degeneracy of the lowest Landau level, is a prominent example of Bose-Einstein condensation of excitons. A macroscopically ordered state is realized where an electron in one layer is tightly bound to a "hole" in the other layer. If exciton transport were the only bulk transportmechanism, a current driven in one layer would spontaneously generate a current of equal magnitude and opposite sign in the other layer. The Corbino Coulomb drag measurements presented in this thesis demonstrate precisely this phenomenon.
Excitonic superfluidity has been long sought in the νT=1 state. The tunneling between the two electron gas layers exihibit a dc Josephson-like effect. A simple model of an overdamped voltage biased Josephson junction is in reasonable agreement with the observed tunneling I-V. At small tunneling biases, it exhibits a tunneling "supercurrent". The dissipation is carefully studied in this tunneling "supercurrent" and found to remain small but finite.</p
Mechanics of Deformable Glacier Beds
Get PDFMy focus in this thesis is to contribute to a more thorough understanding of the mechanics of ice and deformable glacier beds. Glaciers flow under their own weight through a combination of deformation within the ice column and basal slip, which involves both sliding along and deformation within the bed. Deformable beds, which are made up of unfrozen sediment, are prevalent in nature and are often the primary contributors to ice flow wherever they are found. Their granular nature imbues them with unique mechanical properties that depend on the granular structure and hydrological properties of the bed. Despite their importance for understanding glacier flow and the response of glaciers to changing climate, the mechanics of deformable glacier beds are not well understood.
Our general approach to understanding the mechanics of bed deformation and their effect on glacier flow is to acquire synoptic observations of ice surface velocities and their changes over time and to use those observations to infer the mechanical properties of the bed. We focus on areas where changes in ice flow over time are due to known environmental forcings and where the processes of interest are largely isolated from other effects. To make this approach viable, we further develop observational methods that involve the use of mapping radar systems. Chapters 2 and 5 focus largely on the development of these methods and analysis of results from ice caps in central Iceland and an ice stream in West Antarctica. In Chapter 3, we use these observations to constrain numerical ice flow models in order to study the mechanics of the bed and the ice itself. We show that the bed in an Iceland ice cap deforms plastically and we derive an original mechanistic model of ice flow over plastically deforming beds that incorporates changes in bed strength caused by meltwater flux from the surface. Expanding on this work in Chapter 4, we develop a more detailed mechanistic model for till-covered beds that helps explain the mechanisms that cause some glaciers to surge quasi-periodically. In Antarctica, we observe and analyze the mechanisms that allow ocean tidal variations to modulate ice stream flow tens of kilometers inland. We find that the ice stream margins are significantly weakened immediately upstream of the area where ice begins to float and that this weakening likely allows changes in stress over the floating ice to propagate through the ice column. </p
Imaging the Earth with Ambient Noise and Earthquakes
Get PDFIn this thesis, I develop the velocity and structure models for the Los Angeles Basin and Southern Peru. The ultimate goal is to better understand the geological processes involved in the basin and subduction zone dynamics. The results are obtained from seismic interferometry using ambient noise and receiver functions using earthquake- generated waves. Some unusual signals specific to the local structures are also studied. The main findings are summarized as follows:
(1) Los Angeles Basin
The shear wave velocities range from 0.5 to 3.0 km/s in the sediments, with lateral gradients at the Newport-Inglewood, Compton-Los Alamitos, and Whittier Faults. The basin is a maximum of 8 km deep along the profile, and the Moho rises to a depth of 17 km under the basin. The basin has a stretch factor of 2.6 in the center decreasing to 1.3 at the edges, and is in approximate isostatic equilibrium. This "high-density" (~1 km spacing) "short-duration" (~1.5 month) experiment may serve as a prototype experiment that will allow basins to be covered by this type of low-cost survey.
(2) Peruvian subduction zone
Two prominent mid-crust structures are revealed in the 70 km thick crust under the Central Andes: a low-velocity zone interpreted as partially molten rocks beneath the Western Cordillera – Altiplano Plateau, and the underthrusting Brazilian Shield beneath the Eastern Cordillera. The low-velocity zone is oblique to the present trench, and possibly indicates the location of the volcanic arcs formed during the steepening of the Oligocene flat slab beneath the Altiplano Plateau.
The Nazca slab changes from normal dipping (~25 degrees) subduction in the southeast to flat subduction in the northwest of the study area. In the flat subduction regime, the slab subducts to ~100 km depth and then remains flat for ~300 km distance before it resumes a normal dipping geometry. The flat part closely follows the topography of the continental Moho above, indicating a strong suction force between the slab and the overriding plate. A high-velocity mantle wedge exists above the western half of the flat slab, which indicates the lack of melting and thus explains the cessation of the volcanism above. The velocity turns to normal values before the slab steepens again, indicating possible resumption of dehydration and ecologitization.
(3) Some unusual signals
Strong higher-mode Rayleigh waves due to the basin structure are observed in the periods less than 5 s. The particle motions provide a good test for distinguishing between the fundamental and higher mode. The precursor and coda waves relative to the interstation Rayleigh waves are observed, and modeled with a strong scatterer located in the active volcanic area in Southern Peru. In contrast with the usual receiver function analysis, multiples are extensively involved in this thesis. In the LA Basin, a good image is only from PpPs multiples, while in Peru, PpPp multiples contribute significantly to the final results
Distributed Control and Optimization for Communication and Power Systems
Get PDFWe are at the cusp of a historic transformation of both communication system and electricity system. This creates challenges as well as opportunities for the study of networked systems. Problems of these systems typically involve a huge number of end points that require intelligent coordination in a distributed manner. In this thesis, we develop models, theories, and scalable distributed optimization and control algorithms to overcome these challenges.
This thesis focuses on two specific areas: multi-path TCP (Transmission Control Protocol) and electricity distribution system operation and control. Multi-path TCP (MP-TCP) is a TCP extension that allows a single data stream to be split across multiple paths. MP-TCP has the potential to greatly improve reliability as well as efficiency of communication devices. We propose a fluid model for a large class of MP-TCP algorithms and identify design criteria that guarantee the existence, uniqueness, and stability of system equilibrium. We clarify how algorithm parameters impact TCP-friendliness, responsiveness, and window oscillation and demonstrate an inevitable tradeoff among these properties. We discuss the implications of these properties on the behavior of existing algorithms and motivate a new algorithm Balia (balanced linked adaptation) which generalizes existing algorithms and strikes a good balance among TCP-friendliness, responsiveness, and window oscillation. We have implemented Balia in the Linux kernel. We use our prototype to compare the new proposed algorithm Balia with existing MP-TCP algorithms.
Our second focus is on designing computationally efficient algorithms for electricity distribution system operation and control. First, we develop efficient algorithms for feeder reconfiguration in distribution networks. The feeder reconfiguration problem chooses the on/off status of the switches in a distribution network in order to minimize a certain cost such as power loss. It is a mixed integer nonlinear program and hence hard to solve. We propose a heuristic algorithm that is based on the recently developed convex relaxation of the optimal power flow problem. The algorithm is efficient and can successfully computes an optimal configuration on all networks that we have tested. Moreover we prove that the algorithm solves the feeder reconfiguration problem optimally under certain conditions. We also propose a more efficient algorithm and it incurs a loss in optimality of less than 3% on the test networks.
Second, we develop efficient distributed algorithms that solve the optimal power flow (OPF) problem on distribution networks. The OPF problem determines a network operating point that minimizes a certain objective such as generation cost or power loss. Traditionally OPF is solved in a centralized manner. With increasing penetration of volatile renewable energy resources in distribution systems, we need faster and distributed solutions for real-time feedback control. This is difficult because power flow equations are nonlinear and kirchhoff's law is global. We propose solutions for both balanced and unbalanced radial distribution networks. They exploit recent results that suggest solving for a globally optimal solution of OPF over a radial network through a second-order cone program (SOCP) or semi-definite program (SDP) relaxation. Our distributed algorithms are based on the alternating direction method of multiplier (ADMM), but unlike standard ADMM-based distributed OPF algorithms that require solving optimization subproblems using iterative methods, the proposed solutions exploit the problem structure that greatly reduce the computation time. Specifically, for balanced networks, our decomposition allows us to derive closed form solutions for these subproblems and it speeds up the convergence by 1000x times in simulations. For unbalanced networks, the subproblems reduce to either closed form solutions or eigenvalue problems whose size remains constant as the network scales up and computation time is reduced by 100x compared with iterative methods.</p
Distributed Optimal Control of Cyber-Physical Systems: Controller Synthesis, Architecture Design and System Identification
Get PDFThe centralized paradigm of a single controller and a single plant upon which modern control theory is built is no longer applicable to modern cyber-physical systems of interest, such as the power-grid, software defined networks or automated highways systems, as these are all large-scale and spatially distributed. Both the scale and the distributed nature of these systems has motivated the decentralization of control schemes into local sub-controllers that measure, exchange and act on locally available subsets of the globally available system information. This decentralization of control logic leads to different decision makers acting on asymmetric information sets, introduces the need for coordination between them, and perhaps not surprisingly makes the resulting optimal control problem much harder to solve. In fact, shortly after such questions were posed, it was realized that seemingly simple decentralized optimal control problems are computationally intractable to solve, with the Wistenhausen counterexample being a famous instance of this phenomenon. Spurred on by this perhaps discouraging result, a concerted 40 year effort to identify tractable classes of distributed optimal control problems culminated in the notion of quadratic invariance, which loosely states that if sub-controllers can exchange information with each other at least as quickly as the effect of their control actions propagates through the plant, then the resulting distributed optimal control problem admits a convex formulation.
The identification of quadratic invariance as an appropriate means of "convexifying" distributed optimal control problems led to a renewed enthusiasm in the controller synthesis community, resulting in a rich set of results over the past decade. The contributions of this thesis can be seen as being a part of this broader family of results, with a particular focus on closing the gap between theory and practice by relaxing or removing assumptions made in the traditional distributed optimal control framework. Our contributions are to the foundational theory of distributed optimal control, and fall under three broad categories, namely controller synthesis, architecture design and system identification.
We begin by providing two novel controller synthesis algorithms. The first is a solution to the distributed H∞ optimal control problem subject to delay constraints, and provides the only known exact characterization of delay-constrained distributed controllers satisfying an H∞ norm bound. The second is an explicit dynamic programming solution to a two player LQR state-feedback problem with varying delays. Accommodating varying delays represents an important first step in combining distributed optimal control theory with the area of Networked Control Systems that considers lossy channels in the feedback loop. Our next set of results are concerned with controller architecture design. When designing controllers for large-scale systems, the architectural aspects of the controller such as the placement of actuators, sensors, and the communication links between them can no longer be taken as given -- indeed the task of designing this architecture is now as important as the design of the control laws themselves. To address this task, we formulate the Regularization for Design (RFD) framework, which is a unifying computationally tractable approach, based on the model matching framework and atomic norm regularization, for the simultaneous co-design of a structured optimal controller and the architecture needed to implement it. Our final result is a contribution to distributed system identification. Traditional system identification techniques such as subspace identification are not computationally scalable, and destroy rather than leverage any a priori information about the system's interconnection structure. We argue that in the context of system identification, an essential building block of any scalable algorithm is the ability to estimate local dynamics within a large interconnected system. To that end we propose a promising heuristic for identifying the dynamics of a subsystem that is still connected to a large system. We exploit the fact that the transfer function of the local dynamics is low-order, but full-rank, while the transfer function of the global dynamics is high-order, but low-rank, to formulate this separation task as a nuclear norm minimization problem. Finally, we conclude with a brief discussion of future research directions, with a particular emphasis on how to incorporate the results of this thesis, and those of optimal control theory in general, into a broader theory of dynamics, control and optimization in layered architectures.</p
Paths Towards High Efficiency Silicon Photovoltaics
Get PDFWhile photovoltaics hold much promise as a sustainable electricity source, continued cost reduction is necessary to continue the current growth in deployment. A promising path to continuing to reduce total system cost is by increasing device efficiency. This thesis explores several silicon-based photovoltaic technologies with the potential to reach high power conversion efficiencies. Silicon microwire arrays, formed by joining millions of micron diameter wires together, were developed as a low cost, low efficiency solar technology. The feasibility of transitioning this to a high efficiency technology was explored. In order to achieve high efficiency, high quality silicon material must be used. Lifetimes and diffusion lengths in these wires were measured and the action of various surface passivation treatments studied. While long lifetimes were not achieved, strong inversion at the silicon / hydrofluoric acid interface was measured, which is important for understanding a common measurement used in solar materials characterization.
Cryogenic deep reactive ion etching was then explored as a method for fabricating high quality wires and improved lifetimes were measured. As another way to reach high efficiency, growth of silicon-germanium alloy wires was explored as a substrate for a III-V on Si tandem device. Patterned arrays of wires with up to 12% germanium incorporation were grown. This alloy is more closely lattice matched to GaP than silicon and allows for improvements in III-V integration on silicon.
Heterojunctions of silicon are another promising path towards achieving high efficiency devices. The GaP/Si heterointerface and properties of GaP grown on silicon were studied. Additionally, a substrate removal process was developed which allows the formation of high quality free standing GaP films and has wide applications in the field of optics.
Finally, the effect of defects at the interface of the amorphous silicon heterojuction cell was studied. Excellent voltages, and thus efficiencies, are achievable with this system, but the voltage is very sensitive to growth conditions. We directly measured lateral transport lengths at the heterointerface on the order of tens to hundreds of microns, which allows carriers to travel towards any defects that are present and recombine. This measurement adds to the understanding of these types of high efficiency devices and may aid in future device design.</p
Classical and Quantum Effects in Plasmonic Metals
Get PDFThe field of plasmonics exploits the unique optical properties of metallic nanostructures to concentrate and manipulate light at subwavelength length scales. Metallic nanostructures get their unique properties from their ability to support surface plasmons– coherent wave-like oscillations of the free electrons at the interface between a conductive and dielectric medium. Recent advancements in the ability to fabricate metallic nanostructures with subwavelength length scales have created new possibilities in technology and research in a broad range of applications.
In the first part of this thesis, we present two investigations of the relationship between the charge state and optical state of plasmonic metal nanoparticles. Using experimental bias-dependent extinction measurements, we derive a potential- dependent dielectric function for Au nanoparticles that accounts for changes in the physical properties due to an applied bias that contribute to the optical extinction. We also present theory and experiment for the reverse effect– the manipulation of the carrier density of Au nanoparticles via controlled optical excitation. This plasmoelectric effect takes advantage of the strong resonant properties of plasmonic materials and the relationship between charge state and optical properties to eluci- date a new avenue for conversion of optical power to electrical potential.
The second topic of this thesis is the non-radiative decay of plasmons to a hot-carrier distribution, and the distribution’s subsequent relaxation. We present first-principles calculations that capture all of the significant microscopic mechanisms underlying surface plasmon decay and predict the initial excited carrier distributions so generated. We also preform ab initio calculations of the electron-temperature dependent heat capacities and electron-phonon coupling coefficients of plasmonic metals. We extend these first-principle methods to calculate the electron-temperature dependent dielectric response of hot electrons in plasmonic metals, including direct interband and phonon-assisted intraband transitions. Finally, we combine these first-principles calculations of carrier dynamics and optical response to produce a complete theoretical description of ultrafast pump-probe measurements, free of any fitting parameters that are typical in previous analyses.</p
Statistical Mechanical Framework for Predicting Cellular Response
Get PDFDevelopments in singe-cell analysis techniques allow simultaneous high-resolution measurements of cellular component copy number and variation within a cell population. These data provide a probability distribution for all possible states of the cell, as determined by the measured component copy number per cell. We have developed a highly-flexible, theoretical statistical mechanical framework that uses single-cell cellular component data to model the evolution of the probability distribution of those components in a cell in response to an external, physical or molecular, perturbation. This framework uses Bayesian inference to compare potential functional descriptions of how the perturbation couples to the system, and to determine the uncertainty in the parameter estimations given the data. We have applied this methodology to study the impact of changes in oxygen partial pressure on the behavior of glioblastoma multiform cancer cells. We find that oxygen concentration couples not only to individual proteins, but effects the underlying effective interactions between the studied proteins as well. The underlying effective interactions were found to couple linearly to the system, indicating a simple proportional change in the protein network across oxygen concentrations. This description of the system provides improved predictive capabilities for describing the probability distribution of the measured cellular components across a wider range of perturbation conditions than previous methods. Additionally, we apply this methodology to show how it could be used to predict effects in difficult experimental perturbation regimes, identifying undruggable regimes, as well as the result of knocking our individual or combinations of proteins or protein interactions
Reverse Engineering and Quantifying Context Effects in Synthetic Gene Networks
Get PDFIn the first part of this thesis, we undertake a quantitative investigation of how compositional context, the spatial arrangement and relative orientation of genes, affects individual gene expression in a genetic network. Taking a synthetic biology approach, we construct a series of simple two-reporter biocircuits, each expressing either an mRNA aptamer or a fluorescent protein, and show that by varying the relative orientation of the two genes we obtain a wide range of gene expression profiles, including context-dependent bimodality. We develop a mathematical model to describe the experimental trends observed based on concepts from DNA supercoiling theory. We validate the model through a series of in vitro supercoiling experiments and show that by relaxing positive supercoiling in the plasmids, we can significantly reduce the context effects in gene expression. Most importantly, these insights provide a framework for understanding how compositional context and supercoiling can impose feedback on the intended architecture of a synthetic gene network. As a proof of concept, we engineer a genetic toggle switch exploiting compositional context effects to improve its threshold detection and memory capabilities.
In the second part of this thesis, we examine a series of theoretical and computational tools from dynamical systems theory that assist in engineering novel biochemical reaction networks. We briefly review the concept of dynamical structure functions and network reconstruction as tools for understanding biochemical reaction networks. In particular, we review the concept of resource-loading, show that resource-loading can lead to coupling interactions among biochemical species, and that by estimating a dynamical structure function from experimental data, it is possible to quantify resource loading effects in practice. We illustrate the importance of knowing these loading effects through several example systems, showing that crosstalk imbalance in feed-forward loops can lead to performance limitations. However, since biochemical reaction networks are generally large, in practice, only portions of the global network can be reconstructed at a time. We show, with a combination of theory, simulation, modeling and experiments, it is possible to reconstruct the dynamical structure function of a large-scale biochemical network using a series of network reconstruction experiments. We then demonstrate how the dynamical structure function can be used to analyze context interference and how these perturbations interfere with performance. We illustrate these ideas with several classes of standard biological networks, e.g. autocatalytic systems, cascade systems, and input-coupled systems.
Finally, in the third part of this thesis, we consider models for context interference in stochastic chemical reaction networks. We address the problem of representing a biological system and its environment using a stochastic modeling framework. We first introduce a decomposition of the global chemical reaction system into two systems: a system of interest and its environment. We then present and derive a decomposition of the chemical master equation to achieve a representation describing the dynamics of the system of interest, perturbed by an environmental disturbance. We use this decomposition to model examples of two types of environmental disturbances: the disturbance a system experiences through loading effects from limited resources and the disturbance a system experiences when perturbed by an antibiotic that modifies transcription or translation rates.</p