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The Importance of Spin for Observing Gravitational Waves from Coalescing Compact Binaries with LIGO and Virgo
Get PDFGeneral Relativity predicts the existence of gravitational waves, which carry information about the physical and dynamical properties of their source. One of the many promising sources of gravitational waves observable by ground-based instruments, such as in LIGO and Virgo, is the coalescence of two compact objects (neutron star or black hole). Black holes and neutron stars sometimes form binaries with short orbital periods, radiating so strongly in gravitational waves that they coalesce on astrophysically short timescales. General Relativity gives precise predictions for the form of the signal emitted by these systems. The most recent searches for theses events used waveform models that neglected the effects of black hole and neutron star spin. However, real astrophysical compact objects, especially black holes, are expected to have large spins. We demonstrate here a data analysis infrastructure which achieves an improved sensitivity to spinning compact binaries by the inclusion of spin effects in the template waveforms. This infrastructure is designed for scalable, low-latency data analysis, ideal for rapid electromagnetic followup of gravitational wave events
Protein Structure Refinement Algorithms
Get PDFProtein structure prediction has remained a major challenge in structural biology for more than half a century. Accelerated and cost efficient sequencing technologies have allowed researchers to sequence new organisms and discover new protein sequences. Novel protein structure prediction technologies will allow researchers to study the structure of proteins and to determine their roles in the underlying biology processes and develop novel therapeutics.
Difficulty of the problem stems from two folds: (a) describing the energy landscape that corresponds to the protein structure, commonly referred to as force field problem; and (b) sampling of the energy landscape, trying to find the lowest energy configuration that is hypothesized to be the native state of the structure in solution. The two problems are interweaved and they have to be solved simultaneously. This thesis is composed of three major contributions. In the first chapter we describe a novel high-resolution protein structure refinement algorithm called GRID. In the second chapter we present REMCGRID, an algorithm for generation of low energy decoy sets. In the third chapter, we present a machine learning approach to ranking decoys by incorporating coarse-grain features of protein structures.</p
Neuronal Mechanism of State Control in Drosophila melanogaster
Get PDFThe changes in internal states, such as fear, hunger and sleep affect behavioral responses in animals. In most of the cases, these state-dependent influences are “pleiotropic”: one state affects multiple sensory modalities and behaviors; “scalable”: the strengths and choices of such modulations differ depending on the imminence of demands; and “persistent”: once the state is switched on the effects last even after the internal demands are off. These prominent features of state-control enable animals to adjust their behavioral responses depending on their internal demands. Here, we studied the neuronal mechanisms of state-controls by investigating energy-deprived state (hunger state) and social-deprived state of fruit flies, Drosophila melanogaster, as prototypic models. To approach these questions, we developed two novel methods: a genetically based method to map sites of neuromodulation in the brain and optogenetic tools in Drosophila.
These methods, and genetic perturbations, reveal that the effect of hunger to alter behavioral sensitivity to gustatory cues is mediate by two distinct neuromodulatory pathways. The neuropeptide F (NPF) – dopamine (DA) pathway increases sugar sensitivity under mild starvation, while the adipokinetic hormone (AKH)- short neuropeptide F (sNPF) pathway decreases bitter sensitivity under severe starvation. These two pathways are recruited under different levels of energy demands without any cross interaction. Effects of both of the pathways are mediated by modulation of the gustatory sensory neurons, which reinforce the concept that sensory neurons constitute an important locus for state-dependent control of behaviors. Our data suggests that multiple independent neuromodulatory pathways are underlying pleiotropic and scalable effects of the hunger state.
In addition, using optogenetic tool, we show that the neural control of male courtship song can be separated into probabilistic/biasing, and deterministic/command-like components. The former, but not the latter, neurons are subject to functional modulation by social experience, supporting the idea that they constitute a locus of state-dependent influence. Interestingly, moreover, brief activation of the former, but not the latter, neurons trigger persistent behavioral response for more than 10 min. Altogether, these findings and new tools described in this dissertation offer new entry points for future researchers to understand the neuronal mechanism of state control.</p
Towards Understanding the Mixing Characteristics of Turbulent Buoyant Flows
Get PDFThis work proposes a new simulation methodology in which variable density turbulent flows can be studied in the context of a mixing layer with or without the presence of gravity. Specifically, this methodology is developed to probe the nature of non-buoyantly-driven (i.e. isotropically-driven) or buoyantly-driven mixing deep inside a mixing layer. Numerical forcing methods are incorporated into both the velocity and scalar fields, which extends the length of time over which mixing physics can be studied. The simulation framework is designed to allow for independent variation of four non-dimensional parameters, including the Reynolds, Richardson, Atwood, and Schmidt numbers. Additionally, the governing equations are integrated in such a way to allow for the relative magnitude of buoyant energy production and non-buoyant energy production to be varied.
The computational requirements needed to implement the proposed configuration are presented. They are justified in terms of grid resolution, order of accuracy, and transport scheme. Canonical features of turbulent buoyant flows are reproduced as validation of the proposed methodology. These features include the recovery of isotropic Kolmogorov scales under buoyant and non-buoyant conditions, the recovery of anisotropic one-dimensional energy spectra under buoyant conditions, and the preservation of known statistical distributions in the scalar field, as found in other DNS studies.
This simulation methodology is used to perform a parametric study of turbulent buoyant flows to discern the effects of varying the Reynolds, Richardson, and Atwood numbers on the resulting state of mixing. The effects of the Reynolds and Atwood numbers are isolated by looking at two energy dissipation rate conditions under non-buoyant (variable density) and constant density conditions. The effects of Richardson number are isolated by varying the ratio of buoyant energy production to total energy production from zero (non-buoyant) to one (entirely buoyant) under constant Atwood number, Schmidt number, and energy dissipation rate conditions. It is found that the major differences between non-buoyant and buoyant turbulent flows are contained in the transfer spectrum and longitudinal structure functions, while all other metrics are largely similar (e.g. energy spectra, alignment characteristics of the strain-rate tensor). Also, despite the differences noted between fully buoyant and non-buoyant turbulent fields, the scalar field, in all cases, is unchanged by these. The mixing dynamics in the scalar field are found to be insensitive to the source of turbulent kinetic energy production (non-buoyant vs. buoyant).</p
Optical Designs for Improved Solar Cell Performance
Get PDFThe solar resource is the most abundant renewable resource on earth, yet it is currently exploited with relatively low efficiencies. To make solar energy more affordable, we can either reduce the cost of the cell or increase the efficiency with a similar cost cell. In this thesis, we consider several different optical approaches to achieve these goals. First, we consider a ray optical model for light trapping in silicon microwires. With this approach, much less material can be used, allowing for a cost savings. We next focus on reducing the escape of radiatively emitted and scattered light from the solar cell. With this angle restriction approach, light can only enter and escape the cell near normal incidence, allowing for thinner cells and higher efficiencies. In Auger-limited GaAs, we find that efficiencies greater than 38% may be achievable, a significant improvement over the current world record. To experimentally validate these results, we use a Bragg stack to restrict the angles of emitted light. Our measurements show an increase in voltage and a decrease in dark current, as less radiatively emitted light escapes. While the results in GaAs are interesting as a proof of concept, GaAs solar cells are not currently made on the production scale for terrestrial photovoltaic applications. We therefore explore the application of angle restriction to silicon solar cells. While our calculations show that Auger-limited cells give efficiency increases of up to 3% absolute, we also find that current amorphous silicion-crystalline silicon heterojunction with intrinsic thin layer (HIT) cells give significant efficiency gains with angle restriction of up to 1% absolute. Thus, angle restriction has the potential for unprecedented one sun efficiencies in GaAs, but also may be applicable to current silicon solar cell technology. Finally, we consider spectrum splitting, where optics direct light in different wavelength bands to solar cells with band gaps tuned to those wavelengths. This approach has the potential for very high efficiencies, and excellent annual power production. Using a light-trapping filtered concentrator approach, we design filter elements and find an optimal design. Thus, this thesis explores silicon microwires, angle restriction, and spectral splitting as different optical approaches for improving the cost and efficiency of solar cells
Dynamic Rupture Simulation Integrated with Earthquake Observations
Get PDFDynamic rupture simulations are unique in their contributions to the study of earthquake physics. The current rapid development of dynamic rupture simulations poses several new questions: Do the simulations reflect the real world? Do the simulations have predictive power? Which one should we believe when the simulations disagree? This thesis illustrates how integration with observations can help address these questions and reduce the effects of non-uniqueness of both dynamic rupture simulations and kinematic inversion problems. Dynamic rupture simulations with observational constraints can effectively identify non-physical features inferred from observations. Moreover, the integrative technique can also provide more physical insights into the mechanisms of earthquakes. This thesis demonstrates two examples of such kinds of integration: dynamic rupture simulations of the Mw 9.0 2011 Tohoku-Oki earthquake and of earthquake ruptures in damaged fault zones:
(1) We develop simulations of the Tohoku-Oki earthquake based on a variety of observations and minimum assumptions of model parameters. The simulations provide realistic estimations of stress drop and fracture energy of the region and explain the physical mechanisms of high-frequency radiation in the deep region. We also find that the overridding subduction wedge contributes significantly to the up-dip rupture propagation and large final slip in the shallow region. Such findings are also applicable to other megathrust earthquakes.
(2) Damaged fault zones are usually found around natural faults, but their effects on earthquake ruptures have been largely unknown. We simulate earthquake ruptures in damaged fault zones with material properties constrained by seismic and geological observations. We show that reflected waves in fault zones are effective at generating pulse-like ruptures and head waves tend to accelerate and decelerate rupture speeds. These mechanisms are robust in natural fault zones with large attenuation and off-fault plasticity. Moreover, earthquakes in damaged fault zones can propagate at super-Rayleigh speeds that are unstable in homogeneous media. Supershear transitions in fault zones do not require large fault stresses. In the end, we present observations in the Big Bear region, where variability of rupture speeds of small earthquakes correlates with the laterally variable materials in a damaged fault zone. </p
Advanced Density Functional Theory Methods tor Materials Science
Get PDFIn this work we chiefly deal with two broad classes of problems in computational materials science, determining the doping mechanism in a semiconductor and developing an extreme condition equation of state. While solving certain aspects of these questions is well-trodden ground, both require extending the reach of existing methods to fully answer them. Here we choose to build upon the framework of density functional theory (DFT) which provides an efficient means to investigate a system from a quantum mechanics description.
Zinc Phosphide (Zn3P2) could be the basis for cheap and highly efficient solar cells. Its use in this regard is limited by the difficulty in n-type doping the material. In an effort to understand the mechanism behind this, the energetics and electronic structure of intrinsic point defects in zinc phosphide are studied using generalized Kohn-Sham theory and utilizing the Heyd, Scuseria, and Ernzerhof (HSE) hybrid functional for exchange and correlation. Novel 'perturbation extrapolation' is utilized to extend the use of the computationally expensive HSE functional to this large-scale defect system. According to calculations, the formation energy of charged phosphorus interstitial defects are very low in n-type Zn3P2 and act as 'electron sinks', nullifying the desired doping and lowering the fermi-level back towards the p-type regime. Going forward, this insight provides clues to fabricating useful zinc phosphide based devices. In addition, the methodology developed for this work can be applied to further doping studies in other systems.
Accurate determination of high pressure and temperature equations of state is fundamental in a variety of fields. However, it is often very difficult to cover a wide range of temperatures and pressures in an laboratory setting. Here we develop methods to determine a multi-phase equation of state for Ta through computation. The typical means of investigating thermodynamic properties is via ’classical’ molecular dynamics where the atomic motion is calculated from Newtonian mechanics with the electronic effects abstracted away into an interatomic potential function. For our purposes, a ’first principles’ approach such as DFT is useful as a classical potential is typically valid for only a portion of the phase diagram (i.e. whatever part it has been fit to). Furthermore, for extremes of temperature and pressure quantum effects become critical to accurately capture an equation of state and are very hard to capture in even complex model potentials. This requires extending the inherently zero temperature DFT to predict the finite temperature response of the system. Statistical modelling and thermodynamic integration is used to extend our results over all phases, as well as phase-coexistence regions which are at the limits of typical DFT validity. We deliver the most comprehensive and accurate equation of state that has been done for Ta. This work also lends insights that can be applied to further equation of state work in many other materials.</p
Design Strategies for Ultra-High Efficiency Photovoltaics
Get PDFWhile concentrator photovoltaic cells have shown significant improvements in efficiency in the past ten years, once these cells are integrated into concentrating optics, connected to a power conditioning system and deployed in the field, the overall module efficiency drops to only 34 to 36%. This efficiency is impressive compared to conventional flat plate modules, but it is far short of the theoretical limits for solar energy conversion. Designing a system capable of achieving ultra high efficiency of 50% or greater cannot be achieved by refinement and iteration of current design approaches.
This thesis takes a systems approach to designing a photovoltaic system capable of 50% efficient performance using conventional diode-based solar cells. The effort began with an exploration of the limiting efficiency of spectrum splitting ensembles with 2 to 20 sub cells in different electrical configurations. Incorporating realistic non-ideal performance with the computationally simple detailed balance approach resulted in practical limits that are useful to identify specific cell performance requirements. This effort quantified the relative benefit of additional cells and concentration for system efficiency, which will help in designing practical optical systems.
Efforts to improve the quality of the solar cells themselves focused on the development of tunable lattice constant epitaxial templates. Initially intended to enable lattice matched multijunction solar cells, these templates would enable increased flexibility in band gap selection for spectrum splitting ensembles and enhanced radiative quality relative to metamorphic growth. The III-V material family is commonly used for multijunction solar cells both for its high radiative quality and for the ease of integrating multiple band gaps into one monolithic growth. The band gap flexibility is limited by the lattice constant of available growth templates. The virtual substrate consists of a thin III-V film with the desired lattice constant. The film is grown strained on an available wafer substrate, but the thickness is below the dislocation nucleation threshold. By removing the film from the growth substrate, allowing the strain to relax elastically, and bonding it to a supportive handle, a template with the desired lattice constant is formed. Experimental efforts towards this structure and initial proof of concept are presented.
Cells with high radiative quality present the opportunity to recover a large amount of their radiative losses if they are incorporated in an ensemble that couples emission from one cell to another. This effect is well known, but has been explored previously in the context of sub cells that independently operate at their maximum power point. This analysis explicitly accounts for the system interaction and identifies ways to enhance overall performance by operating some cells in an ensemble at voltages that reduce the power converted in the individual cell. Series connected multijunctions, which by their nature facilitate strong optical coupling between sub-cells, are reoptimized with substantial performance benefit.
Photovoltaic efficiency is usually measured relative to a standard incident spectrum to allow comparison between systems. Deployed in the field systems may differ in energy production due to sensitivity to changes in the spectrum. The series connection constraint in particular causes system efficiency to decrease as the incident spectrum deviates from the standard spectral composition. This thesis performs a case study comparing performance of systems over a year at a particular location to identify the energy production penalty caused by series connection relative to independent electrical connection.</p
Nanoelectromechanical Membranes for Multimode Mass Spectrometry
Get PDFNanoelectromechanical systems (NEMS) represent the next wave in miniaturizing various electrical and mechanical devices used in a variety of fields, such as physics, biology, and engineering. In particular, NEMS devices have high surface area to volume ratios, low power consumption, low mass, and extremely small footprints. These properties allow NEMS to explore more fundamental regimes of matter. Current NEMS mass spectrometry advancements have only utilized doubly-clamped beams and cantilevers. However to expand the measurement capabilities of NEMS mass spectrometry, we utilize a circular membrane geometry in order to build upon the existing measurements in 1 spatial dimension to measure mass spatially in 2-dimensions. Furthermore, membranes should provide a larger potential mass dynamic range. For this experiment, we utilize circular piezoelectric membranes of aluminum nitride and molybdenum stacks. For mass deposition, we utilize a technique known as matrix-assisted laser desorption/ionization (MALDI), which focuses a pulsed UV laser onto the desired sample embedded in a corresponding matrix. The energy causes a plume of particles to desorb off the sample and towards the device. As a particle lands on the device, we are able to deduce its mass from the shift in its resonant frequency. In particular we need to measure the first three resonant frequencies, since the frequency shifts also depend on the location the particle landed on the device. Here we show the viability of our detection setup, mass deposition setup, and our mass deposition results
