Matching Items (41)
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Description
A thorough exploration of star formation necessitates observation across the electromagnetic spectrum. In particular, observations in the submillimeter and ultra-violet allow one to observe very early stage star formation and to trace the evolution from molecular cloud collapse to stellar ignition. Submillimeter observations are essential for piercing the heart of

A thorough exploration of star formation necessitates observation across the electromagnetic spectrum. In particular, observations in the submillimeter and ultra-violet allow one to observe very early stage star formation and to trace the evolution from molecular cloud collapse to stellar ignition. Submillimeter observations are essential for piercing the heart of heavily obscured stellar nurseries to observe star formation in its infancy. Ultra-violet observations allow one to observe stars just after they emerge from their surrounding environment, allowing higher energy radiation to escape. To make detailed observations of early stage star formation in both spectral regimes requires state-of-the-art detector technology and instrumentation. In this dissertation, I discuss the calibration and feasibility of detectors developed by Lawrence Berkeley National Laboratory and specially processed at the Jet Propulsion Laboratory to increase their quantum efficiency at far-ultraviolet wavelengths. A cursory treatment of the delta-doping process is presented, followed by a thorough discussion of calibration procedures developed at JPL and in the Laboratory for Astronomical and Space Instrumentation at ASU. Subsequent discussion turns to a novel design for a Modular Imager Cell forming one possible basis for construction of future large focal plane arrays. I then discuss the design, fabrication, and calibration of a sounding rocket imaging system developed using the MIC and these specially processed detectors. Finally, I discuss one scientific application of sub-mm observations. I used data from the Heinrich Hertz Sub-millimeter Telescope and the Sub-Millimeter Array (SMA) to observe sub-millimeter transitions and continuum emission towards AFGL 2591. I tested the use of vibrationally excited HCN emission to probe the protostellar accretion disk structure. I measured vibrationally excited HCN line ratios in order to elucidate the appropriate excitation mechanism. I find collisional excitation to be dominant, showing the emission originates in extremely dense (n&sim10;11 cm-3), warm (T&sim1000; K) gas. Furthermore, from the line profile of the v=(0, 22d, 0) transition, I find evidence for a possible accretion disk.
ContributorsVeach, Todd Justin (Author) / Scowen, Paul A (Thesis advisor) / Groppi, Christopher E (Thesis advisor) / Beasley, Matthew N (Committee member) / Rhoads, James E (Committee member) / Windhorst, Rogier A (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Understanding the properties and formation histories of individual stars in galaxies remains one of the most important areas in astrophysics. The impact of the Hubble Space Telescope<\italic> (HST<\italic>) has been revolutionary, providing deep observations of nearby galaxies at high resolution and unprecedented sensitivity over a wavelength range from near-ultraviolet to

Understanding the properties and formation histories of individual stars in galaxies remains one of the most important areas in astrophysics. The impact of the Hubble Space Telescope<\italic> (HST<\italic>) has been revolutionary, providing deep observations of nearby galaxies at high resolution and unprecedented sensitivity over a wavelength range from near-ultraviolet to near-infrared. In this study, I use deep HST<\italic> imaging observations of three nearby star-forming galaxies (M83, NGC 4214, and CGCG 269-049) based on the HST<\italic> observations, in order to provide to construct color-magnitude and color-color diagrams of their resolved stellar populations. First, I select 50 regions in the spiral arm and inter-arm areas of M83, and determine the age distribution of the luminous stellar populations in each region. I developed an innovative method of star-by-star correction for internal extinction to improve stellar age and mass estimates. I compare the extinction-corrected ages of the 50 regions with those determined from several independent methods. The young stars are much more likely to be found in concentrated aggregates along spiral arms, while older stars are more dispersed. These results are consistent with a scenario where star formation is associated with the spiral arms, and stars form primarily in star clusters before dispersing on short timescales to form the field population. I address the effects of spatial resolution on the measured colors, magnitudes, and age estimates. While individual stars can occasionally show measurable differences in the colors and magnitudes, the age estimates for entire regions are only slightly affected. The same procedure is applied to nearby starbursting dwarf NGC 4214 to study the distributions of young and old stellar populations. Lastly, I describe the analysis of the HST<\italic> and Spitzer Space Telescope<\italic> observations of the extremely metal-poor dwarf galaxy (XMPG) CGCG 269-049 at a distance of 4.96 Mpc. This galaxy is one of the most metal-poor known with 12+log(O/H)=7.43. I find clear evidence for the presence of an old stellar population in CGCG~269-049, ruling out the possibility that this galaxy is forming its first generation of stars, as originally proposed for XMPGs. This comprehensive study of resolved stellar populations in three nearby galaxies provides detailed view of the current state of star formation and evolution of galaxies.
ContributorsKim, Hwihyun (Author) / Windhorst, Rogier A (Thesis advisor) / Jansen, Rolf A (Committee member) / Rhoads, James E (Committee member) / Scannapieco, Evan (Committee member) / Young, Patrick (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Quasars, the visible phenomena associated with the active accretion phase of super- massive black holes found in the centers of galaxies, represent one of the most energetic processes in the Universe. As matter falls into the central black hole, it is accelerated and collisionally heated, and the radiation emitted can

Quasars, the visible phenomena associated with the active accretion phase of super- massive black holes found in the centers of galaxies, represent one of the most energetic processes in the Universe. As matter falls into the central black hole, it is accelerated and collisionally heated, and the radiation emitted can outshine the combined light of all the stars in the host galaxy. Studies of quasar host galaxies at ultraviolet to near-infrared wavelengths are fundamentally limited by the precision with which the light from the central quasar accretion can be disentangled from the light of stars in the surrounding host galaxy. In this Dissertation, I discuss direct imaging of quasar host galaxies at redshifts z ≃ 2 and z ≃ 6 using new data obtained with the Hubble Space Telescope. I describe a new method for removing the point source flux using Markov Chain Monte Carlo parameter estimation and simultaneous modeling of the point source and host galaxy. I then discuss applications of this method to understanding the physical properties of high-redshift quasar host galaxies including their structures, luminosities, sizes, and colors, and inferred stellar population properties such as age, mass, and dust content.
ContributorsMechtley, Matt R (Author) / Windhorst, Rogier A (Thesis advisor) / Butler, Nathaniel (Committee member) / Jansen, Rolf A (Committee member) / Rhoads, James (Committee member) / Scowen, Paul (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Advances in experimental techniques have allowed for investigation of molecular dynamics at ever smaller temporal and spatial scales. There is currently a varied and growing body of literature which demonstrates the phenomenon of \emph{anomalous diffusion} in physics, engineering, and biology. In particular many diffusive type processes in the cell have

Advances in experimental techniques have allowed for investigation of molecular dynamics at ever smaller temporal and spatial scales. There is currently a varied and growing body of literature which demonstrates the phenomenon of \emph{anomalous diffusion} in physics, engineering, and biology. In particular many diffusive type processes in the cell have been observed to follow a power law $\left \propto t^\alpha$ scaling of the mean square displacement of a particle. This contrasts with the expected linear behavior of particles undergoing normal diffusion. \emph{Anomalous sub-diffusion} ($\alpha<1$) has been attributed to factors such as cytoplasmic crowding of macromolecules, and trap-like structures in the subcellular environment non-linearly slowing the diffusion of molecules. Compared to normal diffusion, signaling molecules in these constrained spaces can be more concentrated at the source, and more diffuse at longer distances, potentially effecting the signalling dynamics. As diffusion at the cellular scale is a fundamental mechanism of cellular signaling and additionally is an implicit underlying mathematical assumption of many canonical models, a closer look at models of anomalous diffusion is warranted. Approaches in the literature include derivations of fractional differential diffusion equations (FDE) and continuous time random walks (CTRW). However these approaches are typically based on \emph{ad-hoc} assumptions on time- and space- jump distributions. We apply recent developments in asymptotic techniques on collisional kinetic equations to develop a FDE model of sub-diffusion due to trapping regions and investigate the nature of the space/time probability distributions assosiated with trapping regions. This approach both contrasts and compliments the stochastic CTRW approach by positing more physically realistic underlying assumptions on the motion of particles and their interactions with trapping regions, and additionally allowing varying assumptions to be applied individually to the traps and particle kinetics.
ContributorsHoleva, Thomas Matthew (Author) / Ringhofer, Christian (Thesis advisor) / Baer, Steve (Thesis advisor) / Crook, Sharon (Committee member) / Gardner, Carl (Committee member) / Taylor, Jesse (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Numerical simulations are very helpful in understanding the physics of the formation of structure and galaxies. However, it is sometimes difficult to interpret model data with respect to observations, partly due to the difficulties and background noise inherent to observation. The goal, here, is to attempt to bridge this ga

Numerical simulations are very helpful in understanding the physics of the formation of structure and galaxies. However, it is sometimes difficult to interpret model data with respect to observations, partly due to the difficulties and background noise inherent to observation. The goal, here, is to attempt to bridge this gap between simulation and observation by rendering the model output in image format which is then processed by tools commonly used in observational astronomy. Images are synthesized in various filters by folding the output of cosmological simulations of gasdynamics with star-formation and dark matter with the Bruzual- Charlot stellar population synthesis models. A variation of the Virgo-Gadget numerical simulation code is used with the hybrid gas and stellar formation models of Springel and Hernquist (2003). Outputs taken at various redshifts are stacked to create a synthetic view of the simulated star clusters. Source Extractor (SExtractor) is used to find groupings of stellar populations which are considered as galaxies or galaxy building blocks and photometry used to estimate the rest frame luminosities and distribution functions. With further refinements, this is expected to provide support for missions such as JWST, as well as to probe what additional physics are needed to model the data. The results show good agreement in many respects with observed properties of the galaxy luminosity function (LF) over a wide range of high redshifts. In particular, the slope (alpha) when fitted to the standard Schechter function shows excellent agreement both in value and evolution with redshift, when compared with observation. Discrepancies of other properties with observation are seen to be a result of limitations of the simulation and additional feedback mechanisms which are needed.
ContributorsMorgan, Robert (Author) / Windhorst, Rogier A (Thesis advisor) / Scannapieco, Evan (Committee member) / Rhoads, James (Committee member) / Gardner, Carl (Committee member) / Belitsky, Andrei (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Factory production is stochastic in nature with time varying input and output processes that are non-stationary stochastic processes. Hence, the principle quantities of interest are random variables. Typical modeling of such behavior involves numerical simulation and statistical analysis. A deterministic closure model leading to a second

Factory production is stochastic in nature with time varying input and output processes that are non-stationary stochastic processes. Hence, the principle quantities of interest are random variables. Typical modeling of such behavior involves numerical simulation and statistical analysis. A deterministic closure model leading to a second order model for the product density and product speed has previously been proposed. The resulting partial differential equations (PDE) are compared to discrete event simulations (DES) that simulate factory production as a time dependent M/M/1 queuing system. Three fundamental scenarios for the time dependent influx are studied: An instant step up/down of the mean arrival rate; an exponential step up/down of the mean arrival rate; and periodic variation of the mean arrival rate. It is shown that the second order model, in general, yields significant improvement over current first order models. Specifically, the agreement between the DES and the PDE for the step up and for periodic forcing that is not too rapid is very good. Adding diffusion to the PDE further improves the agreement. The analysis also points to fundamental open issues regarding the deterministic modeling of low signal-to-noise ratio for some stochastic processes and the possibility of resonance in deterministic models that is not present in the original stochastic process.
ContributorsWienke, Matthew (Author) / Armbruster, Dieter (Thesis advisor) / Jones, Donald (Committee member) / Platte, Rodrigo (Committee member) / Gardner, Carl (Committee member) / Ringhofer, Christian (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Swarms of animals, fish, birds, locusts etc. are a common occurrence but their coherence and method of organization poses a major question for mathematics and biology.The Vicsek and the Attraction-Repulsion are two models that have been proposed to explain the emergence of collective motion. A major issue

Swarms of animals, fish, birds, locusts etc. are a common occurrence but their coherence and method of organization poses a major question for mathematics and biology.The Vicsek and the Attraction-Repulsion are two models that have been proposed to explain the emergence of collective motion. A major issue for the Vicsek Model is that its particles are not attracted to each other, leaving the swarm with alignment in velocity but without spatial coherence. Restricting the particles to a bounded domain generates global spatial coherence of swarms while maintaining velocity alignment. While individual particles are specularly reflected at the boundary, the swarm as a whole is not. As a result, new dynamical swarming solutions are found.

The Attraction-Repulsion Model set with a long-range attraction and short-range repulsion interaction potential typically stabilizes to a well-studied flock steady state solution. The particles for a flock remain spatially coherent but have no spatial bound and explore all space. A bounded domain with specularly reflecting walls traps the particles within a specific region. A fundamental refraction law for a swarm impacting on a planar boundary is derived. The swarm reflection varies from specular for a swarm dominated by

kinetic energy to inelastic for a swarm dominated by potential energy. Inelastic collisions lead to alignment with the wall and to damped pulsating oscillations of the swarm. The fundamental refraction law provides a one-dimensional iterative map that allows for a prediction and analysis of the trajectory of the center of mass of a flock in a channel and a square domain.

The extension of the wall collisions to a scattering experiment is conducted by setting two identical flocks to collide. The two particle dynamics is studied analytically and shows a transition from scattering: diverging flocks to bound states in the form of oscillations or parallel motions. Numerical studies of collisions of flocks show the same transition where the bound states become either a single translating flock or a rotating (mill).
ContributorsThatcher, Andrea (Author) / Armbruster, Hans (Thesis advisor) / Motsch, Sebastien (Committee member) / Ringhofer, Christian (Committee member) / Platte, Rodrigo (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Inverse problems model real world phenomena from data, where the data are often noisy and models contain errors. This leads to instabilities, multiple solution vectors and thus ill-posedness. To solve ill-posed inverse problems, regularization is typically used as a penalty function to induce stability and allow for the incorporation of

Inverse problems model real world phenomena from data, where the data are often noisy and models contain errors. This leads to instabilities, multiple solution vectors and thus ill-posedness. To solve ill-posed inverse problems, regularization is typically used as a penalty function to induce stability and allow for the incorporation of a priori information about the desired solution. In this thesis, high order regularization techniques are developed for image and function reconstruction from noisy or misleading data. Specifically the incorporation of the Polynomial Annihilation operator allows for the accurate exploitation of the sparse representation of each function in the edge domain.

This dissertation tackles three main problems through the development of novel reconstruction techniques: (i) reconstructing one and two dimensional functions from multiple measurement vectors using variance based joint sparsity when a subset of the measurements contain false and/or misleading information, (ii) approximating discontinuous solutions to hyperbolic partial differential equations by enhancing typical solvers with l1 regularization, and (iii) reducing model assumptions in synthetic aperture radar image formation, specifically for the purpose of speckle reduction and phase error correction. While the common thread tying these problems together is the use of high order regularization, the defining characteristics of each of these problems create unique challenges.

Fast and robust numerical algorithms are also developed so that these problems can be solved efficiently without requiring fine tuning of parameters. Indeed, the numerical experiments presented in this dissertation strongly suggest that the new methodology provides more accurate and robust solutions to a variety of ill-posed inverse problems.
ContributorsScarnati, Theresa (Author) / Gelb, Anne (Thesis advisor) / Platte, Rodrigo (Thesis advisor) / Cochran, Douglas (Committee member) / Gardner, Carl (Committee member) / Sanders, Toby (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Predicting resistant prostate cancer is critical for lowering medical costs and improving the quality of life of advanced prostate cancer patients. I formulate, compare, and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen (PSA). I accomplish these tasks by employing clinical data of locally advanced

Predicting resistant prostate cancer is critical for lowering medical costs and improving the quality of life of advanced prostate cancer patients. I formulate, compare, and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen (PSA). I accomplish these tasks by employing clinical data of locally advanced prostate cancer patients undergoing androgen deprivation therapy (ADT). I demonstrate that the inverse problem of parameter estimation might be too complicated and simply relying on data fitting can give incorrect conclusions, since there is a large error in parameter values estimated and parameters might be unidentifiable. I provide confidence intervals to give estimate forecasts using data assimilation via an ensemble Kalman Filter. Using the ensemble Kalman Filter, I perform dual estimation of parameters and state variables to test the prediction accuracy of the models. Finally, I present a novel model with time delay and a delay-dependent parameter. I provide a geometric stability result to study the behavior of this model and show that the inclusion of time delay may improve the accuracy of predictions. Also, I demonstrate with clinical data that the inclusion of the delay-dependent parameter facilitates the identification and estimation of parameters.
ContributorsBaez, Javier (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric (Committee member) / Crook, Sharon (Committee member) / Gardner, Carl (Committee member) / Nagy, John (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Need-based transfers (NBTs) are a form of risk-pooling in which binary welfare exchanges

occur to preserve the viable participation of individuals in an economy, e.g. reciprocal gifting

of cattle among East African herders or food sharing among vampire bats. With the

broad goal of better understanding the mathematics of such binary welfare and

Need-based transfers (NBTs) are a form of risk-pooling in which binary welfare exchanges

occur to preserve the viable participation of individuals in an economy, e.g. reciprocal gifting

of cattle among East African herders or food sharing among vampire bats. With the

broad goal of better understanding the mathematics of such binary welfare and risk pooling,

agent-based simulations are conducted to explore socially optimal transfer policies

and sharing network structures, kinetic exchange models that utilize tools from the kinetic

theory of gas dynamics are utilized to characterize the wealth distribution of an NBT economy,

and a variant of repeated prisoner’s dilemma is analyzed to determine whether and

why individuals would participate in such a system of reciprocal altruism.

From agent-based simulation and kinetic exchange models, it is found that regressive

NBT wealth redistribution acts as a cutting stock optimization heuristic that most efficiently

matches deficits to surpluses to improve short-term survival; however, progressive

redistribution leads to a wealth distribution that is more stable in volatile environments and

therefore is optimal for long-term survival. Homogeneous sharing networks with low variance

in degree are found to be ideal for maintaining community viability as the burden and

benefit of NBTs is equally shared. Also, phrasing NBTs as a survivor’s dilemma reveals

parameter regions where the repeated game becomes equivalent to a stag hunt or harmony

game, and thus where cooperation is evolutionarily stable.
ContributorsKayser, Kirk (Author) / Armbruster, Dieter (Thesis advisor) / Lampert, Adam (Committee member) / Ringhofer, Christian (Committee member) / Motsch, Sebastien (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Created2018