Astrophysics and Astronomy Commons^™

Classification Of Stars From Redshifted Stellar Spectra Utilizing Machine Learning, Michael J. Brice

All Master's Theses

The classification of stellar spectra is a fundamental task in stellar astrophysics. There have been many explorations into the automated classification of stellar spectra but few that involve the Sloan Digital Sky Survey (SDSS). Stellar spectra from the SDSS are applied to standard classification methods such as K-Nearest Neighbors, Random Forest, and Support Vector Machine to automatically classify the spectra. Stellar spectra are high dimensional data and the dimensionality is reduced using standard Feature Selection methods such as Chi-Squared and Fisher score and with domain-specific astronomical knowledge because classifiers work in low dimensional space. These methods are utilized to classify …

Sky Surveys Scheduling Using Reinforcement Learning, Andres Felipe Alba Hernandez

Graduate Research Theses & Dissertations

Modern cosmic sky surveys (e.g., CMB S4, DES, LSST) collect a complex diversity of astronomical objects. Each of class of objects presents different requirements for observation time and sensitivity. For determining the best sequence of exposures for mapping the sky systematically, conventional scheduling methods do not optimize the use of survey time and resources. Dynamic sky survey scheduling is an NP-hard problem that has been therefore treated primarily with heuristic methods. We present an alternative scheduling method based on reinforcement learning (RL) that aims to optimize the use of telescope resources for scheduling sky surveys.

We present an exploration of …

High-Speed Distributed Data Process Of Photometric Astronomical Data, Paul Doyle

Other

Since the 1970s the CCD has been the principle method of measuring flux to calculate the apparent magnitude of celestial objects within astronomical photometry. Each CCD image must be digitally cleaned and calibrated prior to its use. As data archives increase in size to Petabytes, the data processing challenge requires image processing techniques to continue to exceed the rate of data capture.

This paper describes NIMBUS, a rapidly scalable, failure resilient distributed network architecture capable of processing CCD image data at a rate of hundreds of Terabytes per day. NIMBUS is implemented using a decentralized web queue to control the …

Modeling Recombination In Solar Cells, Paul Chery

Macalester Journal of Physics and Astronomy

Solar cells are a competitive alternative to nonrenewable energy sources such as fossil fuels. However, the efficiency of these devices is limited by photogenerated carrier recombination. We use a finite difference numerical model to study recombination phenomena in the absorber layer of solar cells including alternate recombination models and the effects of spatial distribution of recombination centers. We compare the effect of using the constant lifetime approximation for recombination to the full Shockley-Read-Hall expression in Silicon solar cells and find that the constant lifetime approximation holds for high defect densities but not for high photon flux densities. Finally, we simulate …

An Analysis Of Frenkel Defects And Backgrounds Modeling For Supercdms Dark Matter Searches, Matthew Stein

Physics Theses and Dissertations

Years of astrophysical observations suggest that dark matter comprises more than ~80 % of all matter in the universe. Particle physics theories favor a weakly-interacting particle that could be directly detected in terrestrial experiments. The Super Cryogenic Dark Matter Search (SuperCDMS) Collaboration operates world-leading experiments to directly detect dark matter interacting with ordinary matter. The SuperCDMS Soudan experiment searched for weakly interacting massive particles (WIMPs) via their elastic-scattering interactions with nuclei in low-temperature germanium detectors.

During the operation of the SuperCDMS Soudan experiment, ²¹⁰Pb sources were installed to study background rejection of the Ge detectors. Data from these sources …

Introduction To The Usu Library Of Solutions To The Einstein Field Equations, Ian M. Anderson, Charles G. Torre

Tutorials on... in 1 hour or less

This is a Maple worksheet providing an introduction to the USU Library of Solutions to the Einstein Field Equations. The library is part of the DifferentialGeometry software project and is a collection of symbolic data and metadata describing solutions to the Einstein equations.

Dark Matter Halo Mass Function From Hpc N-Body Simulations, Da Bi, Isaac Shlosman, Emilio Romano-Diaz

Commonwealth Computational Summit

Dark matter (DM) dominates the matter in the Universe. Because of self-gravity, DM collapses and becomes clumpy, building the large-scale hierarchical structures. Baryons assemble within DM potential wells and form galaxies.

Because we can not directly observe DM halos, numerical simulations is the only way one can study their dynamics and other properties. Using N-body simulations, we can obtain the Halo Mass Function (HMF), which provides the abundance of DM halos as a function of their mass. The HMF depends weakly on cosmological redshift and is one of the basic tools in modern cosmology.

We use GIZMO --- a flexible, …

Formation Of Supermassive Black Holes In The Early Universe: High-Resolution Numerical Simulations Of Radiation Transfer Inside Collapsing Gas, Yang Luo, Kazem Ardaneh, Isaac Shlosman, Kentaro Nagamine, John Wise, Mitchell C. Begelman

Commonwealth Computational Summit

Observations of high-redshift quasars reveal that super massive black holes (SMBHs) with masses exceeding 10⁹ M_⊙ formed as early as redshift z ~ 7 [1,3,6]. This means that SMBHs have already formed ~700 million years after the Big Bang. How did such SMBHs could grow so quickly?

In this work, we use a modified and improved version of the blockstructured adaptive mesh refinement (AMR) code ENZO [2] to provide high spatial and temporal resolution for modeling the formation of SMBHs via direct collapse within dark matter (DM) halos at high redshifts. The radiation hydrodynamics equations are solved in …

Evolution Of Barred Galaxies In Spinning Dark Matter Halos: High Resolution N-Body Simulations At Dlx, Angela Collier, Isaac Shlosman, Clayton Heller

Commonwealth Computational Summit

Observations show that galaxies are dominated by stellar disks immersed in much more massive, slowly tumbling dark matter (DM) halos. Large fraction of galactic disks, at least 75%, are barred (see Hubble Fork on the right). Stellar bars form either via spontaneous break of axial symmetry or via galaxy interactions.

The formation and evolution of stellar bars is not fully understood. Stellar bar evolution is highly nonlinear and cannot be treated analytically. The main approach to study these disk-halo systems is via numerical simulations, whose goal is to explain why galaxies have such a wide range of morphologies as shown …

Data Mining By Grid Computing In The Search For Extrasolar Planets, Oisin Creaner [Thesis]

Doctoral

A system is presented here to provide improved precision in ensemble differential photometry. This is achieved by using the power of grid computing to analyse astronomical catalogues. This produces new catalogues of optimised pointings for each star, which maximise the number and quality of reference stars available. Astronomical phenomena such as exoplanet transits and small-scale structure within quasars may be observed by means of millimagnitude photometric variability on the timescale of minutes to hours. Because of atmospheric distortion, ground-based observations of these phenomena require the use of differential photometry whereby the target is compared with one or more reference stars. …

Investigating The Impact Of Unsupervised Feature-Extraction From Multi-Wavelength Image Data For Photometric Classification Of Stars, Galaxies And Qsos, Annika Lindh

Conference papers

Accurate classification of astronomical objects currently relies on spectroscopic data. Acquiring this data is time-consuming and expensive compared to photometric data. Hence, improving the accuracy of photometric classification could lead to far better coverage and faster classification pipelines. This paper investigates the benefit of using unsupervised feature-extraction from multi-wavelength image data for photometric classification of stars, galaxies and QSOs. An unsupervised Deep Belief Network is used, giving the model a higher level of interpretability thanks to its generative nature and layer-wise training. A Random Forest classifier is used to measure the contribution of the novel features compared to a set …

Investigating The Impact Of Unsupervised Feature-Extraction From Multi-Wavelength Image Data For Photometric Classification Of Stars, Galaxies And Qsos, Annika Lindh

Dissertations

This thesis reviews the current state of photometric classification in Astronomy and identifies two main gaps: a dependence on handcrafted rules, and a lack of interpretability in the more successful classifiers. To address this, Deep Learning and Computer Vision were used to create a more interpretable model, using unsupervised training to reduce human bias.

The main contribution is the investigation into the impact of using unsupervised feature-extraction from multi-wavelength image data for the classification task. The feature-extraction is achieved by implementing an unsupervised Deep Belief Network to extract lower-dimensionality features from the multi-wavelength image data captured by the Sloan Digital …

High Altitude Cosmic Ray Detection, Jordan D. Van Nest

2017 Academic High Altitude Conference

Cosmic rays are high energy atomic nuclei travelling near the speed of light that collide with atoms and molecules in Earth’s upper atmosphere (primarily with nitrogen and oxygen), breaking down into a shower of particles of various energies in the stratosphere. As they travel earthward, these particles continue to break down and lose energy which results in relatively little ionizing radiation reaching the surface. Due to the scattering of cosmic rays, the angle at which the rays enter the atmosphere can affect the number and energies of ionizing particles detected at various altitudes. When using a standard Geiger counter on …

Contributing To Astropy: A Community Python Library For Astronomers, Asra Nizami

Macalester Journal of Physics and Astronomy

This paper discusses the author’s contributions to two packages affiliated with Astropy, a community Python library for astronomers. The packages the author contributed to were modeling, a sub-package within the core Astropy package, and WCSAxes, an Astropy affiliated package, outside the core package.

Teaching Numerical Methods In The Context Of Galaxy Mergers, Maria Kourjanskaia

Physics

Methods of teaching numerical methods to solve ordinary differential equations in the context of galaxy mergers were explored. The research published in a paper by Toomre and Toomre in 1972 describing the formation of galactic tails and bridges from close tidal interactions was adapted into a project targeting undergraduate physics students. Typically undergraduate physics students only take one Computational Physics class in which various techniques and algorithms are taught. Although it is important to study computational physics techniques, it is just as important to apply this knowledge to a problem that is representative of what computational physics researchers are investigating …

The Parallelization And Optimization Of The N-Body Problem Using Openmp And Openmpi, Nicholas J. Carugati

Student Publications

The focus of this research is exploring the efficient ways we can implement the NBody problem. The N-Body problem, in the field of physics, is a problem in which predicts or simulates the movements of planets and how they interact with each other gravitationally. For this research, we are viewing if the simulation can execute efficiently by delegating the heavy computational work through different cores of a CPU. The approach that is being used to figure this out is by integrating the parallelization API OpenMP and the message-passing library OpenMPI into the code. Rather than all the code executing on …

Better Together

DePaul Magazine

Faculty have taken full advantage of the university's innovative intercollegiate grant program, and the resulting research is as interesting and diverse as the collaborators themselves. What is resulting is research on "Patient and Primary Care Provider Perspectives on Recreational and Therapeutic Cannabis Use Within a Changing Socioculltural and Political Context;" a new minor in climate change science and policy; a new class, Communication, Coding and Entrepreneurship; brain inflammation research; and the project "Cosmology Meets Continental Philosophy: Natural Laws and Why There Is Something Rather Than Nothing"

Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang

COBRA Preprint Series

Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …

Factorized Runge-Kutta-Chebyshev Methods, Stephen O'Sullivan

Conference papers

The second-order extended stability Factorized Runge-Kutta-Chebyshev (FRKC2) class of explicit schemes for the integration of large systems of PDEs with diffusive terms is presented. FRKC2 schemes are straightforward to implement through ordered sequences of forward Euler steps with complex stepsizes, and easily parallelised for large scale problems on distributed architectures.

Preserving 7 digits for accuracy at 16 digit precision, the schemes are theoretically capable of maintaining internal stability at acceleration factors in excess of 6000 with respect to standard explicit Runge-Kutta methods. The stability domains have approximately the same extents as those of RKC schemes, and are a third longer …

Study Solar Activity In The Backside Of The Sun, Catherine A. Gibbs

Von Braun Symposium Student Posters

No abstract provided.

Empyreal Radiance: An Application Of Sonification In The Field Of Astrophysics, Ryan Loth

Undergraduate Distinction Papers

Broadly, this paper discusses the application of sonification and its potential for increasing knowledge. The paper is broken up into three sections: the theory of sonification, sonification for artistic purposes, and lastly an extensive look at one process of sonification dealing with solar winds in space. Concerning the theory of sonification, the paper will divulge into the process of sonification and ask questions about the limitations of it as well. The second section discusses how sonification is a way to build the curiosity of not just scientists, but also the general public. The final section addresses my composition Empyreal Radiance …

Building A Scalable Global Data Processing Pipeline For Large Astronomical Photometric Datasets, Paul Doyle

Other

Astronomical photometry is the science of measuring the flux of a celestial object. Since its introduction, the CCD has been the principle method of measuring flux to calculate the apparent magnitude of an object. Each CCD image taken must go through a process of cleaning and calibration prior to its use. As the number of research telescopes increases the overall computing resources required for image processing also increases. Existing processing techniques are primarily sequential in nature, requiring increasingly powerful servers, faster disks and faster networks to process data. Existing High Performance Computing solutions involving high capacity data centres are complex …

Study Solar Activity In The Backside Of The Sun With The Stereo Mission, Catherine A. Gibbs

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.

Updating And Revising Star Camera For Future Flights Of Balloon Borne Experiment, Krystle N. Sy, Seth Hillbrand

STAR Program Research Presentations

The BLAST (Balloon-borne Large Aperture Submillimeter Telescope) experiment surveys the galaxy from altitudes of 100,000 ft in order to answer important cosmological questions, such as how stars are formed. This experiment is conducted above Antarctica to minimize unwanted noise. Two star cameras are used in the navigation systems to identify known stars. The cameras take pictures and match stars in the image to known star positions from a catalog stored in the star camera's computer. This is done using code written in C++, a computer programming language. In order to modernize the system, the code needs to be updated. A …

Neutrosophic Theory And Its Applications : Collected Papers - Vol. 1, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophic Theory means Neutrosophy applied in many fields in order to solve problems related to indeterminacy. Neutrosophy is a new branch of philosophy that studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. This theory considers every entity together with its opposite or negation and with their spectrum of neutralities in between them (i.e. entities supporting neither nor ). The and ideas together are referred to as . Neutrosophy is a generalization of Hegel's dialectics (the last one is based on and only). According to this theory every entity tends to be …

Analyzing The Performance Of The Sofia Infrared Telescope, Sarah M. Bass, Jeffrey Van Cleve, Zaheer Ali

STAR Program Research Presentations

The Stratospheric Observatory for Infrared Astronomy (SOFIA) is an airborne near-space observatory onboard a modified Boeing 747-SP aircraft, which flies at altitudes of 45,000 ft., above 99% of the Earth’s water vapor. SOFIA contains an effective 2.5 m infrared (IR) telescope that has a dichroic tertiary mirror, reflecting IR and visible wavelengths to the science instrument (SI) and focal plane imager (FPI), respectively. To date, seven different SIs have been designed to cover a wide range of wavelengths and spectral resolutions. Since the telescope operates in the infrared, different techniques, including chopping, nodding, and dithering, are used to reduce the …

Flitecam Data Process Validation, Jesse K. Tsai, Sachindev S. Shenoy, Brent Cedric Nicklas, Zaheer Ali, William T. Reach

STAR Program Research Presentations

FLITECAM Data Processing Validation

Many of the challenges that come from working with astronomical imaging arise from the reduction of raw data into scientifically meaningful data. First Light Infrared Test CAMera (FLITECAM) is an infrared camera operating in the 1.0–5.5 μm waveband on board SOFIA (Stratospheric Observatory For Infrared Astronomy). Due to the significant noise from the atmosphere and the camera itself, astronomers have developed many methods to reduce the effects of atmospheric and instrumental emission. The FLITECAM Data Reduction Program (FDRP) is a program, developed at SOFIA Science Center, subtracts darks, removes flats, and dithers images.

This project contains …

Image Processing Algorithms For Improving Planetary Exploration And Understanding, Ali Pouryazdanpanah

College of Engineering: Graduate Celebration Programs

• To design a fully automated tool-set that allows to detect and extract the sky region in planetary images.

• To develop the new method for rock segmentation in planetary stereo images.
• To develop the new method for shadow detection in planetary images

The Implementation Of The Shear Correlation Function And The Matter Power Spectrum In R, Allison A. Scheppelmann, Deborah J. Bard

STAR Program Research Presentations

Weak gravitational lensing is an important tool in understanding the large-scale structure of the universe. One component in understanding the effect of weak gravitational lensing is the shear correlation function and matter power spectrum. The calculation of these values is often complicated and time consuming. In order to decrease the cost of these calculations they were implemented in R using parallelization. This resulted in the calculations completing faster and the process to be easily changed in order to fit the need of each researcher using the algorithms created in R.

Block Preconditioning Of Stiff Implicit Models For Radiative Ionization In The Early Universe, Daniel R. Reynolds, Robert Harkness, Geoffrey So, Michael L. Norman

Mathematics Research

No abstract provided.