Stars, Interstellar Medium and the Galaxy Commons^™

Pulsey: Stellar Pulsation Models In Python, Andrew Ayala

Dissertations, Theses, and Capstone Projects

The era of the Kepler/K2 and TESS space-telescope missions has inundated the astrophysics community with photometric data for millions of stars with continuous observation and very high cadence. This data confirms that nearly every observed stellar source exhibits an oscillating luminosity, with stellar pulsation being the driving mechanism behind a large fraction of the cause. The result has been an explosion in the field of asteroseismology, where the recorded luminosity variations, or "light curves", of pulsating stars to probe their interior structures. By modeling observed light curves, we can constrain values of the physical stellar parameters producing them. The brightness …

The Computational Search For Unidentified Central Configurations Of The Newtonian N-Body Problem, Hannah G. Havel

CURE Proceedings

The N-body problem is a field of study in mathematics and physics that involves predicting the motion of particles moving under their mutual gravitational attraction. It is vital in celestial mechanics, such as planning collision-free satellite orbit trajectories. When beginning to understand the N-body problem, we can start by looking at equal masses of these particles or celestial bodies. As particles move, their position and velocity change, both energy and angular momentum are conserved. Sets of constant energy and angular momentum, known as integral manifolds, are higher-dimensional figures that represent constraints of movement to a system. Integral manifolds are described …

Stellar Atmosphere Models For Select Veritas Stellar Intensity Interferometry Targets, Jackson Ladd Sackrider, Jason P. Aufdenberg, Katelyn Sonnen

Beyond: Undergraduate Research Journal

Since 2020 the Very Energetic Radiation Imaging Telescope Array System (VERITAS) has observed 48 stellar targets using the technique of Stellar Intensity Interferometry (SII). Angular diameter measurements by VERITAS SII (VSII) in a waveband near 400 nm complement existing angular diameter measurements in the near-infrared. VSII observations will test fundamental predictions of stellar atmosphere models and should be more sensitive to limb darkening and gravity darkening effects than measurements in the near-IR, however, the magnitude of this difference has not been systematically explored in the literature. In order to investigate the synthetic interferometric (as well as spectroscopic) appearance of stars …

Bifurcation Levels Of The Integral Manifolds Of The Newtonian N-Body Problem, Hannah G. Havel

CURE Proceedings

The N-body problem, first proposed by Isaac Newton, is a field of study in mathematics and physics that involves predicting the motion of particles moving under their mutual gravitational attraction. It has significance to many areas of science, including physics and computer science, and is crucial in understanding how the universe works. In fact, it was a primary motivation for Newton's development of calculus. An important application of the N-body problem is within celestial mechanics and involves how planets and other celestial bodies move with mutual gravitational attraction. It is important in developing how satellites behave in space using complicated …

Automated Morgan Keenan Classification Of Observed Stellar Spectra Collected By The Sloan Digital Sky Survey Using A Single Classifier, Michael J. Brice, Răzvan Andonie

All Faculty Scholarship for the College of the Sciences

The classification of stellar spectra is a fundamental task in stellar astrophysics. Stellar spectra from the Sloan Digital Sky Survey are applied to standard classification methods, k-nearest neighbors and random forest, to automatically classify the spectra. Stellar spectra are high dimensional data and the dimensionality is reduced using astronomical knowledge because classifiers work in low dimensional space. These methods are utilized to classify the stellar spectra into a complete Morgan Keenan classification (spectral and luminosity) using a single classifier. The motion of stars (radial velocity) causes machine-learning complications through the feature matrix when classifying stellar spectra. Due to the nature …

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 …

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. …

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 …

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 …