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Articles 1 - 7 of 7
Full-Text Articles in Stars, Interstellar Medium and the Galaxy
Stellar Atmosphere Models For Select Veritas Stellar Intensity Interferometry Targets, Jackson Ladd Sackrider, Jason P. Aufdenberg, Katelyn Sonnen
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 …
Using Methanol Masers To Probe High Mass Star Forming Regions, Naomi S. Shechter, Anuj P. Sarma
Using Methanol Masers To Probe High Mass Star Forming Regions, Naomi S. Shechter, Anuj P. Sarma
DePaul Discoveries
Compared to low mass stars, the formation of high mass stars is not well understood. To understand better how high mass stars form, we can utilize masers, naturally amplified point sources of microwave radiation. One example is the methanol maser, which falls into two categories. Class I methanol masers form in the bipolar outflows from the protostar, and Class II masers form in the accretion disk. Their compact size and intensity make them an excellent source of information about the process of high mass star formation. We compiled a modest database of Class I and II methanol masers through a …
Automated Spectroscopic Detection And Mapping Using Alma And Machine Learningtechniques, Steven Cocke, Andrew Wilkins, Josephine Mcdaniel, John Santerre, Conor Nixon
Automated Spectroscopic Detection And Mapping Using Alma And Machine Learningtechniques, Steven Cocke, Andrew Wilkins, Josephine Mcdaniel, John Santerre, Conor Nixon
SMU Data Science Review
In this paper we present a methodology for automating theclassification of spectrally resolved observations of multiple emissionlines with the Atacama Large Millimeter/submillimeter Array (ALMA).Molecules in planetary atmospheres emit or absorb different wavelengthsof light thereby providing a unique signature for each species. ALMAdata were taken from interferometric observations of Titan made be-tween UT 2012 July 03 23:22:14 and 2012 July 04 01:06:18 as part ofALMA project 2011.0.00319.S. We first employed a greedy set cover algorithm to identify the most probable molecules that would reproducethe set of frequencies with respective flux greater than 3σaway from themean. We then selected a subset of …
Perfect Circles: A Study Of The Scattering Regions Of Wolf Rayet Binary Stars, Stella Yoos, Jennifer Hoffman, Andrew Fullard
Perfect Circles: A Study Of The Scattering Regions Of Wolf Rayet Binary Stars, Stella Yoos, Jennifer Hoffman, Andrew Fullard
DU Undergraduate Research Journal Archive
Although we have been able to develop an understanding of many aspects of stellar evolution and formation, a few key gaps remain. One is the fate of massive binary star systems composed of Wolf-Rayet (WR) and O-type stars. In these WR + O binaries, the stellar winds surrounding these stars collide, creating a complex interaction region in which light from the stars scatters and becomes polarized. To study these scattering regions, I employ a technique that allows me to map the polarization of the light emitted from these stars and track its variation over the binary orbit. I found that …
Machine Learning Pipeline For Exoplanet Classification, George Clayton Sturrock, Brychan Manry, Sohail Rafiqi
Machine Learning Pipeline For Exoplanet Classification, George Clayton Sturrock, Brychan Manry, Sohail Rafiqi
SMU Data Science Review
Planet identification has typically been a tasked performed exclusively by teams of astronomers and astrophysicists using methods and tools accessible only to those with years of academic education and training. NASA’s Exoplanet Exploration program has introduced modern satellites capable of capturing a vast array of data regarding celestial objects of interest to assist with researching these objects. The availability of satellite data has opened up the task of planet identification to individuals capable of writing and interpreting machine learning models. In this study, several classification models and datasets are utilized to assign a probability of an observation being an exoplanet. …
Have We Found Our Neighbors? The Search For Habitable Planets Outside Our Solar System, Madeline Galbraith
Have We Found Our Neighbors? The Search For Habitable Planets Outside Our Solar System, Madeline Galbraith
D.U.Quark
No abstract provided.
Defining The Circumstellar Habitable Zone, Blake Cervetti, Joanna Mccall
Defining The Circumstellar Habitable Zone, Blake Cervetti, Joanna Mccall
DePaul Discoveries
The study of habitable exoplanets is a rapidly expanding field in astronomy. Exoplanets are planets that orbit stars other than our own sun. One of the keys to knowing whether or not an exoplanet is habitable is by studying the circumstellar habitable zone, or CHZ. Over the past several years, the defined limits of the CHZ have become susceptible to change as new parameters and factors are found to affect a planets habitability. There are many factors that affect its habitability, including the composition of the star, the mass of the planet, the planets atmosphere, etc. Our focus is divided …