Mapping The Extent Of The Magellanic Clouds Using Gaia Data

Kelly, David Joel (2018) Mapping The Extent Of The Magellanic Clouds Using Gaia Data. Masters thesis, Northern Arizona University.

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Abstract

The Gaia Data Release 1 (GDR1) set yields a promising amount of information about the Milky Way and the Large and Small Magellanic Clouds (LMC and SMC), mapping over one billion star positions. We can learn more about the distribution of stars in the Magellanic Clouds and determine the Cloud’s extent. We assumed that the Milky Way is axisymmetric about its center in Galactic latitude and longitude. Iso- lating a region of the Gaia star counts around the Magellanic Clouds, we can reduce the foreground contribution from the Milky Way by finding the corresponding region reflected around the Milky Way’s center to create a proper foreground correction or “filter”. This filter is made using a Voronoi tessellation, by which we can determine the local density at each point throughout each region. One can then statistically subtract the local density of each point in the reflected region of the Milky Way (representing the foreground stars) from that of the LMC and SMC. The result is the excess from the Magellanic Clouds. When comparing how the density of the LMC and SMC change with distance, we define the “edge” to be where those densities met that of the Milky Way. We found that the edge is at about 10.2 kpc radially from the LMC center, and about 8.0 kpc radially from the SMC center.

Item Type:	Thesis (Masters)
Publisher’s Statement:	© Copyright is held by the author. Digital access to this material is made possible by the Cline Library, Northern Arizona University. Further transmission, reproduction or presentation of protected items is prohibited except with permission of the author.
Keywords:	Gaia; Magellanic Clouds
Subjects:	Q Science > QB Astronomy
NAU Depositing Author Academic Status:	Student
Department/Unit:	College of the Environment, Forestry, and Natural Sciences > Physics and Astronomy
Date Deposited:	26 Apr 2021 19:15
URI:	http://openknowledge.nau.edu/id/eprint/5283

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