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Presentation Time: 1:30-1:50
Home University: UNC-Chapel Hill
Research Mentor: Dr. Sheila Kannappan, Physics and Astronomy
Program: Sheila Kannappan - Physics
Research Title: Galaxy Nearest Neighbor Search Methods

Despite their size, galaxies are not the largest structures in the universe. Unless they are isolated, gravity allows galaxies to congregate at different scales in groups, clusters, and superclusters, which make up the large scale structure of the universe. A galaxy’s environment is dependent on the other galaxies around it, so one way to quantify galaxy environments is by identifying nearest neighbors. Two algorithms that accomplish this are called the KD-Tree Search and Cylinder Search methods. KD-Tree builds a binary tree out of a list of coordinates, where the points in the tree are the coordinates of galaxies. It compares the distances between a particular search point and other points in the tree to find the minimum distance. On the other hand, Cylinder Search limits possible nearest neighbors to particular redshift differences and angular separations before computing the distances between galaxies and finding N nearest neighbors. In my presentation I will explain each search method as they pertain to finding the nearest neighbors of galaxies, as well as provide a comparison between the two.