A Probabilistic Approach to Finding Geometric Objects in Spatial Datasets of the Milky Way
Data from the Sloan Digital Sky Survey has given evidence of structures within the Milky Way halo from other nearby galaxies. Both the halo and these structures are approximated by densities based on geometric objects. A model of the data is formed by a mixture of geometric densities. By using an EM-style algorithm, we optimize the parameters of our model in order to separate out these structures from the data and thus obtain an accurate dataset of the Milky Way.
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