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A dataset of 126,501 spiral galaxies taken from Sloan Digital Sky Survey was used to analyze the large-scale galaxy handedness in different regions of the local universe. The analysis was automated by using a transformation of the galaxy images to their radial intensity plots, which allows automatic analysis of the galaxy spin and can therefore be used to analyze a large galaxy dataset. The results...
We propose an image analysis unsupervised learning algorithm that can detect peculiar galaxies in datasets of galaxy images. The algorithm first computes a large set of calculated characteristics reflecting different aspects of the visual content, and then weighs them based on the σ of the values computed from the galaxy images. The weighted Euclidean distance of each galaxy image from the median...
Summary form only given. Large-scale computation has achieved a pivotal role in many areas of astrophysics and cosmology. Not only does increasing computational power allow us to better model the huge range of spatial and temporal scales in the universe, but simulations provide in many cases the only laboratory in which we may actively experiment on cosmic phenomena. The talk will highlight some of...
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