Spectro-Morphological Classification of Galaxies by Shapelet Decomposition in the Sloan Digital Sky Survey

Details Spectro-Morphological Classification of Galaxies by Shapelet Decomposition in the Sloan Digital Sky Survey Spectro-Morphological Classification of Galaxies by Shapelet Decomposition in the Sloan Digital Sky Survey

Dec 2004

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004aas...205.6002k&link_type=abstract

American Astronomical Society Meeting 205, #60.02; Bulletin of the American Astronomical Society, Vol. 36, p.1442

Mathematics

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Scientific paper

We describe application of the `shapelet' linear decomposition of galaxy images to multi-wavelength morphological classification using the u,g,r,i, and z-band images of 1519 galaxies from the Sloan Digital Sky Survey. This combination of morphological information in a variety of bands is unique, and it allows automatic separation of different classes in ways which is impossible using single band images or simple spectro-photometric measurements such as color. After decomposing the galaxies we perform a principal component analysis to reduce the dimensionality of the spectro-morphological parameter space. We find that galaxies of different broad Hubble type separate cleanly in the principal component space. We apply a mixture of Gaussians model to the 2-dimensional space spanned by the first two principal components and use the results as a basis for classification. Using the mixture model, we separate galaxies into three classes and give a description of each class's physical and morphological properties. We find that the two dominant mixture model classes correspond to early and late type galaxies, respectively, both in their morphology and their physical parameters (e.g., color, velocity dispersions, etc.). The third class cannot be associated with any broad Hubble type, however it is the most probable class for irregular galaxies. We compare our method to a simple cut on u-r color and find the shapelet method to be superior in separating early and late type galaxies. Furthermore, we find evidence that the u-r=2.22 decision boundary may not be optimal for separation between early and late type galaxies, and suggest that the optimal cut may be u-r ˜ 2.4. Our framework provides an objective and quantitative alternative to traditional one color visual classification, and the powerful use of both spectral and morphological information gives our method an advantage over separation techniques based on simpler calculations.

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