Computer-generated visual morphology catalog of ~3,000,000 SDSS galaxies

Abstract

We applied computer analysis to classify the broad morphological type of ~3,000,000 SDSS galaxies. The catalog provides for each galaxy the DR8 object ID, right ascension, declination, and the certainty of the automatic classification to spiral or elliptical. The certainty of the classification allows controlling the accuracy of a subset of galaxies by sacrificing some of the least certain classifications. The accuracy of the catalog was tested using galaxies that were classified by the manually annotated Galaxy Zoo catalog. The results show that the catalog contains ~900,000 spiral galaxies and ~600,000 elliptical galaxies with classification certainty that has a statistical agreement rate of ~98% with Galaxy Zoo debiased 'superclean' dataset. That also demonstrates the ability of computers to turn large datasets of galaxy images into structured catalogs of galaxy morphology. The catalog can be downloaded at http://vfacstaff.ltu.edu/lshamir/data/morph_catalog , and can be accessed through public tables on CAS: public.broadMorph.LargeGM, public.broadMorph.LargeWnnGM, and public.broadMorph.SpectraGM. The image analysis software that was used to create the catalog is also publicly available.

ApJS, accepted. CAS public tables added

References in corpus (4)

• Rotation-invariant convolutional neural networks for galaxy morphology prediction
• Galaxy Zoo 1 : Data Release of Morphological Classifications for nearly 900,000 galaxies
• Combining human and machine learning for morphological analysis of galaxy images
• Automatic detection of peculiar galaxy pairs in Sloan Digital Sky Survey

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