A 'deep learning' algorithm trained on images from cosmological simulations is surprisingly successful at classifying real galaxies in Hubble images. Top row: High-resolution images from a computer simulation of a young galaxy going through three phases of evolution (before, during, and after the "blue nugget" phase). Middle row: The same images from the computer simulation of a young galaxy in three phases of evolution as it would appear if observed by the Hubble Space Telescope. Bottom row: Hubble Space Telescope images of distant young galaxies classified by a deep learning algorithm trained to recognize the three phases of galaxy evolution. The width of each image is approximately 100,000 light years.
Image credits for top two rows: Greg Snyder, Space Telescope Science Institute, and Marc Huertas-Company, Paris Observatory. For bottom row: The HST images are from the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS).