Automatic detection and quantitative assessment of peculiar galaxy pairs in Sloan Digital Sky Survey

We applied computational tools for automatic detection of peculiar galaxy pairs. We first detected in SDSS DR7 ∼400,000 galaxy images with i magnitude <18 that had more than one point spread function, and then applied a machine learning algorithm that detected ∼26,000 galaxy images that had morphology similar to the morphology of galaxy mergers. That dataset was mined using a novelty detection algorithm, producing a short list of 500 most peculiar galaxies as quantitatively determined by the algorithm. Manual examination of these galaxies showed that while most of the galaxy pairs in the list were not necessarily peculiar, numerous unusual galaxy pairs were detected. In this paper we describe the protocol and computational tools used for the detection of peculiar mergers, and provide examples of peculiar galaxy pairs that were detected.