We applied computational tools for automatic detection of peculiar galaxy pairs. We first detected in Sloan Digital Sky Survey DR7 ~400000 galaxy images with i magnitude <18 that had more than one point spread function, and then applied a machine learning algorithm that detected ~26000 galaxy images that had morphology similar to the morphology of galaxy mergers. That data set 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.

Cone search capability for table J/MNRAS/443/3528/table1 (Tabular data on the example galaxies)

Cone search capability for table J/MNRAS/443/3528/list (List used for analysis)