Poster Presentation

Topological data analysis of galaxy spatial distributions

Author(s): Shunya Uchida, Tsutomu T. Takeuchi (Nagoya Univ.), Suchetha Cooray (Stanford Univ.), Ryusei R. Kano (Nagoya Univ.), Yoh-ichi Mototake (Hitotsubashi Univ.), Daiki D. Iwasaki (Nagoya Univ.)

Presenter: Shunya Uchida (Nagoya University)

Galaxies do not evolve as isolated objects, but rather is dependent on their environment within the large-scale structures of the Universe. Therefore, it is important to understand the connection between the galaxies and their spatial distribution. Traditionally, conditional two-point correlation functions have been used to characterize the effect on galaxy properties by their spatial distribution. However, traditional statistics cannot identify individual structures. In this study, we applied Topological Data Analysis (TDA), a technique that can identify prominent structures from point cloud data, for studying the galaxy distributions and their property dependence. We applied TDA to a dataset binned by stellar mass and star formation rate and explored the distribution patterns. This poster presents the findings from the TDA approach and examines their validity.