摘要
We investigate the environmental dependence of galaxy mergers using high-resolution imaging data from the Hyper Suprime-Cam (HSC) Subaru Strategic Program. We focus on galaxy groups and clusters at z < 0 . 2 identified by the Sloan Digital Sky Survey as a laboratory of galaxy environment. We develop a new non-parametric classification scheme that combines the Gini-M-20 statistics with the shape asymmetry parameter, enabling robust identification of mergers with both central concentration and outer morphological disturbances. Applying this method to a sample of 33320 galaxies at 0 . 075 <= z < 0 . 2 taken by the HSC, we identify 12666 mergers, corresponding to a merger fraction of 38% . Our results are consistent with visual classifications from the GALAXY CRUISE project, validating the effectiveness of our method. We find that the merger fraction increases with redshift for all subsamples ( field galaxies, galaxy pairs, and cluster members) , and also shows a strong radial gradient within clusters, increasing toward the center. These trends suggest that merger activity is enhanced both at earlier cosmic times and in denser environments, particularly in galaxy groups. We also find tentative evidence that mergers may contribute to AGN triggering in cluster cores. Our study highlights the utility of combining non-parametric morphological diagnostics for large-scale merger identification and provides new insights into the role of environment in galaxy evolution.