Superclusters, encompassing environments across a wide range of overdensities, can be regarded as unique laboratories for studying galaxy evolution. Although numerous supercluster catalogs have been published, none of them goes beyond redshift z=0.7. In this work, we adopt a physically motivated supercluster definition, requiring that superclusters should eventually collapse even in the presence of dark energy. Applying a friends-of-friends (FoF) algorithm to the CAMIRA cluster sample constructed using the Subaru Hyper Suprime-Cam survey data, we have conducted the first systematic search for superclusters at z=0.5−1.0 and identified 673 supercluster candidates over an area of 1027 deg2. The FoF algorithm is calibrated by evolving N-body simulations to the far future to ensure high purity. We found that these high-z superclusters are mainly composed of 2−4 clusters, suggesting the limit of gravitationally bound structures in the younger Universe. In addition, we studied the properties of the clusters and brightest cluster galaxies (BCGs) residing in different large-scale environments. We found that clusters associated with superclusters are typically richer, but no apparent dependence of the BCG properties on large-scale structures is found. We also compared the abundance of observed superclusters with mock superclusters extracted from halo light cones, finding that photometric redshift uncertainty is a limiting factor in the performance of superclusters detection.
@article{arxiv.2401.10322,
title = {A Systematic Search of Distant Superclusters with the Subaru Hyper Suprime-Cam Survey},
author = {Tsung-Chi Chen and Yen-Ting Lin and Hsi-Yu Schive and Masamune Oguri and Kai-Feng Chen and Nobuhiro Okabe and Sadman Ali and Connor Bottrell and Roohi Dalal and Yusei Koyama and Rogério Monteiro-Oliveira and Rhythm Shimakawa and Tomotsugu Goto and Bau-Ching Hsieh and Tadayuki Kodama and Atsushi J. Nishizawa},
journal= {arXiv preprint arXiv:2401.10322},
year = {2024}
}