Gravitational lensing detection of an extremely dense environment around a galaxy cluster

TL;DR

This paper reports the first detection of correlated dark matter around a very massive galaxy cluster using gravitational lensing, revealing an extremely dense environment extending up to 30 Mpc, which enhances our understanding of structure formation.

Contribution

It presents the first direct gravitational lensing detection of environment bias around a single massive galaxy cluster, highlighting the dense surroundings predicted by structure formation models.

Findings

Detected strong lensing signal up to 30 Mpc around a galaxy cluster.

Observed excess dark matter density in the cluster environment.

Demonstrated the effectiveness of lensing surveys in studying single halo environments.

Abstract

Galaxy clusters form at the highest density nodes of the cosmic web. The clustering of massive halos is enhanced relative to the general mass distribution and matter beyond the virial region is strongly correlated to the halo mass (halo bias). Clustering can be further enhanced depending on halo properties other than mass (secondary bias). The questions of how much and why the regions surrounding rich clusters are over-dense are still unanswered. Here, we report the analysis of the environment bias in a sample of very massive clusters, selected through the Sunyaev-Zel'dovich effect by the Planck mission. We present the first detection of the correlated dark matter associated to a single cluster, PSZ2 G099.86+58.45. The system is extremely rare in the current paradigm of structure formation. The gravitational lensing signal was traced up to 30 megaparsecs with high signal-to-noise ratio ~3.4. The measured shear is very large and points at environment matter density in notable excess of the cosmological mean. The boosting of the correlated dark matter density around high mass halos can be very effective. Together with ensemble studies of the large scale structure, lensing surveys can picture the surroundings of single haloes.