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We present the direct detection of the splashback feature using the sample of massive galaxy clusters from the Local Cluster Substructure Survey (LoCuSS). This feature is clearly detected (above $5sigma$) in the stacked luminosity density profile obtained using the K-band magnitudes of spectroscopically confirmed cluster members. We obtained the best-fit model by means of Bayesian inference, which ranked models including the splashback feature as more descriptive of the data with respect to models that do not allow for this transition. In addition, we have assessed the impact of the cluster dynamical state on the occurrence of the splashback feature. We exploited the extensive multi-wavelength LoCuSS dataset to test a wide range of proxies for the cluster formation history, finding the most significant dependence of the splashback feature location and scale according to the presence or absence of X-ray emitting galaxy groups in the cluster infall regions. In particular, we report for the first time that clusters that do not show massive infalling groups present the splashback feature at a smaller clustercentric radius $ r_{rm{sp}}/r_{rm{200,m}} = 1.158 pm 0.071$ than clusters that are actively accreting groups $r_{rm{sp}}/r_{rm{200,m}} = 1.291 pm 0.062$. The difference between these two sub-samples is significant at $4.2sigma$, suggesting a correlation between the properties of the cluster potential and its accretion rate and merger history. Similarly, clusters that are classified as old and dynamically inactive present stronger signatures of the splashback feature, with respect to younger, more active clusters. We are directly observing how fundamental dynamical properties of clusters reverberate across vastly different physical scales.
The lensing signal around galaxy clusters can, in principle, be used to test detailed predictions for their average mass profile from numerical simulations. However, the intrinsic shape of the profiles can be smeared out when a sample that spans a wi
We critically examine the methodology behind the claimed observational detection of halo assembly bias using optically selected galaxy clusters by Miyatake et al. (2016) and More et al. (2016). We mimic the optical cluster detection algorithm and app
We study the luminosity gap, dm12, between the first and second ranked galaxies in a sample of 59 massive galaxy clusters, using data from the Hale Telescope, HST, Chandra, and Spitzer. We find that the dm12 distribution, p(dm12), is a declining func
We present a pilot study on the origin and assembly history of the ICL for four galaxy clusters at 0.44<z<0.57 observed with the Hubble Space Telescope from the Cluster Lensing and Supernova Survey with Hubble (CLASH) sample. Using this sample of clu