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We estimate the Intracluster Light (ICL) component within a sample of 18 clusters detected in XMM Cluster Survey (XCS) data using deep ($\sim$ 26.8 mag) Hyper Suprime Cam Subaru Strategic Program DR1 (HSC-SSP DR1) $i$-band data. We apply a rest-frame ${\mu}_{B} = 25 \ \mathrm{mag/arcsec^{2}}$ isophotal threshold to our clusters, below which we define light as the ICL within an aperture of $R_{X,500}$ (X-ray estimate of $R_{500}$) centered on the Brightest Cluster Galaxy (BCG). After applying careful masking and corrections for flux losses from background subtraction, we recover $\sim$20% of the ICL flux, approximately four times our estimate of the typical background at the same isophotal level ($\sim$ 5%). We find that the ICL makes up about $\sim$ 24% of the total cluster stellar mass on average ($\sim$ 41% including the flux contained in the BCG within 50 kpc); this value is well-matched with other observational studies and semi-analytic/numerical simulations, but is significantly smaller than results from recent hydrodynamical simulations (even when measured in an observationally consistent way). We find no evidence for any links between the amount of ICL flux with cluster mass, but find a growth rate of $2-4$ for the ICL between $0.1 < z < 0.5$. We conclude that the ICL is the dominant evolutionary component of stellar mass in clusters from $z \sim 1$. Our work highlights the need for a consistent approach when measuring ICL alongside the need for deeper imaging, in order to unambiguously measure the ICL across as broad a redshift range as possible (e.g. 10-year stacked imaging from the Vera C. Rubin Observatory)., Comment: Accepted by MNRAS (05/01/2021), 20 pages, 17 figures

We perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset. Our analysis uses the same shear and source photometric redshifts estimates as were used in the DES combined probes analysis. Our analysis results in surprisingly low values for $S_8 =\sigma_8(\Omega_{\rm m}/0.3)^{0.5}= 0.65\pm 0.04$, driven by a low matter density parameter, $\Omega_{\rm m}=0.179^{+0.031}_{-0.038}$, with $\sigma_8-\Omega_{\rm m}$ posteriors in $2.4\sigma$ tension with the DES Y1 3x2pt results, and in $5.6\sigma$ with the Planck CMB analysis. These results include the impact of post-unblinding changes to the analysis, which did not improve the level of consistency with other data sets compared to the results obtained at the unblinding. The fact that multiple cosmological probes (supernovae, baryon acoustic oscillations, cosmic shear, galaxy clustering and CMB anisotropies), and other galaxy cluster analyses all favor significantly higher matter densities suggests the presence of systematic errors in the data or an incomplete modeling of the relevant physics. Cross checks with X-ray and microwave data, as well as independent constraints on the observable--mass relation from SZ selected clusters, suggest that the discrepancy resides in our modeling of the weak lensing signal rather than the cluster abundance. Repeating our analysis using a higher richness threshold ($\lambda \ge 30$) significantly reduces the tension with other probes, and points to one or more richness-dependent effects not captured by our model., Comment: 35 pages, 20 figures, submitted to Physical Review D

In order to place constraints on cosmology through optical surveys of galaxy clusters, one must first understand the properties of those clusters. To this end, we introduce the Mass Analysis Tool for Chandra (MATCha), a pipeline which uses a parallellized algorithm to analyze archival Chandra data. MATCha simultaneously calculates X-ray temperatures and luminosities and performs centering measurements for hundreds of potential galaxy clusters using archival X-ray exposures. We run MATCha on the redMaPPer SDSS DR8 cluster catalog and use MATCha's output X-ray temperatures and luminosities to analyze the galaxy cluster temperature-richness, luminosity-richness, luminosity-temperature, and temperature-luminosity scaling relations. We detect 447 clusters and determine 246 r2500 temperatures across all redshifts. Within 0.1 < z < 0.35 we find that r2500 Tx scales with optical richness as ln(kB Tx / 1.0 keV) = (0.52 \pm 0.05) ln({\lambda}/70) + (1.85 \pm 0.03) with intrinsic scatter of 0.27 \pm 0.02 (1 {\sigma}). We investigate the distribution of offsets between the X-ray center and redMaPPer center within 0.1 < z < 0.35, finding that 68.3 \pm 6.5% of clusters are well-centered. However, we find a broad tail of large offsets in this distribution, and we explore some of the causes of redMaPPer miscentering., Comment: 36 pages, 17 figures, 7 tables. Accepted to ApJS