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P. Melchior

Publications and source records attributed to P. Melchior.

At least 37 records · Page 2Linked to original sources

Velocity Dispersions of Clusters in the Dark Energy Survey Y3 redMaPPer Catalog

We measure the velocity dispersions of clusters of galaxies selected by the redMaPPer algorithm in the first three years of data from the Dark Energy Survey (DES), allowing us to probe cluster selection and richness estimation, $λ$, in light of cluster dynamics. Our sample consists of 126 clusters with sufficient spectroscopy for individual velocity dispersion estimates. We examine the correlations between cluster velocity dispersion, richness, X-ray temperature and luminosity as well as central galaxy velocity offsets. The velocity dispersion-richness relation exhibits a bimodal distribution. The majority of clusters follow scaling relations between velocity dispersion, richness, and X-ray properties similar to those found for previous samples; however, there is a significant population of clusters with velocity dispersions which are high for their richness. These clusters account for roughly 22\% of the $λ< 70$ systems in our sample, but more than half (55\%) of $λ< 70$ clusters at $z>0.5$. A couple of these systems are hot and X-ray bright as expected for massive clusters with richnesses that appear to have been underestimated, but most appear to have high velocity dispersions for their X-ray properties likely due to line-of-sight structure. These results suggest that projection effects contribute significantly to redMaPPer selection, particularly at higher redshifts and lower richnesses. The redMaPPer determined richnesses for the velocity dispersion outliers are consistent with their X-ray properties, but several are X-ray undetected and deeper data is needed to understand their nature.

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Dark Energy Survey Year 3 Results: Calibration of Lens Sample Redshift Distributions using Clustering Redshifts with BOSS/eBOSS

We present clustering redshift measurements for Dark Energy Survey (DES) lens sample galaxies to be used in weak gravitational lensing and galaxy clustering studies. To perform this measurement, we cross-correlate with spectroscopic galaxies from the Baryon Acoustic Oscillation Survey (BOSS) and its extension, eBOSS. We validate our methodology in simulations, including a new technique to calibrate systematic errors due to the galaxy clustering bias, finding our method to be generally unbiased in calibrating the mean redshift. We apply our method to the data, and estimate the redshift distribution for eleven different photometrically-selected bins. We find general agreement between clustering redshift and photometric redshift estimates, with differences on the inferred mean redshift to be below $|Δz|=0.01$ in most of the bins. We also test a method to calibrate a width parameter for redshift distributions, which we found necessary to use for some of our samples. Our typical uncertainties on the mean redshift ranged from 0.003 to 0.008, while our uncertainties on the width ranged from 4 to 9\%. We discuss how these results calibrate the photometric redshift distributions used in companion DES Year 3 Results papers.

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The DECam Local Volume Exploration Survey Data Release 2

We present the second public data release (DR2) from the DECam Local Volume Exploration survey (DELVE). DELVE DR2 combines new DECam observations with archival DECam data from the Dark Energy Survey, the DECam Legacy Survey, and other DECam community programs. DELVE DR2 consists of ~160,000 exposures that cover >21,000 deg^2 of the high Galactic latitude (|b| > 10 deg) sky in four broadband optical/near-infrared filters (g, r, i, z). DELVE DR2 provides point-source and automatic aperture photometry for ~2.5 billion astronomical sources with a median 5σ point-source depth of g=24.3, r=23.9, i=23.5, and z=22.8 mag. A region of ~17,000 deg^2 has been imaged in all four filters, providing four-band photometric measurements for ~618 million astronomical sources. DELVE DR2 covers more than four times the area of the previous DELVE data release and contains roughly five times as many astronomical objects. DELVE DR2 is publicly available via the NOIRLab Astro Data Lab science platform.

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Dark Energy Survey Year 3 Results: A 2.7% measurement of Baryon Acoustic Oscillation distance scale at redshift 0.835

We present angular diameter measurements obtained by measuring the position of Baryon Acoustic Oscillations (BAO) in an optimised sample of galaxies from the first three years of Dark Energy Survey data (DES Y3). The sample consists of 7 million galaxies distributed over a footprint of 4100 deg$^2$ with $0.6 < z_{\rm photo} < 1.1$ and a typical redshift uncertainty of $0.03(1+z)$. The sample selection is the same as in the BAO measurement with the first year of DES data, but the analysis presented here uses three times the area, extends to higher redshift and makes a number of improvements, including a fully analytical BAO template, the use of covariances from both theory and simulations, and an extensive pre-unblinding protocol. We used two different statistics: angular correlation function and power spectrum, and validate our pipeline with an ensemble of over 1500 realistic simulations. Both statistics yield compatible results. We combine the likelihoods derived from angular correlations and spherical harmonics to constrain the ratio of comoving angular diameter distance $D_M$ at the effective redshift of our sample to the sound horizon scale at the drag epoch. We obtain $D_M(z_{\rm eff}=0.835)/r_{\rm d} = 18.92 \pm 0.51$, which is consistent with, but smaller than, the Planck prediction assuming flat \lcdm, at the level of $2.3 σ$. The analysis was performed blind and is robust to changes in a number of analysis choices. It represents the most precise BAO distance measurement from imaging data to date, and is competitive with the latest transverse ones from spectroscopic samples at $z>0.75$. When combined with DES 3x2pt + SNIa, they lead to improvements in $H_0$ and $Ω_m$ constraints by $\sim 20\%$

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Dark Energy Survey Year 3 Results: Point-Spread Function Modeling

We introduce a new software package for modeling the point-spread function (PSF) of astronomical images, called Piff (PSFs In the Full FOV), which we apply to the first three years (known as Y3) of the Dark Energy Survey (DES) data. We describe the relevant details about the algorithms used by Piff to model the PSF, including how the PSF model varies across the field of view (FOV). Diagnostic results show that the systematic errors from the PSF modeling are very small over the range of scales that are important for the DES Y3 weak lensing analysis. In particular, the systematic errors from the PSF modeling are significantly smaller than the corresponding results from the DES year one (Y1) analysis. We also briefly describe some planned improvements to Piff that we expect to further reduce the modeling errors in future analyses.

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Dark Energy Survey Year 3 Results: Deep Field Optical + Near-Infrared Images and Catalogue

We describe the Dark Energy Survey (DES) Deep Fields, a set of images and associated multi-wavelength catalogue ($ugrizJHKs$) built from Dark Energy Camera (DECam) and Visible and Infrared Survey Telescope for Astronomy (VISTA) data. The DES Deep Fields comprise 11 fields (10 DES supernova fields plus COSMOS), with a total area of $\sim30~$ square degrees in $ugriz$ bands and reaching a maximum $i$-band depth of 26.75 (AB, $10σ$, 2 arcsec). We present a catalogue for the DES 3-year cosmology analysis of those four fields with full 8-band coverage, totalling $5.88~$ sq. deg. after masking. Numbering $2.8~$million objects ($1.6~$million post masking), our catalogue is drawn from images coadded to consistent depths of $r=25.7, i=25, z=24.3$ mag. We use a new model-fitting code, built upon established methods, to deblend sources and ensure consistent colours across the $u$-band to $Ks$-band wavelength range. We further detail the tight control we maintain over the point-spread function modelling required for the model fitting, astrometry and consistency of photometry between the four fields. The catalogue allows us to perform a careful star-galaxy separation and produces excellent photometric redshift performance (${\rm NMAD} = 0.023$ at $i<23$). The Deep-Fields catalogue will be made available as part of the cosmology data products release, following the completion of the DES 3-year weak lensing and galaxy clustering cosmology work.

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Robust sampling for weak lensing and clustering analyses with the Dark Energy Survey

Recent cosmological analyses rely on the ability to accurately sample from high-dimensional posterior distributions. A variety of algorithms have been applied in the field, but justification of the particular sampler choice and settings is often lacking. Here we investigate three such samplers to motivate and validate the algorithm and settings used for the Dark Energy Survey (DES) analyses of the first 3 years (Y3) of data from combined measurements of weak lensing and galaxy clustering. We employ the full DES Year 1 likelihood alongside a much faster approximate likelihood, which enables us to assess the outcomes from each sampler choice and demonstrate the robustness of our full results. We find that the ellipsoidal nested sampling algorithm $\texttt{MultiNest}$ reports inconsistent estimates of the Bayesian evidence and somewhat narrower parameter credible intervals than the sliced nested sampling implemented in $\texttt{PolyChord}$. We compare the findings from $\texttt{MultiNest}$ and $\texttt{PolyChord}$ with parameter inference from the Metropolis-Hastings algorithm, finding good agreement. We determine that $\texttt{PolyChord}$ provides a good balance of speed and robustness, and recommend different settings for testing purposes and final chains for analyses with DES Y3 data. Our methodology can readily be reproduced to obtain suitable sampler settings for future surveys.

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The Evolution of AGN Activity in Brightest Cluster Galaxies

We present the results of an analysis of Wide-field Infrared Survey Explorer (WISE) observations on the full 2500 deg^2 South Pole Telescope (SPT)-SZ cluster sample. We describe a process for identifying active galactic nuclei (AGN) in brightest cluster galaxies (BCGs) based on WISE mid-infrared color and redshift. Applying this technique to the BCGs of the SPT-SZ sample, we calculate the AGN-hosting BCG fraction, which is defined as the fraction of BCGs hosting bright central AGNs over all possible BCGs. Assuming {\bf an evolving} single-burst stellar population model, we find statistically significant evidence (>99.9%) for a mid-IR excess at high redshift compared to low redshift, suggesting that the fraction of AGN-hosting BCGs increases with redshift over the range of 0 < z < 1.3. The best-fit redshift trend of the AGN-hosting BCG fraction has the form (1+z)^(4.1+/-1.0). These results are consistent with previous studies in galaxy clusters as well as field galaxies. One way to explain this result is that member galaxies at high redshift tend to have more cold gas. While BCGs in nearby galaxy clusters grow mostly by dry mergers with cluster members, leading to no increase in AGN activity, BCGs at high redshift could primarily merge with gas-rich satellites, providing fuel for feeding AGNs. If this observed increase in AGN activity is linked to gas-rich mergers, rather than ICM cooling, we would expect to see an increase in scatter in the P_cav vs L_cool relation at z > 1. Lastly, this work confirms that the runaway cooling phase, as predicted by the classical cooling flow model, in the Phoenix cluster is extremely rare and most BCGs have low (relative to Eddington) black hole accretion rates.

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Synthetic Galaxy Clusters and Observations Based on Dark Energy Survey Year 3 Data

We develop a novel data-driven method for generating synthetic optical observations of galaxy clusters. In cluster weak lensing, the interplay between analysis choices and systematic effects related to source galaxy selection, shape measurement and photometric redshift estimation can be best characterized in end-to-end tests going from mock observations to recovered cluster masses. To create such test scenarios, we measure and model the photometric properties of galaxy clusters and their sky environments from the Dark Energy Survey Year 3 (DES Y3) data in two bins of cluster richness $λ\in[30;\,45)$, $λ\in[45;\,60)$ and three bins in cluster redshift ($z\in[0.3;\,0.35)$, $z\in[0.45;\,0.5)$ and $z\in[0.6;\,0.65)$. Using deep-field imaging data we extrapolate galaxy populations beyond the limiting magnitude of DES Y3 and calculate the properties of cluster member galaxies via statistical background subtraction. We construct mock galaxy clusters as random draws from a distribution function, and render mock clusters and line-of-sight catalogs into synthetic images in the same format as actual survey observations. Synthetic galaxy clusters are generated from real observational data, and thus are independent from the assumptions inherent to cosmological simulations. The recipe can be straightforwardly modified to incorporate extra information, and correct for survey incompleteness. New realizations of synthetic clusters can be created at minimal cost, which will allow future analyses to generate the large number of images needed to characterize systematic uncertainties in cluster mass measurements.

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DES Y3 results: Blending shear and redshift biases in image simulations

As the statistical power of galaxy weak lensing reaches percent level precision, large, realistic and robust simulations are required to calibrate observational systematics, especially given the increased importance of object blending as survey depths increase. To capture the coupled effects of blending in both shear and photometric redshift calibration, we define the effective redshift distribution for lensing, $n_γ(z)$, and describe how to estimate it using image simulations. We use an extensive suite of tailored image simulations to characterize the performance of the shear estimation pipeline applied to the Dark Energy Survey (DES) Year 3 dataset. We describe the multi-band, multi-epoch simulations, and demonstrate their high level of realism through comparisons to the real DES data. We isolate the effects that generate shear calibration biases by running variations on our fiducial simulation, and find that blending-related effects are the dominant contribution to the mean multiplicative bias of approximately $-2\%$. By generating simulations with input shear signals that vary with redshift, we calibrate biases in our estimation of the effective redshfit distribution, and demonstrate the importance of this approach when blending is present. We provide corrected effective redshift distributions that incorporate statistical and systematic uncertainties, ready for use in DES Year 3 weak lensing analyses.

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Dark Energy Survey Year 3 Results: Measuring the Survey Transfer Function with Balrog

We describe an updated calibration and diagnostic framework, Balrog, used to directly sample the selection and photometric biases of the Dark Energy Survey's (DES) Year 3 (Y3) dataset. We systematically inject onto the single-epoch images of a random 20% subset of the DES footprint an ensemble of nearly 30 million realistic galaxy models derived from DES Deep Field observations. These augmented images are analyzed in parallel with the original data to automatically inherit measurement systematics that are often too difficult to capture with traditional generative models. The resulting object catalog is a Monte Carlo sampling of the DES transfer function and is used as a powerful diagnostic and calibration tool for a variety of DES Y3 science, particularly for the calibration of the photometric redshifts of distant "source" galaxies and magnification biases of nearer "lens" galaxies. The recovered Balrog injections are shown to closely match the photometric property distributions of the Y3 GOLD catalog, particularly in color, and capture the number density fluctuations from observing conditions of the real data within 1% for a typical galaxy sample. We find that Y3 colors are extremely well calibrated, typically within ~1-8 millimagnitudes, but for a small subset of objects we detect significant magnitude biases correlated with large overestimates of the injected object size due to proximity effects and blending. We discuss approaches to extend the current methodology to capture more aspects of the transfer function and reach full coverage of the survey footprint for future analyses.

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The DES Bright Arcs Survey: Candidate Strongly Lensed Galaxy Systems from the Dark Energy Survey 5,000 Sq. Deg. Footprint

We report the combined results of eight searches for strong gravitational lens systems in the full 5,000 sq. deg. of Dark Energy Survey (DES) observations. The observations accumulated by the end of the third observing season fully covered the DES footprint in 5 filters (grizY), with an $i-$band limiting magnitude (at $10σ$) of 23.44. In four searches, a list of potential candidates was identified using a color and magnitude selection from the object catalogs created from the first three observing seasons. Three other searches were conducted at the locations of previously identified galaxy clusters. Cutout images of potential candidates were then visually scanned using an object viewer. An additional set of candidates came from a data-quality check of a subset of the color-coadd "tiles" created from the full DES six-season data set. A short list of the most promising strong lens candidates was then numerically ranked according to whether or not we judged them to be bona fide strong gravitational lens systems. These searches discovered a diverse set of 247 strong lens candidate systems, of which 81 are identified for the first time. We provide the coordinates, magnitudes, and photometric properties of the lens and source objects, and an estimate of the Einstein radius for 81 new systems and 166 previously reported. This catalog will be of use for selecting interesting systems for detailed follow-up, studies of galaxy cluster and group mass profiles, as well as a training/validation set for automated strong lens searches.

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Lensing Without Borders. I. A Blind Comparison of the Amplitude of Galaxy-Galaxy Lensing Between Independent Imaging Surveys

Lensing Without Borders is a cross-survey collaboration created to assess the consistency of galaxy-galaxy lensing signals ($ΔΣ$) across different data-sets and to carry out end-to-end tests of systematic errors. We perform a blind comparison of the amplitude of $ΔΣ$ using lens samples from BOSS and six independent lensing surveys. We find good agreement between empirically estimated and reported systematic errors which agree to better than 2.3$σ$ in four lens bins and three radial ranges. For lenses with $z_{\rm L}>0.43$ and considering statistical errors, we detect a 3-4$σ$ correlation between lensing amplitude and survey depth. This correlation could arise from the increasing impact at higher redshift of unrecognised galaxy blends on shear calibration and imperfections in photometric redshift calibration. At $z_{\rm L}>0.54$ amplitudes may additionally correlate with foreground stellar density. The amplitude of these trends is within survey-defined systematic error budgets which are designed to include known shear and redshift calibration uncertainty. Using a fully empirical and conservative method, we do not find evidence for large unknown systematics. Systematic errors greater than 15% (25%) ruled out in three lens bins at 68% (95%) confidence at $z<0.54$. Differences with respect to predictions based on clustering are observed to be at the 20-30% level. Our results therefore suggest that lensing systematics alone are unlikely to fully explain the "lensing is low" effect at $z<0.54$. This analysis demonstrates the power of cross-survey comparisons and provides a promising path for identifying and reducing systematics in future lensing analyses.

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Dark Energy Survey Year 3 results: Cosmology with peaks using an emulator approach

We constrain the matter density $Ω_{\mathrm{m}}$ and the amplitude of density fluctuations $σ_8$ within the $Λ$CDM cosmological model with shear peak statistics and angular convergence power spectra using mass maps constructed from the first three years of data of the Dark Energy Survey (DES Y3). We use tomographic shear peak statistics, including cross-peaks: peak counts calculated on maps created by taking a harmonic space product of the convergence of two tomographic redshift bins. Our analysis follows a forward-modelling scheme to create a likelihood of these statistics using N-body simulations, using a Gaussian process emulator. We include the following lensing systematics: multiplicative shear bias, photometric redshift uncertainty, and galaxy intrinsic alignment. Stringent scale cuts are applied to avoid biases from unmodelled baryonic physics. We find that the additional non-Gaussian information leads to a tightening of the constraints on the structure growth parameter yielding $S_8~\equiv~σ_8\sqrt{Ω_{\mathrm{m}}/0.3}~=~0.797_{-0.013}^{+0.015}$ (68% confidence limits), with a precision of 1.8%, an improvement of ~38% compared to the angular power spectra only case. The results obtained with the angular power spectra and peak counts are found to be in agreement with each other and no significant difference in $S_8$ is recorded. We find a mild tension of $1.5 \thinspace σ$ between our study and the results from Planck 2018, with our analysis yielding a lower $S_8$. Furthermore, we observe that the combination of angular power spectra and tomographic peak counts breaks the degeneracy between galaxy intrinsic alignment $A_{\mathrm{IA}}$ and $S_8$, improving cosmological constraints. We run a suite of tests concluding that our results are robust and consistent with the results from other studies using DES Y3 data.

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The Dark Energy Survey Data Release 2

We present the second public data release of the Dark Energy Survey, DES DR2, based on optical/near-infrared imaging by the Dark Energy Camera mounted on the 4-m Blanco telescope at Cerro Tololo Inter-American Observatory in Chile. DES DR2 consists of reduced single-epoch and coadded images, a source catalog derived from coadded images, and associated data products assembled from 6 years of DES science operations. This release includes data from the DES wide-area survey covering ~5000 deg2 of the southern Galactic cap in five broad photometric bands, grizY. DES DR2 has a median delivered point-spread function full-width at half maximum of g= 1.11, r= 0.95, i= 0.88, z= 0.83, and Y= 0.90 arcsec photometric uniformity with a standard deviation of < 3 mmag with respect to Gaia DR2 G-band, a photometric accuracy of ~10 mmag, and a median internal astrometric precision of ~27 mas. The median coadded catalog depth for a 1.95 arcsec diameter aperture at S/N= 10 is g= 24.7, r= 24.4, i= 23.8, z= 23.1 and Y= 21.7 mag. DES DR2 includes ~691 million distinct astronomical objects detected in 10,169 coadded image tiles of size 0.534 deg2 produced from 76,217 single-epoch images. After a basic quality selection, benchmark galaxy and stellar samples contain 543 million and 145 million objects, respectively. These data are accessible through several interfaces, including interactive image visualization tools, web-based query clients, image cutout servers and Jupyter notebooks. DES DR2 constitutes the largest photometric data set to date at the achieved depth and photometric precision.

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Cross-correlation of DES Y3 lensing and ACT/${\it Planck}$ thermal Sunyaev Zel'dovich Effect I: Measurements, systematics tests, and feedback model constraints

We present a tomographic measurement of the cross-correlation between thermal Sunyaev-Zeldovich (tSZ) maps from ${\it Planck}$ and the Atacama Cosmology Telescope (ACT) and weak galaxy lensing shears measured during the first three years of observations of the Dark Energy Survey (DES Y3). This correlation is sensitive to the thermal energy in baryons over a wide redshift range, and is therefore a powerful probe of astrophysical feedback. We detect the correlation at a statistical significance of $21σ$, the highest significance to date. We examine the tSZ maps for potential contaminants, including cosmic infrared background (CIB) and radio sources, finding that CIB has a substantial impact on our measurements and must be taken into account in our analysis. We use the cross-correlation measurements to test different feedback models. In particular, we model the tSZ using several different pressure profile models calibrated against hydrodynamical simulations. Our analysis marginalises over redshift uncertainties, shear calibration biases, and intrinsic alignment effects. We also marginalise over $Ω_{\rm m}$ and $σ_8$ using ${\it Planck}$ or DES priors. We find that the data prefers the model with a low amplitude of the pressure profile at small scales, compatible with a scenario with strong AGN feedback and ejection of gas from the inner part of the halos. When using a more flexible model for the shear profile, constraints are weaker, and the data cannot discriminate between different baryonic prescriptions.

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Density split statistics: joint model of counts and lensing in cells

We present density split statistics, a framework that studies lensing and counts-in-cells as a function of foreground galaxy density, thereby providing a large-scale measurement of both 2-point and 3-point statistics. Our method extends our earlier work on trough lensing and is summarized as follows: given a foreground (low redshift) population of galaxies, we divide the sky into subareas of equal size but distinct galaxy density. We then measure lensing around uniformly spaced points separately in each of these subareas, as well as counts-in-cells statistics (CiC). The lensing signals trace the matter density contrast around regions of fixed galaxy density. Through the CiC measurements this can be related to the density profile around regions of fixed matter density. Together, these measurements constitute a powerful probe of cosmology, the skewness of the density field and the connection of galaxies and matter. In this paper we show how to model both the density split lensing signal and CiC from basic ingredients: a non-linear power spectrum, clustering hierarchy coefficients from perturbation theory and a parametric model for galaxy bias and shot-noise. Using N-body simulations, we demonstrate that this model is sufficiently accurate for a cosmological analysis on year 1 data from the Dark Energy Survey.

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The Observed Evolution of the Stellar Mass - Halo Mass Relation for Brightest Central Galaxies

We quantify evolution in the cluster scale stellar mass - halo mass (SMHM) relation's parameters using 2323 clusters and brightest central galaxies (BCGs) over the redshift range $0.03 \le z \le 0.60$. The precision on inferred SMHM parameters is improved by including the magnitude gap ($\rm m_{gap}$) between the BCG and fourth brightest cluster member (M14) as a third parameter in the SMHM relation. At fixed halo mass, accounting for $\rm m_{gap}$, through a stretch parameter, reduces the SMHM relation's intrinsic scatter. To explore this redshift range, we use clusters, BCGs, and cluster members identified using the Sloan Digital Sky Survey C4 and redMaPPer cluster catalogs and the Dark Energy Survey redMaPPer catalog. Through this joint analysis, we detect no systematic differences in BCG stellar mass, $\rm m_{gap}$, and cluster mass (inferred from richness) between the datsets. We utilize the Pareto function to quantify each parameter's evolution. We confirm prior findings of negative evolution in the SMHM relation's slope (3.5$σ$) and detect negative evolution in the stretch parameter (4.0$σ$) and positive evolution in the offset parameter (5.8$σ$). This observed evolution, combined with the absence of BCG growth, when stellar mass is measured within 50kpc, suggests that this evolution results from changes in the cluster's $\rm m_{gap}$. For this to occur, late-term growth must be in the intra-cluster light surrounding the BCG. We also compare the observed results to Illustris TNG 300-1 cosmological hydrodynamic simulations and find modest qualitative agreement. However, the simulations lack the evolutionary features detected in the real data.

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