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August E. Evrard

Publications and source records attributed to August E. Evrard.

At least 19 recordsLinked to original sources

Mass Proxy Quality of Massive Halo Properties in the IllustrisTNG and FLAMINGO Simulations: I. Hot Gas

We examine scale and redshift dependence of mass-property relations (MPRs) for five hot gas properties of two large group- and cluster-scale halo samples realized by the IllustrisTNG, TNG-Cluster and FLAMINGO cosmological hydrodynamical simulations. For intrinsic properties of i) hot gas mass ($M_{\rm gas}$), ii) spectroscopic-like temperature ($T_{\rm sl}$), iii) soft-band X-ray luminosity ($L_{\rm X}$), and iv) X-ray ($Y_{\rm X}$) and v) Sunyaev-Zel'dovich ($Y_{\rm SZ}$) thermal energies, we use MPR parameters to infer mass proxy quality (MPQ) -- the implied scatter in total halo mass conditioned on a property -- for halos with $M_{\rm 500c} \geq 10^{13}{\, {\rm M}_\odot}$ at redshifts, $z \in \{0, 0.5, 1, 2\}$. We find: (1) in general, scaling relation slopes and covariance display moderate to strong dependence on halo mass, with redshift dependence secondary; (2) for halos with $M_{\rm 500c} > 10^{14}{\, {\rm M}_\odot}$, scalings of $M_{\rm gas}$ and $Y_{\rm SZ}$ simplify toward self-similar slope and constant intrinsic scatter (5 and 10 per cent, respectively) nearly independent of scale, making both measures ideal for cluster finding and characterization to $z=2$; (3) halo mass-conditioned likelihoods of hot gas mass and thermal energy at fixed halo mass closely follow a log-normal form; (4) despite normalization differences ranging up to $0.4$ dex between the two simulations, higher order scaling features such as slopes and property covariance show much better agreement. Slopes show appreciable redshift dependence at the group scale, while redshift dependence of the scatter is exhibited by low-mass FLAMINGO halos only; (5) property correlations are largely consistent between the simulations, with values that mainly agree with existing empirical measurements. We close with a literature survey placing our MPR slopes and intrinsic scatter estimates into community context.

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Association between optically identified galaxy clusters and the underlying dark matter halos

Clusters of galaxies trace massive dark matter halos in the Universe, but they can include multiple halos projected along lines of sight. As a case study, we quantify the properties of halos contributing to clusters identified by the redMaPPer algorithm using the Cardinal simulation, which mimics the Dark Energy Survey data. For each cluster, we identify the halos hosting its member galaxies, and we define the main halo as the one contributing the most to the cluster's richness ($λ$, the estimated number of member galaxies). At $z=0.3$, for clusters with $λ> 60$, the main halo typically contributes to $92\%$ of the richness, and this fraction drops to $67\%$ for $λ\approx 20$. Defining "clean" clusters as those with $\geq50\%$ of the richness contributed by the main halo, we find that $100\%$ of the $λ> 60$ clusters are clean, while $73\%$ of the $λ\approx 20$ clusters are clean. Three halos can usually account for more than $80\%$ of the richness of a cluster. The main halos associated with redMaPPer clusters have a completeness ranging from $98\%$ at virial mass $10^{14.6}~h^{-1}M_{\odot}$ to $64\%$ at $10^{14}~h^{-1}M_{\odot}$. In addition, we compare the inferred cluster centers with true halo centers, finding that $30\%$ of the clusters are miscentered with a mean offset $40\%$ of the cluster radii, in agreement with recent X-ray studies. These systematics worsen as redshift increases, but we expect that upcoming surveys extending to longer wavelengths will improve the cluster finding at high redshifts. Our results affirm the robustness of the redMaPPer algorithm and provide a framework for benchmarking other cluster-finding strategies.

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Cosmic Dragons: A Two-Component Mixture Model of COSMOS Galaxies

Using the photometric population prediction method {\bf Red Dragon}, we characterize the Red Sequence (RS) and Blue Cloud (BC) of DES galaxies in the COSMOS field. Red Dragon (RD) uses a redshift-evolving, error-corrected Gaussian mixture model to detail the distribution of photometric colors, smoothly parameterizing the two populations with relative weights, mean colors, intrinsic scatters, and inter-color correlations. This resulting fit of RS and BC yields RS membership probabilities $P_{\rm RS}$ for each galaxy. Even when training on only DES main bands $griz$, RD selects the quiescent population (defined here as galaxies with $\lg {\rm sSFR \cdot yr} < -11$) with $\gtrsim 90\%$ balanced accuracy out to $z=2$; augmenting with extended photometry from VIRCAM improves this accuracy to $\sim 95\%$ out to $z=3$. We measure redshift evolution of sSFR and galactic age in several stellar mass bins, finding that the BC is consistently more star-forming (by $\gtrsim 1~{\rm dex}$) and typically younger (by $\gtrsim 1~{\rm Gyr}$) than the RS (up to $z \sim 1.4$). This characterization of both RS and BC as functions of redshift and stellar mass improves our understanding of both populations and opens the door to more precise galaxy population characterization in future deep optical and IR systems.

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Cluster Cosmology Redux: A Compact Model of the Halo Mass Function

Massive halos hosting groups and clusters of galaxies imprint coherent, arcminute-scale features across the spectrophotometric sky, especially optical-IR clusters of galaxies, distortions in the sub-mm CMB, and extended sources of X-ray emission. Statistical modeling of such features often rely upon the evolving space-time density of dark matter halos -- the halo mass function (HMF) -- as a common theoretical ground for cosmological, astrophysical and fundamental physics studies. We propose a compact (eight parameter) representation of the HMF with readily interpretable parameters that stem from polynomial expansions, first in terms of log-mass, then expanding those coefficients similarly in redshift. We demonstrate good ($\sim \! 5\%$) agreement of this form, referred to as the dual-quadratic (DQ-HMF), with Mira-Titan N-body emulator estimates for halo masses above $10^{13.7} h^{-1} {\rm M}_\odot$ over the redshift range $0.1 < z < 1.5$, present best-fit parameters for a Planck 2018 cosmology, and present parameter variation in the $σ_8 - Ω_{\rm m}$ plane. Convolving with a minimal mass-observable relation (MOR) yields closed-form expressions for counts, mean mass, and mass variance of cluster samples characterized by some observable property. Performing information-matrix forecasts of potential parameter constraints from existing and future surveys under different levels of systematic uncertainties, we demonstrate the potential for percent-level constraints on model parameters by an LSST-like optical cluster survey of 300,000 clusters and a richness-mass variance of $0.3^2$. Even better constraints could potentially be achieved by a survey with one-tenth the sample size but with a reduced selection property variance of $0.1^2$. Potential benefits and extensions to the basic MOR parameterization are discussed.

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HSC-XXL : Baryon budget of the 136 XXL Groups and Clusters

We present our determination of the baryon budget for an X-ray-selected XXL sample of 136 galaxy groups and clusters spanning nearly two orders of magnitude in mass ($M_{500}\sim 10^{13}-10^{15}M_\odot$) and the redshift range $0< z < 1$. Our joint analysis is based on the combination of HSC-SSP weak-lensing mass measurements, XXL X-ray gas mass measurements, and HSC and SDSS multiband photometry. We carry out a Bayesian analysis of multivariate mass-scaling relations of gas mass, galaxy stellar mass, stellar mass of brightest cluster galaxies (BCGs), and soft-band X-ray luminosity, by taking into account the intrinsic covariance between cluster properties, selection effect, weak-lensing mass calibration, and observational error covariance matrix. The mass-dependent slope of the gas mass--total mass ($M_{500}$) relation is found to be $1.29_{-0.10}^{+0.16}$, which is steeper than the self-similar prediction of unity, whereas the slope of the stellar mass--total mass relation is shallower than unity, $0.85_{-0.09}^{+0.12}$. The BCG stellar mass weakly depends on cluster mass with a slope of $0.49_{-0.10}^{+0.11}$. The baryon, gas mass, and stellar mass fractions as a function of $M_{500}$ agree with the results from numerical simulations and previous observations. We successfully constrain the full intrinsic covariance of the baryonic contents. The BCG stellar mass shows the larger intrinsic scatter at a given halo total mass, followed in order by stellar mass and gas mass. We find a significant positive intrinsic correlation coefficient between total (and satellite) stellar mass and BCG stellar mass and no evidence for intrinsic correlation between gas mass and stellar mass. All the baryonic components show no redshift evolution.

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Galaxy Velocity Bias in Cosmological Simulations: Towards Percent-level Calibration

Galaxy cluster masses, rich with cosmological information, can be estimated from internal dark matter (DM) velocity dispersions, which in turn can be observationally inferred from satellite galaxy velocities. However, galaxies are biased tracers of the DM, and the bias can vary over host halo and galaxy properties as well as time. We precisely calibrate the velocity bias, b_v -- defined as the ratio of galaxy and DM velocity dispersions -- as a function of redshift, host halo mass, and galaxy stellar mass threshold (Mstarsat), for massive halos (M200c > 1e13.5 msun) from five cosmological simulations: IllustrisTNG, Magneticum, Bahamas + Macsis, The Three Hundred Project, and MultiDark Planck-2. We first compare scaling relations for galaxy and DM velocity dispersion across simulations; the former is estimated using a new ensemble velocity likelihood method that is unbiased for low galaxy counts per halo, while the latter uses a local linear regression. The simulations show consistent trends of b_v increasing with M200c and decreasing with redshift and Mstarsat. The ensemble-estimated theoretical uncertainty in b_v is 2-3% but becomes percent-level when considering only the three highest resolution simulations. We update the mass-richness normalization previously estimated by Farahi et al. (2016) for an SDSS redMaPPer cluster sample. The improved accuracy of our b_v estimates reduces the mass normalization uncertainty from 22% to 8%, demonstrating that dynamical estimation techniques can be competitive with weak lensing in calibrating population mean masses. We discuss necessary steps for further improving this precision. Our estimates for b_v(M200c, Mstarsat, z) are made publicly available.

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Baryonic Imprints on DM Halos: Population Statistics from Dwarf Galaxies to Galaxy Clusters

In a purely cold dark matter universe, the initial matter power spectrum and its subsequent gravitational growth contain no special mass- or time-scales, and so neither do the emergent population statistics of internal dark matter (DM) halo properties. Using 1.5 million halos from three IllustrisTNG realizations of a LambdaCDM universe, we show that galaxy formation physics drives non-monotonic features ("wiggles") into DM property statistics across six decades in halo mass, from dwarf galaxies to galaxy clusters. We characterize these features by extracting the halo mass-dependent statistics of five DM halo properties -- velocity dispersion, NFW concentration, density- and velocity-space shapes, and formation time -- using kernel-localized linear regression (KLLR). Comparing precise estimates of normalizations, slopes, and covariances between realizations with and without galaxy formation, we find systematic deviations across all mass-scales, with maximum deviations of 25% at the Milky-Way mass of 1e12 Msun. The mass-dependence of the wiggles is set by the interplay between different cooling and feedback mechanisms, and we discuss its observational implications. The property covariances depend strongly on halo mass and physics treatment, but the correlations are mostly robust. Using multivariate KLLR and interpretable machine learning, we show the halo concentration and velocity-space shape are principal contributors, at different mass, to the velocity dispersion variance. Statistics of mass accretion rate and DM surface pressure energy are provided in an appendix. We publicly release halo property catalogs and KLLR parameters for the TNG runs at twenty epochs up to z = 12.

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The Role of Machine Learning in the Next Decade of Cosmology

In recent years, machine learning (ML) methods have remarkably improved how cosmologists can interpret data. The next decade will bring new opportunities for data-driven cosmological discovery, but will also present new challenges for adopting ML methodologies and understanding the results. ML could transform our field, but this transformation will require the astronomy community to both foster and promote interdisciplinary research endeavors.

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Probing galaxy evolution in massive clusters using ACT and DES: splashback as a cosmic clock

We measure the projected number density profiles of galaxies and the splashback feature in clusters selected by the Sunyaev--Zeldovich (SZ) effect from the Advanced Atacama Cosmology Telescope (AdvACT) survey using galaxies observed by the Dark Energy Survey (DES). The splashback radius for the complete galaxy sample is consistent with theoretical measurements from CDM-only simulations, and is located at $2.4^{+0.3}_{-0.4}$ Mpc $h^{-1}$. We split the sample based on galaxy color and find significant differences in the profile shapes. Red galaxies and those in the green valley show a splashback-like minimum in their slope profile consistent with theoretical predictions, while the bluest galaxies show a weak feature that appears at a smaller radius. We develop a mapping of galaxies to subhalos in $N$-body simulations by splitting subhalos based on infall time onto the cluster halos. We find that the location of the steepest slope and differences in the shapes of the profiles can be mapped to differences in the average time of infall of galaxies of different colors. The minima of the slope in the galaxy profiles trace a discontinuity in the phase space of dark matter halos. By relating spatial profiles to infall time for galaxies of different colours, we can use splashback as a clock to understand galaxy quenching. We find that red galaxies have on average been in their clusters for over $3.2 ~\rm Gyrs$, green galaxies about $2.2 ~\rm Gyrs$, while blue galaxies have been accreted most recently and have not reached apocenter. Using the information from the complete radial profiles, we fit a simple quenching model and find that the onset of galaxy quenching in clusters occurs after a delay of about a gigayear, and that galaxies quench rapidly thereafter with an exponential timescale of $0.6$ Gyr.

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Stellar Property Statistics of Massive Halos from Cosmological Hydrodynamics Simulations: Common Kernel Shapes

We study stellar property statistics, including satellite galaxy occupation, of massive halo populations realized by three cosmological hydrodynamics simulations: BAHAMAS + MACSIS, TNG300 of the IllustrisTNG suite, and Magneticum Pathfinder. The simulations incorporate independent sub-grid methods for astrophysical processes with spatial resolutions ranging from $1.5$ to $6$ kpc, and each generates samples of $1000$ or more halos with $M_{\rm halo}> 10^{13.5} M_{\odot}$ at redshift $z=0$. Applying localized, linear regression (LLR), we extract halo mass-conditioned statistics (normalizations, slopes, and intrinsic covariance) for a three-element stellar property vector consisting of: i) $N_{sat}$, the number of satellite galaxies with stellar mass, $M_{\star, \rm sat} > 10^{10} M_{\odot}$ within radius $R_{200c}$ of the halo; ii) $M_{\star,\rm tot}$, the total stellar mass within that radius, and; iii) $M_{\star,\rm BCG}$, the gravitationally-bound stellar mass of the central galaxy within a $100 \, \rm kpc$ radius. Scaling parameters for the three properties with halo mass show mild differences among the simulations, in part due to numerical resolution, but there is qualitative agreement on property correlations, with halos having smaller than average central galaxies tending to also have smaller total stellar mass and a larger number of satellite galaxies. Marginalizing over total halo mass, we find the satellite galaxy kernel, $p(\ln N_{sat}\,|\,M_{\rm halo},z)$ to be consistently skewed left, with skewness parameter $γ= -0.91 \pm 0.02$, while that of $\ln M_{\star,\rm tot}$ is closer to log-normal, in all three simulations. The highest resolution simulations find $γ\simeq -0.8$ for the $z=0$ shape of $p(\ln M_{\star,\rm BCG}\,|\,M_{\rm halo},z)$ and also that the fractional scatter in total stellar mass is below $10\%$ in halos more massive than $10^{14.3} M_{\odot}$.

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Detection of anti-correlation of hot and cold baryons in galaxy clusters

The largest clusters of galaxies in the Universe contain vast amounts of dark matter, plus baryonic matter in two principal phases, a majority hot gas component and a minority cold stellar phase comprising stars, compact objects, and low-temperature gas. Hydrodynamic simulations indicate that the highest-mass systems retain the cosmic fraction of baryons, a natural consequence of which is anti-correlation between the masses of hot gas and stars within dark matter halos of fixed total mass. We report observational detection of this anti-correlation based on 4 elements of a $9\times9$ element covariance matrix for nine cluster properties, measured from X-ray, optical, infrared and millimetre wavelength observations of 41 clusters from the Local Cluster Substructure Survey. These clusters were selected using explicit and quantitative selection rules that were then encoded in our hierarchical Bayesian model. Our detection of anti-correlation is consistent with predictions from contemporary hydrodynamic cosmological simulations that were not tuned to reproduce this signal.

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LoCuSS: Scaling relations between galaxy cluster mass, gas, and stellar content

We present a simultaneous analysis of galaxy cluster scaling relations between weak-lensing mass and multiple cluster observables, across a wide range of wavelengths, that probe both gas and stellar content. Our new hierarchical Bayesian model simultaneously considers the selection variable alongside all other observables in order to explicitly model intrinsic property covariance and account for selection effects. We apply this method to a sample of 41 clusters at $0.15<z<0.30$, with a well-defined selection criteria based on RASS X-ray luminosity, and observations from Chandra / XMM, SZA, Planck, UKIRT, SDSS and Subaru. These clusters have well-constrained weak-lensing mass measurements based on Subaru / Suprime-Cam observations, which serve as the reference masses in our model. We present 30 scaling relation parameters for 10 properties. All relations probing the intracluster gas are slightly shallower than self-similar predictions, in moderate tension with prior measurements, and the stellar fraction decreases with mass. K-band luminosity has the lowest intrinsic scatter with a 95th percentile of 0.16, while the lowest scatter gas probe is gas mass with a fractional intrinsic scatter of $0.16 \pm 0.03$. We find no distinction between the core-excised X-ray or high-resolution Sunyaev-Zel'dovich relations of clusters of different central entropy, but find with modest significance that higher entropy clusters have higher stellar fractions than their lower entropy counterparts. We also report posterior mass estimates from our likelihood model.

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The Buzzard Flock: Dark Energy Survey Synthetic Sky Catalogs

We present a suite of 18 synthetic sky catalogs designed to support science analysis of galaxies in the Dark Energy Survey Year 1 (DES Y1) data. For each catalog, we use a computationally efficient empirical approach, ADDGALS, to embed galaxies within light-cone outputs of three dark matter simulations that resolve halos with masses above ~5x10^12 h^-1 m_sun at z <= 0.32 and 10^13 h^-1 m_sun at z~2. The embedding method is tuned to match the observed evolution of galaxy counts at different luminosities as well as the spatial clustering of the galaxy population. Galaxies are lensed by matter along the line of sight --- including magnification, shear, and multiple images --- using CALCLENS, an algorithm that calculates shear with 0.42 arcmin resolution at galaxy positions in the full catalog. The catalogs presented here, each with the same LCDM cosmology (denoted Buzzard), contain on average 820 million galaxies over an area of 1120 square degrees with positions, magnitudes, shapes, photometric errors, and photometric redshift estimates. We show that the weak-lensing shear catalog, redMaGiC galaxy catalogs and redMaPPer cluster catalogs provide plausible realizations of the same catalogs in the DES Y1 data by comparing their magnitude, color and redshift distributions, angular clustering, and mass-observable relations, making them useful for testing analyses that use these samples. We make public the galaxy samples appropriate for the DES Y1 data, as well as the data vectors used for cosmology analyses on these simulations.

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Localized massive halo properties in Bahamas and Macsis simulations: scalings, log-normality, and covariance

Using tens of thousands of halos realized in the BAHAMAS and MACSIS simulations produced with a consistent astrophysics treatment that includes AGN feedback, we validate a multi-property statistical model for the stellar and hot gas mass behavior in halos hosting groups and clusters of galaxies. The large sample size allows us to extract fine-scale mass--property relations (MPRs) by performing local linear regression (LLR) on individual halo stellar mass (${\rm M}_{\rm star}$) and hot gas mass (${\rm M}_{\rm gas}$) as a function of total halo mass (${\rm M}_{\rm halo}$). We find that: 1) both the local slope and variance of the MPRs run with mass (primarily) and redshift (secondarily); 2) the conditional likelihood, $p({\rm M}_{\rm star},\ {\rm M}_{\rm gas} | \ {\rm M}_{\rm halo}, z)$ is accurately described by a multivariate, log-normal distribution, and; 3) the covariance of ${\rm M}_{\rm star}$ and ${\rm M}_{\rm gas}$ at fixed ${\rm M}_{\rm halo}$ is generally negative, reflecting a partially closed baryon box model for high mass halos. We validate the analytical population model of Evrard et al. (2014), finding sub-percent accuracy in the log-mean halo mass selected at fixed property, $\langle \ln {\rm M}_{\rm halo} | {\rm M}_{\rm gas} \rangle$ or $\langle \ln {\rm M}_{\rm halo} | {\rm M}_{\rm star} \rangle$, when scale-dependent MPR parameters are employed. This work highlights the potential importance of allowing for running in the slope and scatter of MPRs when modeling cluster counts for cosmological studies. We tabulate LLR fit parameters as a function of halo mass at $z=0$, $0.5$ and 1 for two popular mass conventions.

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VDES J2325-5229 a z=2.7 gravitationally lensed quasar discovered using morphology independent supervised machine learning

We present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift $z_{s}=2.74$ and image separation of $2.9"$ lensed by a foreground $z_{l}=0.40$ elliptical galaxy. Since the images of gravitationally lensed quasars are the superposition of multiple point sources and a foreground lensing galaxy, we have developed a morphology independent multi-wavelength approach to the photometric selection of lensed quasar candidates based on Gaussian Mixture Models (GMM) supervised machine learning. Using this technique and $gi$ multicolour photometric observations from the Dark Energy Survey (DES), near IR $JK$ photometry from the VISTA Hemisphere Survey (VHS) and WISE mid IR photometry, we have identified a candidate system with two catalogue components with $i_{AB}=18.61$ and $i_{AB}=20.44$ comprised of an elliptical galaxy and two blue point sources. Spectroscopic follow-up with NTT and the use of an archival AAT spectrum show that the point sources can be identified as a lensed quasar with an emission line redshift of $z=2.739\pm0.003$ and a foreground early type galaxy with $z=0.400\pm0.002$. We model the system as a single isothermal ellipsoid and find the Einstein radius $θ_E \sim 1.47"$, enclosed mass $M_{enc} \sim 4 \times 10^{11}$M$_{\odot}$ and a time delay of $\sim$52 days. The relatively wide separation, month scale time delay duration and high redshift make this an ideal system for constraining the expansion rate beyond a redshift of 1.

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Host Galaxy Identification for Supernova Surveys

Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST), which will discover SNe by the thousands. Spectroscopic resources are limited, so in the absence of real-time SN spectra these surveys must rely on host galaxy spectra to obtain accurate redshifts for the Hubble diagram and to improve photometric classification of SNe. In addition, SN luminosities are known to correlate with host-galaxy properties. Therefore, reliable identification of host galaxies is essential for cosmology and SN science. We simulate SN events and their locations within their host galaxies to develop and test methods for matching SNe to their hosts. We use both real and simulated galaxy catalog data from the Advanced Camera for Surveys General Catalog and MICECATv2.0, respectively. We also incorporate "hostless" SNe residing in undetected faint hosts into our analysis, with an assumed hostless rate of 5%. Our fully automated algorithm is run on catalog data and matches SNe to their hosts with 91% accuracy. We find that including a machine learning component, run after the initial matching algorithm, improves the accuracy (purity) of the matching to 97% with a 2% cost in efficiency (true positive rate). Although the exact results are dependent on the details of the survey and the galaxy catalogs used, the method of identifying host galaxies we outline here can be applied to any transient survey.

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RHAPSODY-G simulations II - Baryonic growth and metal enrichment in massive galaxy clusters

We study the evolution of the stellar component and the metallicity of both the intracluster medium and of stars in massive ($M_{\rm vir}\approx 6\times 10^{14}$ M$_{\odot}/h$) simulated galaxy clusters from the Rhapsody-G suite in detail and compare them to observational results. The simulations were performed with the AMR code RAMSES and include the effect of AGN feedback at the sub-grid level. AGN feedback is required to produce realistic galaxy and cluster properties and plays a role in mixing material in the central regions and regulating star formation in the central galaxy. In both our low and high resolution runs with fiducial stellar yields, we find that stellar and ICM metallicities are a factor of two lower than in observations. We find that cool core clusters exhibit steeper metallicity gradients than non-cool core clusters, in qualitative agreement with observations. We verify that the ICM metallicities measured in the simulation can be explained by a simple "regulator" model in which the metallicity is set by a balance of stellar yield and gas accretion. It is plausible that a combination of higher resolution and higher metal yield in AMR simulation would allow the metallicity of simulated clusters to match observed values; however this hypothesis needs to be tested with future simulations. Comparison to recent literature highlights that results concerning the metallicity of clusters and cluster galaxies might depend sensitively on the scheme chosen to solve the hydrodynamics.

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Galaxy Cluster Mass Estimation from Stacked Spectroscopic Analysis

We use simulated galaxy surveys to study: i) how galaxy membership in redMaPPer clusters maps to the underlying halo population, and ii) the accuracy of a mean dynamical cluster mass, $M_σ(λ)$, derived from stacked pairwise spectroscopy of clusters with richness $λ$. Using $\sim\! 130,000$ galaxy pairs patterned after the SDSS redMaPPer cluster sample study of Rozo et al. (2015 RMIV), we show that the pairwise velocity PDF of central--satellite pairs with $m_i < 19$ in the simulation matches the form seen in RMIV. Through joint membership matching, we deconstruct the main Gaussian velocity component into its halo contributions, finding that the top-ranked halo contributes $\sim 60\%$ of the stacked signal. The halo mass scale inferred by applying the virial scaling of Evrard et al. (2008) to the velocity normalization matches, to within a few percent, the log-mean halo mass derived through galaxy membership matching. We apply this approach, along with mis-centering and galaxy velocity bias corrections, to estimate the log-mean matched halo mass at $z=0.2$ of SDSS redMaPPer clusters. Employing the velocity bias constraints of Guo et al. (2015), we find $\langle \ln(M_{200c})|λ\rangle = \ln(M_{30}) + α_m \ln(λ/30)$ with $M_{30} = 1.56 \pm 0.35 \times 10^{14} M_\odot$ and $α_m = 1.31 \pm 0.06_{stat} \pm 0.13_{sys}$. Systematic uncertainty in the velocity bias of satellite galaxies overwhelmingly dominates the error budget.

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