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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Do blue galaxy-clusters have hot intracluster gas?

Abstract We present herein a systematic X-ray analysis of blue galaxy clusters at z = 0.84 discovered by the Subaru telescope. The sample consisted of 43 clusters identified by combining red-sequence and blue-cloud surveys, covering a wide range of emitter fractions (i.e., 0.3–0.8). The spatial extent of the over-density region of emitter galaxies was approximately 1 Mpc in radius. The average cluster mass was estimated as 0.6(<1.5) × 1014 M⊙ from the stacked weak-lensing measurement. We analyzed the XMM-Newton archival data, and measured the X-ray luminosity of the hot intracluster medium. As a result, diffuse X-ray emission was marginally detected in 14 clusters, yielding an average luminosity of 5 × 1042 erg s−1. To the contrary, it was not significant in 29 clusters. The blue clusters were significantly fainter than the red-dominated clusters, and the X-ray luminosity did not show any meaningful correlation either with emitter fraction or richness. The X-ray surface brightness was low, but the amount of gas mass was estimated to be comparable to that observed in the 1013–1014 M⊙ cluster. Based on the results, we suggest that the blue clusters are at the early formation stage, and the gas is yet to be compressed and heated up to produce appreciable X-rays. Follow-up spectroscopic measurements are essential to clarify the dynamical status and co-evolution of galaxies and hot gas in the blue clusters.

Misato, Rana↗
DOE OSTI2024

Identifying Climate Patterns Using Clustering Autoencoder Techniques

Abstract The complexity of growing spatiotemporal resolution of climate simulations produces a variety of climate patterns under different projection scenarios. This paper proposes a new data-driven climate classification workflow via an unsupervised deep learning technique that can dimensionally reduce the vast volume of spatiotemporal numerical climate projection data into a compact representation. We aim to identify distinct zones that capture multiple climate variables as well as their future changes under different climate change scenarios. Our approach leverages convolutional autoencoders combined with k -means clustering (standard autoencoder) and online clustering based on the Sinkhorn–Knopp algorithm (clustering autoencoder) across the conterminous United States (CONUS) to capture unique climate patterns in a data-driven fashion from the Geophysical Fluid Dynamics Laboratory Earth System Model with GOLD component (GFDL-ESM2G). The developed approach compresses 70 years of GFDL-ESM2G simulation at 0.125° spatial resolution across the CONUS under multiple warming scenarios to a lower-dimensional space by a factor of 660 000 and then tested on 150 years of GFDL-ESM2G simulation data. The results show that five climate clusters capture physically reasonable and spatially stable climatological patterns matched to known climate classes defined by human experts. Results also show that using a clustering autoencoder can reduce the computational time for clustering by up to 9.2 times when compared to using a standard autoencoder. Our five unique climate patterns resulting from the deep learning–based clustering of the lower-dimensional space thereby enable us to provide insights on hydrometeorology and its spatial heterogeneity across the conterminous United States immediately without downloading large climate datasets. Significance Statement This paper presents a data-driven climate classification approach using unsupervised deep learning to dimensionally reduce climate model outputs and to identify distinct climate regions for their future changes. Our approach compresses climate information for 70 years of Geophysical Fluid Dynamics Laboratory Earth System Model data across the conterminous United States (CONUS) at 0.125° spatial resolution. The results reveal that five climate clusters capture reasonable and stable climatological patterns matched to known climate patterns. The embedded clustering process in deep learning provides ×9.2 times faster execution than the k -means clustering technique. These results give us insight about climate spatial patterns and heterogeneity of hydrological patterns across the conterminous United States without downloading large climate datasets.

Kurihana, Takuya↗
DOE OSTI2021

Analysis of Completion Design Impact on Cluster Efficiency and Pressure-Based Well Communication in HFTS-2 Delaware Basin

The Hydraulic Fracturing Test Site 2 (HFTS-2) is a joint industry project in the Delaware basin to advance hydraulic fracturing understanding and improve productivity in shale reservoirs. The project integrates multi-disciplinary approaches to evaluate different completion designs, well spacing, inter-well communication, and stimulated rock volume, among other factors. This paper focused on two major areas related to hydraulic fracture performance. First, an analysis of different completion designs on cluster efficiency based on near well Distributed Acoustic Sensing (DAS). Second, an evaluation of well and completion designs on inter-well fracture driven interactions (FDIs) based on downhole pressure monitoring. Fluid/sand distribution and cluster efficiency analyses were based on near wellbore DAS data collected from two adjacent horizontal wells completed in two different landing zones in the Wolfcamp formation. These wells had different completion designs aiming to evaluate the effect of normal vs. extended stage lengths, perforation hole tapering and limited entry. Standard deviation from ideal fluid/sand distribution and waterfall plots were used to evaluate cluster efficiency for each design and stage. Inter-well FDIs analysis was conducted among the horizontal wells and a vertical monitor well. One horizontal well served as the monitor well while the other horizontal well was being treated. The vertical well was instrumented with downhole pressure and temperature gauges to aid monitoring fracture height growth. The pressure response during and after fracturing was characterized based on maximum pressure increase value and slope. Pressure response vs. FDIs trigger factors such distance, cluster efficiency and stage fluid volume were also analyzed. Based on the different completion and perforation designs tested, DAS analysis suggests that limited entry design worked best. Extreme limited entry showed the potential of high perforation erosion and reduced cluster efficiency. Here, the limited entry and tapered perforation design demonstrated potential to improve the cluster efficiency for extended stage lengths. Pressure monitoring across formation units proved to be critical to understand fracture interactions and fracture vertical growth. Pressure communication across different formation units during hydraulic fracturing operation indicate fractures grew upwards during Wolfcamp wells fracturing. However, this pressure communication dissipated over time. High intensity FDIs were recorded when the frac stages Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/1-21URTC/D011S018R001/2477607/urtec-2021-5289-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5289 were closer to the pressure gauge location in the monitor wells. Some of these stages that produced high intensity FDIs also had high fluid volume per cluster and low cluster efficiency. The multi-disciplinary and high-quality data collected from HFTS-2 helped to further understand why completion approaches such as limited entry and tapered perforation design are successful in improving cluster efficiency. The DAS data combined with downhole high-resolution pressure measurements also helped to quantify the effect of lower cluster efficiency data on the incidence and intensity of FDIs.

58 GEOSCIENCES↗
DOE OSTI2023

Spatio-Temporal Surrogates for Interaction of a Jet with High Explosives: Part II - Clustering Extremely High-Dimensional Grid-Based Data

Building an accurate surrogate model for the spatio-temporal outputs of a computer simulation is a challenging task. A simple approach to improve the accuracy of the surrogate is to cluster the outputs based on similarity and build a separate surrogate model for each cluster. This clustering is relatively straightforward when the output at each time step is of moderate size. However, when the spatial domain is represented by a large number of grid points, numbering in the millions, the clustering of the data becomes more challenging. In this report, we consider output data from simulations of a jet interacting with high explosives. These data are available on spatial domains of different sizes, at grid points that vary in their spatial coordinates, and in a format that distributes the output across multiple files at each time step of the simulation. We first describe how we bring these data into a consistent format prior to clustering. Borrowing the idea of random projections from data mining, we reduce the dimension of our data by a factor of thousand, making it possible to use the iterative k-means method for clustering. We show how we can use the randomness of both the random projections, and the choice of initial centroids in k-means clustering, to determine the number of clusters in our data set. Our approach makes clustering of extremely high dimensional data tractable, generating meaningful cluster assignments for our problem, despite the approximation introduced in the random projections.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

The Distinctive Evolution of orfX Clostridium parabotulinum Strains and Their Botulinum Neurotoxin Type A and F Gene Clusters Is Influenced by Environmental Factors and Gene Interactions via Mobile Genetic Elements

Of the seven currently known botulinum neurotoxin-producing species of Clostridium, C. parabotulinum, or C. botulinum Group I, is the species associated with the majority of human botulism cases worldwide. Phylogenetic analysis of these bacteria reveals a diverse species with multiple genomic clades. The neurotoxins they produce are also diverse, with over 20 subtypes currently represented. The existence of different bont genes within very similar genomes and of the same bont genes/gene clusters within different bacterial variants/species indicates that they have evolved independently. The neurotoxin genes are associated with one of two toxin gene cluster types containing either hemagglutinin (ha) genes or orfX genes. These genes may be located within the chromosome or extrachromosomal elements such as large plasmids. Although BoNT-producing C parabotulinum bacteria are distributed globally, they are more ubiquitous in certain specific geographic regions. Notably, northern hemisphere strains primarily contain ha gene clusters while southern hemisphere strains have a preponderance of orfX gene clusters. OrfX C. parabotulinum strains constitute a subset of this species that contain highly conserved bont gene clusters having a diverse range of bont genes. While much has been written about strains with ha gene clusters, less attention has been devoted to those with orfX gene clusters. The recent sequencing of 28 orfX C. parabotulinum strains and the availability of an additional 91 strains for analysis provides an opportunity to compare genomic relationships and identify unique toxin gene cluster characteristics and locations within this species subset in depth. The mechanisms behind the independent processes of bacteria evolution and generation of toxin diversity are explored through the examination of bacterial relationships relating to source locations and evidence of horizontal transfer of genetic material among different bacterial variants, particularly concerning bont gene clusters. Analysis of the content and locations of the bont gene clusters offers insights into common mechanisms of genetic transfer, chromosomal integration, and development of diversity among these genes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The final WaZP galaxy cluster catalog of the Dark Energy Survey and comparison with SZE data

In this work, we present and characterize the galaxy cluster catalog detected by the WaZP cluster finder, which is not based on red-sequence identification, on the full six years of observations of the Dark Energy Survey (DES-Y6). The full catalog contains over 400k detected clusters with richnesses, Ngals, above 5 and that reach redshifts up to 1.3. We also provide a version of the catalog where the observation depth and richness computation are homogenized to be used for cosmology, containing 33k rich (Ngals >25) clusters. We compare our results with the previous WaZP catalog obtained from the DES first-year data release (DES-Y1). We find that essentially all clusters within the common footprint and depth limit are recovered. The deeper observations on DES-Y6 and the more complete available spectroscopic redshift sample lead to improvements in the redshifts of the clusters, resulting in an average scatter of 1.4% and offset of 0.2%. The optical clusters are also cross-matched with Sunyaev Zel'dovich Effect (SZE) cluster samples detected by the South Pole Telescope (SPT) and the Atacama Cosmology Telescope (ACT). We find that essentially all SZE clusters with reasonable overlapping footprint have a corresponding WaZP cluster. Conversely, 90% of the optical detections with richness greater than 150 have a counterpart in the deeper regions of the SZE surveys. Based on cross-match with the SZE catalogs, we also find that 15-20% of the SZE matched systems have more than one possible WaZP counterpart at the same redshift and within the SZE R500c, indicating possible interacting or unrelaxed systems. Finally, given the optical and SZE beams, WaZP and SZE centerings are found to be consistent. A more detailed study of the SZE-WaZP mass-richness relation will be presented in a separate paper.

Benoist, C. [OCA, Nice, Lab. Lagrange; LIneA, Rio ↗
DOE OSTI2026

Galaxy Clusters Selected via the Sunyaev-Zel'dovich Effect in 5 year data from the SPT-3G Main Survey

We report a new galaxy cluster catalog, selected using the thermal Sunyaev-Zel'dovich (SZ) effect, from 5 years of observations of the SPT-3G Main field. Drawn from arcminute-resolution data with white noise levels of 3.2, 2.5, and 8.9 $μ$K-arcmin at 95, 150, and 220 GHz, respectively, the sample consists of 8,892 cluster candidates detected above significance $ξ=4$, with an expected purity of $>82\%$ (4,480 at $ξ\ge5$ with purity $>99\%$). Using optical and infrared data we have confirmed 7,190 candidates as clusters. The sample spans a mass range $7.9 \times 10^{13}M_\odot/h_{70}< M_\textrm{500c} < 1.6 \times 10^{15}M_\odot/h_{70}$ with a median mass of $1.65 \times 10^{14}M_\odot/h_{70}$, and a redshift range of $0.0371$ and 271 at $z>1.5$. Compared to previous SZ cluster samples from South Pole Telescope and Atacama Cosmology Telescope data, the SPT-3G sample is highly consistent in mass and redshift but is significantly deeper, with per-cluster detection signal-to-noise 2-4 times higher and a cluster density of 4.5 confirmed clusters/deg$^2$. We cross match with eRASS1 cluster and point source catalogs, finding 1,279 and 1,319 matches, respectively. The SPT and eROSITA cluster mass estimates are in relatively good agreement. We perform a series of validation checks using both internal data splits and comparisons to external samples. These tests show increasing correlated (dusty) emission with redshift, with a $\sim17\times$ larger 220 GHz temperature increment for clusters at $z\sim1.5$ than $z\sim0.25$, but only weak evidence for correlated synchrotron emission. Finally, a number of clusters are flagged as candidate strong gravitational lenses.

Bleem, L. E. [Argonne (main); Chicago U., KICP; Ch↗
DOE OSTI2023

The cosmic web around the Coma cluster from constrained cosmological simulations

Galaxy clusters in the Universe occupy the important position of nodes of the cosmic web. They are connected among them by filaments, elongated structures composed of dark matter, galaxies, and gas. The connection of galaxy clusters to filaments is important, as it is related to the process of matter accretion onto the former. For this reason, investigating the connections to the cosmic web of massive clusters, especially well-known ones for which a lot of information is available, is a hot topic in astrophysics. In a previous work, we performed an analysis of the filament connections of the Coma cluster of galaxies, as detected from the observed galaxy distribution. In this work we resort to a numerical simulation whose initial conditions are constrained to reproduce the local Universe, including the region of the Coma cluster to interpret our observations in an evolutionary context. We detect the filaments connected to the simulated Coma cluster and perform an accurate comparison with the cosmic web configuration we detect in observations. We perform an analysis of the halos’ spatial and velocity distributions close to the filaments in the cluster outskirts. We conclude that, although not significantly larger than the average, the flux of accreting matter on the simulated Coma cluster is significantly more collimated close to the filaments with respect to the general isotropic accretion flux. This paper is the first example of such a result and the first installment in a series of publications which will explore the build-up of the Coma cluster system in connection to the filaments of the cosmic web as a function of redshift.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Deep XMM–Newton observations of the most distant SPT-SZ galaxy cluster

ABSTRACT We present results from a 577 ks XMM–Newton observation of SPT-CL J0459–4947, the most distant cluster detected in the South Pole Telescope 2500 square degree (SPT-SZ) survey, and currently the most distant cluster discovered through its Sunyaev–Zel’dovich effect. The data confirm the cluster’s high redshift, z = 1.71 ± 0.02, in agreement with earlier, less precise optical/IR photometric estimates. From the gas density profile, we estimate a characteristic mass of $M_{500}=(1.8\pm 0.2)\times 10^{14}\, {\rm M}_{\odot }$; cluster emission is detected above the background to a radius of $\sim \!2.2\, r_{500}$, or approximately the virial radius. The intracluster gas is characterized by an emission-weighted average temperature of 7.2 ± 0.3 keV and metallicity with respect to Solar of $Z/\, Z_{\odot }=0.37\pm 0.08$. For the first time at such high redshift, this deep data set provides a measurement of metallicity outside the cluster centre; at radii $r\gt 0.3\, r_{500}$, we find $Z/\, Z_{\odot }=0.33\pm 0.17$ in good agreement with precise measurements at similar radii in the most nearby clusters, supporting an early enrichment scenario in which the bulk of the cluster gas is enriched to a universal metallicity prior to cluster formation, with little to no evolution thereafter. The leverage provided by the high redshift of this cluster tightens by a factor of 2 constraints on evolving metallicity models, when combined with previous measurements at lower redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Evolution of the Thermodynamic Properties of Clusters of Galaxies out to Redshift of 1.8

The thermodynamic properties of the hot plasma in galaxy clusters retains information on the processes leading to the formation and evolution of the gas in their deep, dark matter potential wells. These processes are dictated not only by gravity but also by gas physics, e.g. AGN feedback and turbulence. Here, we study the thermodynamic properties, e.g. density, temperature, pressure, and entropy, of the most massive and the most distant (z > 1.2) SPT-selected clusters, and compare them with those of the nearby clusters (z < 0.1) to constrain their evolution as a function of time and radius. We find that thermodynamic properties in the outskirts of high redshift clusters are remarkably similar to the low redshift clusters, and their evolution follows the prediction of the self-similar model. Their intrinsic scatter is larger, indicating that the physical properties that lead to the formation and virialization of cluster outskirts show evolving variance. On the other hand, thermodynamic properties in the cluster cores deviates significantly from self-similarity indicating that the processes that regulate the core are already in place in these very high redshift clusters. This result is supported by the unevolving physical scatter of all thermodynamic quantities in cluster cores.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Ultradiffuse Galaxies (UDGs) with Hyper Suprime-Cam. I. Revised Catalog of Coma Cluster UDGs*

This is the first in a series of papers on the properties of ultradiffuse galaxies (UDGs) in clusters of galaxies. We present an updated catalog of UDGs in the Coma Cluster using g- and r-band images obtained with Hyper Suprime-Cam (HSC) of the Subaru telescope. We develop a method to find UDGs even in the presence of contaminating objects, such as halos and background galaxies. This study expands upon our previous works that covered about half the area of the Coma Cluster. The HSC observations covered the whole Coma Cluster up to the virial radius and beyond (an area twice as large as the previous studies) and doubled the numbers of UDGs (r eff , r ≥ 1.5 kpc) and sub-UDGs (1.0 ≤ r eff , r < 1.5 kpc) to 774 and 729, respectively. The new UDGs show internal properties consistent with those of previous studies (e.g., a Sérsic index of approximately 1), and are distributed across the cluster, with a concentration around the cluster center. The whole cluster coverage clearly revealed an excess of their distribution toward the east to southwest direction along the cluster center, where Coma connects to other large-scale structure, and where a known substructure exists (the NGC 4839 subgroup). The alignment of the UDG distribution along the large-scale structure around Coma supports the interpretation that most of them lie at the distance of the Coma Cluster and the NGC 4839 subgroup.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Jacobian-scaled K-means clustering for physics-informed segmentation of reacting flows

This work introduces Jacobian-scaled K-means (JSK-means) clustering, which is a physicsinformed clustering strategy centered on the K-means framework. The method allows for the injection of underlying physical knowledge into the clustering procedure through a distance function modification: instead of leveraging conventional Euclidean distance vectors, the JSKmeans procedure operates on distance vectors scaled by matrices obtained from dynamical system Jacobians evaluated at the cluster centroids. The goal of this work is to show how the JSKmeans algorithm - without modifying the input dataset - produces clusters that capture regions of dynamical similarity, in that the clusters are redistributed towards high-sensitivity regions in phase space and are described by similarity in the source terms of samples instead of the samples themselves. The algorithm is demonstrated on a complex reacting flow simulation dataset (a channel detonation configuration), where the dynamics in the thermochemical composition space are known through the highly nonlinear and stiff Arrhenius-based chemical source terms. Interpretations of cluster partitions in both physical space and composition space reveal how JSK-means shifts clusters produced by standard K-means towards regions of high chemical sensitivity (e.g., towards regions of peak heat release rate near the detonation reaction zone). Furthermore, the findings presented here illustrate the benefits of utilizing Jacobian-scaled distances in clustering techniques, and the JSK-means method in particular displays promising potential for improving former partition-based modeling strategies in reacting flow (and other multi-physics) applications.

Clustering↗
DOE OSTI2020

Structural Rearrangements of Subnanometer Cu Oxide Clusters Govern Catalytic Oxidation

Sub-nanometer metal oxide clusters are very important materials that are widely used, for example, in catalysis or electronic devices such as sensors. Hence, it is critical to understand the atomic structures and properties of sub-nanometer metal oxide clusters under a reactive gas environment, such as O 2 . We consider here experimentally accessible precise-size Cu clusters (Cu 4 ) supported on partially hydroxylated amorphous alumina and show that such clusters can access, in catalytic conditions at high temperature under a pressure of O 2 , a large ensemble of oxidized structures, representing a large variety of oxygen content, of geometries in link with the support, and of catalytic activities for oxidation reactions, as seen from their reducibilities. A grand canonical basin hopping method based on first-principles energy reveals an ensemble of 24 configurations for the Cu 4 O x cluster of low free energy, less than 0.8 eV above the global minimum. The low free energy ensemble consists of clusters of different stoichiometries, which are mainly Cu 4 O 3 and Cu 4 O 4 in the temperature range of 200–400 °C and under a pressure of 0.5 bar of O 2 . The presence of several competitive isomers at each composition implies that cluster fluxionality impacts the phase diagram, which should be ensemble-averaged. In terms of catalytic oxidation activity, Cu 4 O 3 isomers present highly variable O abstraction energy: the most stable isomers are inactive for alkane oxidative dehydrogenation, but isomerization to metastable isomers, that proceed with low barrier, enable to create active configurations with low O abstraction energy. O atoms with the lowest anionic character, and thus of more electrophilic nature, present the best oxidation capability. In contrast, all Cu 4 O 4 isomers show a low O abstraction energy and a high potential catalytic activity. Here, this manuscript demonstrates the unique structural and electronic properties of sub-nano Cu oxide clusters and illustrates the critical roles of configuration ensembles and rearrangement to highly reactive metastable cluster isomers in nanocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Abell 1430: A merging cluster with exceptional diffuse radio emission

Diffuse radio emission has been found in many galaxy clusters, predominantly in massive systems which are in the state of merging. The radio emission can usually be classified as relic or halo emission, which are believed to be related to merger shocks or volume-filling turbulence, respectively. Recent observations have revealed radio bridges for some pairs of very close galaxy clusters. The mechanisms that may allow one to explain the high specific density of relativistic electrons, which are necessary to explain the radio luminosity of these bridge regions, have been poorly explored until now. When inspecting the first data release of the LOFAR Two-Metre Sky Survey (LoTSS), we discovered diffuse radio emission in the galaxy cluster Abell 1430. Here, for this work, we aim to determine the dynamical state of the cluster and characterise the diffuse radio emission. We analysed the LoTSS data in detail and complemented them with recent Karl G. Jansky Very Large Array observations in the L-band. To study the dynamical state of the cluster, we analysed XMM-Newton data, Chandra data, and Sloan Digital Sky Survey data. Moreover, we compared our results to clusters extracted from THE THREE HUNDRED PROJECT cosmological simulation. We find that Abell 1430 consists of two components, namely A1430-A and A1430-B, with a mass ratio of about 2:1. The massive component shows diffuse radio emission which can be classified as radio halo which shows a low radio power at 1.4 GHz with respect to the mass of the cluster. Most interestingly, there is extended diffuse radio emission in the following dubbed as the ‘Pillow’ according to its morphology, which is apparently related to A1430-B and which is neither typical halo nor typical relic emission. The origin of this emission is puzzling. We speculate that the two components of Abell 1430 undergo an off-axis merger. In this scenario, A1430-B is moving towards the main cluster component and may have compressed and stirred the medium in the filament between the two cluster components. We have discovered evidence for diffuse radio emission related to the low-density intracluster or intergalactic medium in Abell 1430. To date, only a few examples of emission originating from such regions are known. These discoveries are crucial to constrain possible acceleration mechanisms which may allow us to explain the presence of relativistic electrons in these regions. In particular, our results indicate a spectral index of α 144 MHz 1.5 GHz = -1.4±0.5 for the Pillow. If upcoming observations confirm a slope as flat as -1.4 or even flatter, this would pose a challenge for the electron acceleration scenarios.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Clusters of galaxies up to z = 1.5 identified from photometric data of the Dark Energy Survey and unWISE

ABSTRACT Using photometric data from the Dark Energy Survey and the Wide-field Infrared Survey Explorer, we estimate photometric redshifts for 105 million galaxies using the nearest-neighbour algorithm. From such a large data base, 151 244 clusters of galaxies are identified in the redshift range of 0.1 < z ≲ 1.5 based on the overdensity of the total stellar mass of galaxies within a given photometric redshift slice, among which 76 826 clusters are newly identified and 30 477 clusters have a redshift z > 1. We cross-match these clusters with those in the catalogues identified from the X-ray surveys and the Sunyaev–Zel’dovich (SZ) effect by the Planck, South Pole Telescope and Atacama Cosmology Telescope surveys, and get the redshifts for 45 X-ray clusters and 56 SZ clusters. More than 95 per cent SZ clusters in the sky region have counterparts in our catalogue. We find multiple optical clusters in the line of sight towards about 15 per cent of SZ clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Brightest cluster galaxies trace weak lensing mass bias and halo triaxiality in the three hundred project

Galaxy clusters have a triaxial matter distribution. The weak-lensing signal, an important part in cosmological studies, measures the projected mass of all matter along the line of sight, and therefore changes with the orientation of the cluster. Studies suggest that the shape of the brightest cluster galaxy (BCG) in the centre of the cluster traces the underlying halo shape, enabling a method to account for projection effects. We use 324 simulated clusters at four redshifts between 0.1 and 0.6 from ‘The Three Hundred Project’ to quantify correlations between the orientation and shape of the BCG and the halo. We find that haloes and their embedded BCGs are aligned, with an average ~20 degree angle between their major axes. The bias in weak lensing cluster mass estimates correlates with the orientation of both the halo and the BCG. Mimicking observations, we compute the projected shape of the BCG, as a measure of the BCG orientation, and find that it is most strongly correlated to the weak-lensing mass for relaxed clusters. We also test a 2D cluster relaxation proxy measured from BCG mass isocontours. The concentration of stellar mass in the projected BCG core compared to the total stellar mass provides an alternative proxy for the BCG orientation. We find that the concentration does not correlate to the weak-lensing mass bias, but does correlate with the true halo mass. Here, these results indicate that the BCG shape and orientation for large samples of relaxed clusters can provide information to improve weak-lensing mass estimates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Observational constraints of an anisotropic boost due to the projection effects using redMaPPer clusters

Optical clusters identified from red-sequence galaxies suffer from projection effects, where interloper galaxies along the line of sight to a cluster are mistaken as genuine members of the cluster. In the previous study, we found that the projection effects cause the boost on the amplitudes of clustering and lensing on large scale compared to the expected amplitudes in the absence of any projection effects. These boosts are caused by preferential selections of filamentary structure aligned to the line of sight due to distance uncertainties in photometric surveys. We model the projection effects with two simple assumptions and develop a novel method to quantify the size of the boost using cluster-galaxy cross-correlation functions. We validate our method using mock cluster catalogues built from cosmological N-body simulations and find that we can obtain unbiased constraints on the boost parameter with our model. We then apply our analysis on the SDSS redMaPPer clusters and find that the size of the boost is roughly 20 per cent for all the richness bins except the cluster sample with the richness bin λ ∈ [30, 40]. This is the first study to constrain the boost parameter independent from cluster cosmology studies and provides a self-consistency test for the projection effects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Improving galaxy cluster selection with the outskirt stellar mass of galaxies

The number density and redshift evolution of optically selected galaxy clusters offer an independent measurement of the amplitude of matter fluctuations, 𝑆 8 . However, recent results have shown that clusters chosen by the redMaPPer algorithm show richness-dependent biases that affect the weak lensing signals and number densities of clusters, increasing uncertainty in the cluster mass calibration and reducing their constraining power. Here, in this work, we evaluate an alternative cluster proxy, outskirt stellar mass, 𝑀 out , defined as the total stellar mass within a [50, 100] kpc envelope centered on a massive galaxy. This proxy exhibits scatter comparable to redMaPPer richness, 𝜆, but is less likely to be subject to projection effects. We compare the Dark Energy Survey Year 3 redMaPPer cluster catalog with a 𝑀 out selected cluster sample from the Hyper-Suprime Camera survey. We use weak lensing measurements to quantify and compare the scatter of 𝑀 out and 𝜆 with halo mass. Our results show 𝑀 out has a scatter consistent with 𝜆, with a similar halo mass dependence, and that both proxies contain unique information about the underlying halo mass. We find 𝜆-selected samples introduce features into the measured Δ⁢Σ signal that are not well fit by a log-normal scatter only model, absent in 𝑀 out selected samples. Our findings suggest that 𝑀 out offers an alternative for cluster selection with more easily calibrated selection biases, at least at the generally lower richnesses probed here. Combining both proxies may yield a mass proxy with a lower scatter and more tractable selection biases, enabling the use of lower mass clusters in cosmology. Finally, we find the scatter and slope in the 𝜆 −𝑀 out scaling relation to be 0.49 ±0.02 and 0.38 ±0.09.

79 ASTRONOMY AND ASTROPHYSICS↗