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Abstract We present the second data release of the Massive and Distant Clusters of WISE Survey 2 (MaDCoWS2). We expand from the equatorial first data release to most of the Dark Energy Camera Legacy Survey area, covering a total area of 6498 deg². The catalog consists of 133,036 signal-to-noise ratio (S/N) ≥ 5 galaxy cluster candidates at 0.1 ≤z≤ 2, including 6790 candidates atz> 1.5. We train a convolutional neural network (CNN) to identify spurious detections and include CNN-based cluster probabilities in the final catalog. We also compare the MaDCoWS2 sample with literature catalogs in the same area. The larger sample provides robust results that are consistent with our first data release. At S/N ≥ 5, we rediscover 59%–91% of clusters in existing catalogs that lie in the unmasked area of MC2. The median positional offsets are under 250 kpc, and the standard deviation of the redshifts is 0.031(1 +z). We fit a redshift-dependent power law to the relation between MaDCoWS2 S/N and observables from existing catalogs. Over the redshift ranges where the surveys overlap with MaDCoWS2, the lowest scatter is found between S/N and observables from optical/infrared surveys. We also assess the performance of our method using a mock light cone measuring purity and completeness as a function of cluster mass. The purity is above 90%, and we estimate the 50% completeness threshold at a virial mass of log(M/M_⊙) ≈ 14.3. The completeness estimate is uncertain due to the small number of massive halos in the light cone, but consistent with the recovery fraction found by comparing to other cluster catalogs. 

Abstract The evolution of galaxies depends on their masses and local environments; understanding when and how environmental quenching starts to operate remains a challenge. Furthermore, studies of the high-redshift regime have been limited to massive cluster members, owing to sensitivity limits or small fields of view when the sensitivity is sufficient, intrinsically biasing the picture of cluster evolution. In this work, we use stacking to investigate the average star formation history of more than 10,000 groups and clusters drawn from the Massive and Distant Clusters of WISE Survey 2. Our analysis covers near-ultraviolet to far-infrared wavelengths, for galaxy overdensities at 0.5 ≲z≲ 2.54. We employ spectral energy distribution fitting to measure the specific star formation rates (sSFRs) in four annular apertures with radii between 0 and 1000 kpc. Atz≳ 1.6, the average sSFR evolves similarly to the field in both the core and the cluster outskirts. Between $\overline{z}=1.60$and $\overline{z}=1.35$, the sSFR in the core drops sharply, and it continues to fall relative to the field sSFR at lower redshifts. We interpret this change as evidence that the impact of environmental quenching dramatically increases atz∼ 1.5, with the short time span of the transition suggesting that the environmental quenching mechanism dominant at this redshift operates on a rapid timescale. We find indications that the sSFR may decrease with increasing host halo mass, but lower-scatter mass tracers than the signal-to-noise ratio are needed to confirm this relationship. 

Abstract The Massive and Distant Clusters of WISE Survey 2 (MaDCoWS2) is a new survey designed as the successor of the original MaDCoWS survey. MaDCoWS2 improves upon its predecessor by using deeper optical and infrared data and a more powerful detection algorithm (PZWav). As input to the search, we usegrzphotometry from the DECam Legacy Survey (DECaLS) in combination with W1 and W2 photometry from the CatWISE2020 catalog to derive the photometric redshifts with full redshift probability distribution functions for Wide-field Infrared Survey Explorer (WISE)-selected galaxies. Cluster candidates are then detected using the PZWav algorithm to find three-dimensional galaxy overdensities from the sky positions and photometric redshifts. This paper provides the first MaDCoWS2 data release, covering 1461 (1838 without masking) deg²centered on the Hyper-SuprimeCam Subaru Strategic Program equatorial fields. Within this region, we derive a catalog of 22,970 galaxy cluster candidates detected at a signal-to-noise ratio (S/N) > 5. These clusters span the redshift range 0.1 <z< 2, including 1312 candidates atz> 1.5. We compare MaDCoWS2 to six existing catalogs in the area. We rediscover 60%–92% of the clusters in these surveys at S/N > 5. The medians of the absolute redshift offset are <0.02 relative to these surveys, while the standard deviations are less than 0.06. The median offsets between the detection position from MaDCoWS2 and other surveys are less than 0.25 Mpc. We quantify the relation between S/N and gas mass, total mass, luminosity, and richness from other surveys using a redshift-dependent power law relation. We find that the S/N-richness relation exhibits the lowest scatter. 

Abstract Galaxy cluster mergers are rich sources of information to test cluster astrophysics and cosmology. However, cluster mergers produce complex projected signals that are difficult to interpret physically from individual observational probes. Multi-probe constraints on the gas and dark matter (DM) cluster components are necessary to infer merger parameters that are otherwise degenerate. We present Improved Constraints on Mergers with SZ, Hydrodynamical simulations, Optical, and X-ray (ICM-SHOX), a systematic framework to jointly infer multiple merger parameters quantitatively via a pipeline that directly compares a novel combination of multi-probe observables to mock observables derived from hydrodynamical simulations. We report a first application of the ICM-SHOX pipeline to MACS J0018.5+1626, wherein we systematically examine simulated snapshots characterized by a wide range of initial parameters to constrain the MACS J0018.5+1626 merger geometry. We constrain the epoch of MACS J0018.5+1626 to the range 0–60 Myr post-pericenter passage, and the viewing angle is inclined ≈27°–40° from the merger axis. We obtain constraints for the impact parameter (≲250 kpc), mass ratio (≈1.5–3.0), and initial relative velocity when the clusters are separated by 3 Mpc (≈1700–3000 km s⁻¹). The primary and secondary clusters initially (at 3 Mpc) have gas distributions that are moderately and strongly disturbed, respectively. We discover a velocity space decoupling of the DM and gas distributions in MACS J0018.5+1626, traced by cluster-member galaxy velocities and the kinematic Sunyaev–Zel'dovich effect, respectively. Our simulations indicate this decoupling is dependent on the different collisional properties of the two distributions for particular merger epochs, geometries, and viewing angles. 

ABSTRACT We present an extension to a Sunyaev–Zel’dovich Effect (SZE) selected cluster catalogue based on observations from the South Pole Telescope (SPT); this catalogue extends to lower signal to noise than the previous SPT–SZ catalogue and therefore includes lower mass clusters. Optically derived redshifts, centres, richnesses, and morphological parameters together with catalogue contamination and completeness statistics are extracted using the multicomponent matched filter (MCMF) algorithm applied to the S/N > 4 SPT–SZ candidate list and the Dark Energy Survey (DES) photometric galaxy catalogue. The main catalogue contains 811 sources above S/N = 4, has 91  per cent purity, and is 95 per cent complete with respect to the original SZE selection. It contains in total 50 per cent more clusters and twice as many clusters above z = 0.8 in comparison to the original SPT-SZ sample. The MCMF algorithm allows us to define subsamples of the desired purity with traceable impact on catalogue completeness. As an example, we provide two subsamples with S/N > 4.25 and S/N > 4.5 for which the sample contamination and cleaning-induced incompleteness are both as low as the expected Poisson noise for samples of their size. The subsample with S/N > 4.5 has 98 per cent purity and 96 per cent completeness and is part of our new combined SPT cluster and DES weak-lensing cosmological analysis. We measure the number of false detections in the SPT-SZ candidate list as function of S/N, finding that it follows that expected from assuming Gaussian noise, but with a lower amplitude compared to previous estimates from simulations.