Related papers: Cluster optical depth and pairwise velocity estima…
The CMB lensing signal from cosmic voids and superclusters probes the growth of structure in the low-redshift cosmic web. In this analysis, we cross-correlated the Planck CMB lensing map with voids detected in the Dark Energy Survey Year 3…
We cross-match galaxy cluster candidates selected via their Sunyaev-Zel'dovich effect (SZE) signatures in 129.1 deg$^2$ of the South Pole Telescope 2500d SPT-SZ survey with optically identified clusters selected from the Dark Energy Survey…
One emerging application of machine learning methods is the inference of galaxy cluster masses. In this note, machine learning is used to directly combine five simulated multiwavelength measurements in order to find cluster masses. This is…
The kinetic Sunyaev-Zel'dovich (kSZ) effect offers an indirect way to reconstruct large-scale cosmic velocities, by correlating high-resolution CMB temperature maps with galaxy surveys. In this work, we present the first three-dimensional…
New generation ground and space-based CMB experiments have ushered in discoveries of massive galaxy clusters via the Sunyaev-Zeldovich (SZ) effect, providing a new window for studying cluster astrophysics and cosmology. Many of the newly…
We show how to simulate the clustering of rich clusters of galaxies using a technique based on the Zel'dovich approximation. This method well reproduces the spatial distribution of clusters obtainable from full N-body simulations at a…
Forthcoming large galaxy cluster surveys will yield tight constraints on cosmological models. It has been shown that in an idealized survey, containing > 10,000 clusters, statistical errors on dark energy and other cosmological parameters…
We estimate the variance and the skewness of the cluster distribution in several dark matter (DM) models. The cluster simulations are based on the Zel'dovich approximation, the low computational cost of which allows us to run 50 random…
We present the first sample of 882 optically selected galaxy clusters in the Deep Lens Survey (DLS), selected with the Bayesian Cluster Finder. We create mock DLS data to assess completeness and purity rates, and find that both are at least…
We present a deep machine learning (ML) approach to constraining cosmological parameters with multi-wavelength observations of galaxy clusters. The ML approach has two components: an encoder that builds a compressed representation of each…
LSST will provide galaxy cluster catalogs up to z$\sim$1 that can be used to constrain cosmological models once their selection function is well-understood. We have applied the deep convolutional network YOLO for CLuster detection (YOLO-CL)…
The Sunyaev-Zeldovich thermal (tSZ) and kinetic (kSZ) effects can be used to constrain the thermodynamic properties of pressure and density, respectively, of galaxies and their surrounding regions. As SZ observations continue to improve, it…
Cosmic Microwave Background (CMB) lensing is a powerful probe of the matter distribution in the Universe. The standard quadratic estimator, which is typically used to measure the lensing signal, is known to be suboptimal for low-noise…
We present a stacked lensing analysis of 96 galaxy clusters selected by the thermal Sunyaev-Zel'dovich (SZ) effect in maps of the cosmic microwave background (CMB). We select foreground galaxy clusters with a $5\sigma$-level SZ threshold in…
We present a detailed mass reconstruction of the cluster RCS0224-0002 at $z=0.773$ from the strong lensing features observed with HST/WFPC2. The mass profile is reconstructed using a parametric approach. We introduce a novel method to fit…
The total masses of galaxy clusters characterize many aspects of astrophysics and the underlying cosmology. It is crucial to obtain reliable and accurate mass estimates for numerous galaxy clusters over a wide range of redshifts and mass…
The possibility to constrain cosmological parameters from galaxy surveys using field-level machine learning methods that bypass traditional summary statistics analyses, depends crucially on our ability to generate simulated training sets.…
The temperature and density of the hot diffuse medium pervading galaxy groups and clusters combine into one significant quantity, the entropy. Here we express the entropy levels and profiles in model-independent forms by joining two…
Building a comprehensive catalog of galaxy clusters is a fundamental task for the studies on the structure formation and galaxy evolution. In this paper, we present COSMIC (Cluster Optical Search using Machine Intelligence in Catalogs), an…
We compute the evolution of spatially flat, mixed cold and hot dark matter (``MDM") models containing both baryonic matter and two kinds of dark matter. The mean final Zeldovich-Sunyaev $y$ parameter is estimated to be $\bar y=(5.4\pm…