Related papers: DeepSZ: Identification of Sunyaev-Zel'dovich Galax…
We present the analytical formulas, derived based on the halo model, to compute the cross-correlation between the thermal Sunyaev-Zel'dovich (SZ) effect and the distribution of galaxy clusters. By binning the clusters according to their…
We apply a matched-filter cluster detection algorithm to the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) i-band data for the Deep-1, Deep-2, Deep-3 and Deep-4 fields covering a total of 4square degrees. To test the implemented…
We investigate and demonstrate the use of convolutional neural networks (CNNs) for the task of distinguishing between merging and non-merging galaxies in simulated images, and for the first time at high redshifts (i.e. $z=2$). We extract…
The interaction of the cosmic microwave background (CMB) with the hot gas in clusters of galaxies, the so-called Sunyaev--Zel'dovich (SZ) effect, is a very useful tool that allows us to determine the physical conditions in such clusters and…
The pairwise kinematic Sunyaev-Zel'dovich (kSZ) signal from galaxy clusters is a probe of their line-of-sight momenta, and thus a potentially valuable source of cosmological information. In addition to the momenta, the amplitude of the…
As a unique classification scheme for urban forms and functions, the local climate zone (LCZ) system provides essential general information for any studies related to urban environments, especially on a large scale. Remote sensing…
In recent years, significant progress has been made in building new galaxy clusters samples, at low and high redshifts, from wide-area surveys, particularly exploiting the Sunyaev--Zel'dovich (SZ) effect. A large effort is underway to…
We describe a method for measuring the integrated Comptonization (YSZ) of clusters of galaxies from measurements of the Sunyaev-Zel'dovich (SZ) effect in multiple frequency bands and use this method to characterize a sample of galaxy…
We train three convolutional neural networks (CNNs) to classify galaxies with Galaxy Zoo 2 dataset and extract the activations from the last fully connected layer or the last average pooling layer of CNNs to study the high-dimensional…
We present a catalog of galaxy cluster candidates detected in 100 square degrees surveyed with the SPTpol receiver on the South Pole Telescope. The catalog contains 89 candidates detected with a signal-to-noise ratio greater than 4.6. The…
The use of galaxy clusters as precision cosmological probes relies on an accurate determination of their masses. However, inferring the relationship between cluster mass and observables from direct observations is difficult and prone to…
Various galaxy merger detection methods have been applied to diverse datasets. However, it is difficult to understand how they compare. We aim to benchmark the relative performance of machine learning (ML) merger detection methods. We…
Cloud detection is an important preprocessing step for the precise application of optical satellite imagery. In this paper, we propose a deep learning based cloud detection method named multi-scale convolutional feature fusion (MSCFF) for…
Future high resolution, high sensitivity Sunyaev-Zeldovich (SZ) observations of individual clusters will provide an exciting opportunity to answer specific questions about the dynamical state of the intra-cluster medium (ICM). In this paper…
We present Sunyaev-Zel'dovich (SZ) effect observations of a sample of 25 massive relaxed galaxy clusters observed with the Sunyaev-Zel'dovich Array (SZA), an 8-element interferometer that is part of the Combined Array for Research in…
We present a catalog of 500 galaxy cluster candidates in the SPT-Deep field: a 100 deg$^2$ field that combines data from the SPT-3G and SPTpol surveys to reach noise levels of 3.0, 2.2, and 9.0 $\mu$K-arcmin at 95, 150, and 220 GHz,…
We infer the mean optical depth of a sample of optically-selected galaxy clusters from the Dark Energy Survey (DES) via the pairwise kinematic Sunyaev-Zel'dovich (kSZ) effect. The pairwise kSZ signal between pairs of clusters drawn from the…
Studies have shown that the morphologies of galaxies are substantially transformed following coalescence after a merger, but post-mergers are notoriously difficult to identify, especially in imaging that is shallow or low-resolution. We…
Based on the DUSTGRAIN-pathfinder suite of simulations, we investigate observational degeneracies between nine models of modified gravity and massive neutrinos. Three types of machine learning techniques are tested for their ability to…
We develop a new method to estimate the redshift of galaxy clusters through resolved images of the Sunyaev-Zel'dovich effect (SZE). Our method is based on morphological observables which can be measured by actual and future SZE experiments.…