Related papers: Multiband galaxy morphologies for CLASH: a convolu…

We present a new high-precision parametric strong lensing model of the galaxy cluster MACS J0416.1-2403, at z=0.396, which takes advantage of the MUSE Deep Lensed Field (MDLF), with 17.1h integration in the northeast region of the cluster,…

Morphological classification of galaxies becomes increasingly challenging with redshift. We apply a hybrid supervised-unsupervised method to classify $\sim 14,000$ galaxies in the CANDELS fields at $0.2 \leq z \leq 2.4$ into spheroid, disk,…

A two-band (B and V) wide-field imaging survey of a complete, all-sky X-ray selected sample of 78 clusters in the redshift range z=0.04-0.07 is presented. The aim of this survey is to provide the astronomical community with a complete set…

Galaxy mergers play an important role in many aspects of galaxy evolution, therefore, more accurate merger identifications are paramount for achieving a complete understanding of galaxy evolution. As we enter the era of very large imaging…

Galaxies in the Hubble Ultra Deep Field (UDF) larger than 10 pixels (0.3 arcsec) have been classified according to morphology and their photometric properties are presented. There are 269 spirals, 100 ellipticals, 114 chains, 126…

We present in this paper one of the largest galaxy morphological classification catalogues to date, including over 20 million of galaxies, using the Dark Energy Survey (DES) Year 3 data based on Convolutional Neural Networks (CNN).…

ALHAMBRA is a photometric survey designed to trace the cosmic evolution and cosmic variance. It covers a large area of ~ 4 sq. deg in 8 fields, where 7 fields overlap with other surveys, allowing to have complementary data in other…

Aims: We present a wide-field multi-color survey of a homogeneous sample of eleven clusters of galaxies for which we measure total masses and mass distributions from weak lensing. Methods: The eleven clusters in our sample are all X-ray…

There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a…

We present the results of a proof-of-concept experiment which demonstrates that deep learning can successfully be used for production-scale classification of compact star clusters detected in HST UV-optical imaging of nearby spiral galaxies…

Current models of galaxy evolution are constrained by the analysis of catalogs containing the flux and size of galaxies extracted from multiband deep fields carrying inevitable observational and extraction-related biases which can be highly…

In this work, we update the unsupervised machine learning (UML) step by proposing an algorithm based on ConvNeXt large model coding to improve the efficiency of unlabeled galaxy morphology classifications. The method can be summarized into…

We present a 0.4-8$\mu$m multi-wavelength photometric catalog in the Extended Groth Strip (EGS) field. This catalog is built on the Hubble Space Telescope (HST) WFC3 and ACS data from the Cosmic Assembly Near-infrared Deep Extragalactic…

A significant fraction of high redshift star-forming disc galaxies are known to host giant clumps, whose nature and role in galaxy evolution are yet to be understood. In this work we first present a new method based on neural networks to…

Images of the Hubble Ultra Deep Field are analyzed to obtain a catalog of galaxies for which the angular sizes, surface brightness, photometric redshifts, and absolute magnitudes are found. The catalog contains a total of about 4000…

We train deep learning models on thousands of galaxy catalogues from the state-of-the-art hydrodynamic simulations of the CAMELS project to perform regression and inference. We employ Graph Neural Networks (GNNs), architectures designed to…

Brightest cluster galaxies (BCGs) are usually quiescent, but many exhibit star formation. Here we exploit the opportunity provided by rest-frame UV imaging of galaxy clusters in the CLASH (Cluster Lensing and Supernovae with Hubble)…

We perform a three-dimensional triaxial analysis of 16 X-ray regular and 4 high-magnification galaxy clusters selected from the CLASH survey by combining two-dimensional weak-lensing and central strong-lensing constraints. In a Bayesian…

We describe application of the `shapelet' linear decomposition of galaxy images to morphological classification using images of $\sim$ 3000 galaxies from the Sloan Digital Sky Survey. After decomposing the galaxies we perform a principal…

We present a morphological analysis of distant field galaxies using the deep ACS images from the public parallel NICMOS observations of the Hubble Ultra Deep Field obtained in the F435W (B), F606W (V), F775W (i) and F850LP (z) filters. We…