Related papers: Galaxy Zoo: Quantitative Visual Morphological Clas…
We measure the redshift evolution of the bar fraction in a sample of 2380 visually selected disc galaxies found in Cosmic Evolution Survey (COSMOS) Hubble Space Telescope (HST) images. The visual classifications used to identify both the…
Tidal features are a key observable prediction of the hierarchical model of galaxy formation and contain a wealth of information about the properties and history of a galaxy. Modern wide-field surveys such as LSST and Euclid will…
The large number of galaxies imaged by digital sky surveys reinforces the need for computational methods for analyzing galaxy morphology. While the morphology of most galaxies can be associated with a stage on the Hubble sequence,…
We present a description of the observations and data reduction procedures for an extensive spectroscopic and multi-band photometric study of nine high redshift, optically-selected cluster candidates. The primary goal of the survey is to…
We present a comprehensive analysis of the evolution of the morphological and structural properties of a large sample of galaxies at z=3-9 using early JWST CEERS NIRCam observations. Our sample consists of 850 galaxies at z>3 detected in…
Many aspects concerning the formation of spiral and disc galaxies remain unresolved, despite their discovery and detailed study over the past $150$ years. As such, we present the results of an observational search for proto-spiral galaxies…
Hubble Space Telescope (HST) imaging of four rich, X-ray luminous, galaxy clusters (0.33<z<0.83) is used to produce quantitative morphological measurements for galaxies in their fields. Catalogs of these measurements are presented for 1642…
With the development of a series of Galaxy sky surveys in recent years, the observations increased rapidly, which makes the research of machine learning methods for galaxy image recognition a hot topic. Available automatic galaxy image…
Understanding morphological types of galaxies is a key parameter for studying their formation and evolution. Neural networks that have been used previously for galaxy morphology classification have some disadvantages, such as not being…
The dynamical history of most merging galaxies is not well understood. Correlations between galaxy interaction and star formation have been found in previous studies, but require the context of the physical history of merging systems for…
We present structural measurements for the galaxies in the 0.05<z<0.0585 groups of the Zurich Environmental Study, aimed at establishing how galaxy properties depend on four environmental parameters: group halo mass M_GROUP, group-centric…
The Euclid mission is expected to image millions of galaxies with high resolution, providing an extensive dataset to study galaxy evolution. We investigate the application of deep learning to predict the detailed morphologies of galaxies in…
Projected axis ratio measurements of 880 early-type galaxies at redshifts 1<z<2.5 selected from CANDELS are used to reconstruct and model their intrinsic shapes. The sample is selected on the basis of multiple rest-frame colors to reflect…
Big data has become the norm in astronomy, making it an ideal domain for computer science research. Astronomers typically classify galaxies based on their morphologies, a practice that dates back to Hubble (1936). With small datasets,…
We present Hubble Space Telescope Wide Field Camera 3 slitless grism spectroscopy of 28 emission-line galaxies at z~2, in the GOODS-S region of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS). The high…
Warped structures are often observed in disk galaxies, yet their physical origin is still under investigation. We present a systematic study of warped edge-on disk galaxies based on imaging data from the DESI Legacy Imaging Surveys DR8,…
The morphology of a galaxy stems from secular and environmental processes during its evolutionary history. Thus galaxy morphologies have been a long used tool to gain insights on galaxy evolution. We visually classify morphologies on…
We examine resolved spectroscopic data obtained with the Keck II telescope for 44 spheroidal galaxies in the fields of two rich clusters, Cl0024+16 (z=0.40) and MS0451-03 (z=0.54), and contrast this with similar data for 23 galaxies within…
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…
Building on our previous work, we apply a U-Net Variational Autoencoder (VAE) framework to denoise galaxy images from the James Webb Space Telescope (JWST) and enhance morphological classification. This study focuses on galaxies observed up…