Related papers: A New Non-Parametric Approach to Galaxy Morphologi…

We consistently analyse for the first time the impact of survey depth and spatial resolution on the most used morphological parameters for classifying galaxies through non-parametric methods: Abraham and Conselice-Bershady concentration…

Using deep 100-160 micron observations in GOODS-S from the GOODS-H survey, combined with HST/WFC3 NIR imaging from CANDELS, we present the first morphological analysis of a complete, FIR selected sample of 52 ULIRGs at z~2. We also make use…

We explore galaxy properties and their link with environment and clustering using a population of ~1000 galaxies formed in a high resolution hydrodynamic simulation of the Lambda CDM cosmology. At the redshift we concentrate on, z=1, the…

We describe the application of the `shapelet' linear decomposition of galaxy images to multi-wavelength morphological classification using the $u,g,r,i,$ and $z$-band images of 1519 galaxies from the Sloan Digital Sky Survey. We utilize…

We explore the evolution of the morphology density relation using the COSMOS-ACS survey and previous cluster studies. The Gini parameter measured in a Petrosian aperture is found to be an effective way of selecting early-type galaxies free…

We have found the u -r color versus g -i color gradient space can be used for highly successful morphology classification of galaxies in the Sloan Digital Sky Survey. In this space galaxies form early and late type branches well-separated…

Using HST/WFPC2 imaging in F606W (or F450W) and F814W filters, we obtained the color maps in observed frame for 36 distant (0.4<z<1.2) luminous infrared galaxies (LIRGs), with average star formation rates of ~100 M_sun/yr. Stars and compact…

We study morphology and luminosity segregation of galaxies in loose groups. We analyze the two catalogs of groups which have been identified in the Nearby Optical Galaxy (NOG) sample, by means of hierarchical and percolation…

We present new Hubble Space Telescope/Wide Field Camera 3 imaging of 25 extremely luminous (-23.2 < M_ UV < -21.2) Lyman-break galaxies (LBGs) at z ~ 7. The sample was initially selected from 1.65 deg^2 of ground-based imaging in the…

To address how the galaxy Hubble sequence is established and what physical processes are involved, we studied morphological properties and internal structures of field galaxies in the past (0.4<z<1). In addition to structural parameters…

We present the data release paper for the Galaxy Zoo: Hubble (GZH) project. This is the third phase in a large effort to measure reliable, detailed morphologies of galaxies by using crowdsourced visual classifications of colour composite…

We present positions, magnitudes, sizes and morphological classifications for 111 galaxies discovered in the Hubble Space Telescope NICMOS Camera 1 and Camera 2 parallel fields. We combine the magnitudes measured in the JHK-analog filters…

We revisit the evolution of galaxy morphology in the COSMOS field over the redshift range $0.2\leq z \leq 1$, using a large and complete sample of 33,605 galaxies with a stellar mass of log($M_{\ast}$/M$_{\odot} )>9.5$ with significantly…

Galaxy morphology in stellar light can be described by a series of "non-parametric" or "morphometric" parameters, such as concentration-asymmetry-smoothness, Gini, $M_{20}$, and Sersic fit. These parameters can be applied to column density…

We present a study of correlations between the elemental abundances and galaxy morphologies of 91 blue compact galaxies (BCGs) at z=0.20-0.35 with Sloan Digital Sky Survey (SDSS) DR7 data. We classify the morphologies of the galaxies as…

Using archival data from the Hubble Space Telescope, we study the quantitative morphological evolution of spectroscopically confirmed bright galaxies in the core regions of nine clusters ranging in redshift from $z = 0.31$ to $z = 0.84$. We…

In this study, we investigate the morphology of galaxies in the TNG100 simulation by applying mock observation techniques and compare the results with the observational data from the Sloan Digital Sky Survey (SDSS). By employing a…

Classification of galaxies is traditionally associated with their morphologies through visual inspection of images. The amount of data to come renders this task inhuman and Machine Learning (mainly Deep Learning) has been called to the…

We explore unsupervised machine learning for galaxy morphology analyses using a combination of feature extraction with a vector-quantised variational autoencoder (VQ-VAE) and hierarchical clustering (HC). We propose a new methodology that…

We study how optical galaxy morphology depends on mass and star formation rate (SFR) in the Illustris Simulation. To do so, we measure automated galaxy structures in 10808 simulated galaxies at z=0 with stellar masses 10^9.7 < M_*/M_sun <…