Related papers: A robust morphological classification method for g…
This paper follows series of our works on the applicability of various machine learning methods to the morphological galaxy classification (Vavilova et al., 2021, 2022). We exploited the sample of 315776 SDSS DR9 galaxies with absolute…
We analyze the Near Infrared ($\sim0.8-1\mu$m) rest-frame morphologies of galaxies with $\log M_*/M_\odot>9$ in the redshift range $0<z<6$, compare with previous HST-based results and release the first JWST-based morphological catalog of…
Galaxy morphology is one of the most fundamental ways to describe galaxy properties, but the morphology we observe may be affected by wavelength and spatial resolution, which may introduce systematic bias when comparing galaxies at…
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…
Wide-field, multi-band surveys now detect millions of unresolved sources in nearby galaxy clusters, yet separating globular clusters (GCs) from foreground stars and background galaxies remains challenging. Scalable, automated classification…
Galaxy morphology is a powerful diagnostic to assess the realism of cosmological hydrodynamical simulations. Determining the morphology of simulated galaxies requires the generation of synthetic images through 3D radiative transfer…
The morphological diversity of galaxies is a relevant probe of galaxy evolution and cosmological structure formation. However, in large sky surveys, even the morphological classification of galaxies into two classes, like late-type (LT) and…
We applied the image-based approach with a convolutional neural network model to the sample of low-redshifts galaxies with $-24^{m}<M_{r}<-19.4^{m}$ from the SDSS DR9. We divided it into two subsamples, SDSS DR9 galaxy dataset and Galaxy…
To better understand how galaxies assemble their structure and evolve over cosmic time, we present a new catalog of morphological measurements for over 340,000 sources spanning $0 < z < 12$, derived from deep JWST NIRCam imaging across four…
We examine a general framework for visualizing datasets of high (> 2) dimensionality, and demonstrate it using the morphology of galaxies at moderate redshifts. The distributions of various populations of such galaxies are examined in a…
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…
The taxonomy of galaxy morphology is critical in astrophysics as the morphological properties are powerful tracers of galaxy evolution. With the upcoming Large-scale Imaging Surveys, billions of galaxy images challenge astronomers to…
We present a morphological catalogue for $\sim$ 670,000 galaxies in the Sloan Digital Sky Survey in two flavours: T-Type, related to the Hubble sequence, and Galaxy Zoo 2 (GZ2 hereafter) classification scheme. By combining accurate existing…
The classification of galaxy morphology is a hot issue in astronomical research. Although significant progress has been made in the last decade in classifying galaxy morphology using deep learning technology, there are still some…
The distinction between stars and galaxies is a fundamental problem in the field of celestial classification. This issue has become challenging for these ongoing and upcoming digital surveys, which will produce terabytes and even petabytes…
We extend a recently developed galaxy morphology classification method, Quantitative Multiwavelength Morphology (QMM), to connect galaxy morphologies to their underlying physical properties. The traditional classification of galaxies…
The well-known cluster of galaxies ZwCl0024+1652 at z $\sim$ 0.4, lacks an in-depth morphological classification of its central region. While previous studies provide a visual classification of a patched area, we used the public code called…
We utilise the unprecedented depth and resolution of recent early-release science (ERS) JWST observations to define the near-infrared counterparts of sub-millimetre selected galaxies (SMGs). We identify 45 SCUBA-2 SMG positions within The…
We present morphologies of galaxies at $z \gtrsim 9$ resolved by JWST/NIRCam $2$-$5\mu$m imaging. Our sample consists of $22$ galaxy candidates identified by stringent dropout and photo-$z$ criteria in GLASS, CEERS, SMACS J0723, and…
Classification will be an important first step for upcoming surveys that will detect billions of new sources such as LSST and Euclid, as well as DESI, 4MOST and MOONS. The application of traditional methods of model fitting and…