Related papers: Revisiting the Hubble sequence in the SDSS DR7 spe…
This work is focused on the morphological classification of galaxies following the Hubble sequence in which the different classes are arranged in a hierarchy. The proposed method, BCNN, is composed of two main modules. First, 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…
There is an obvious need for automated classification of galaxies, as the number of observed galaxies increases very fast. We examine several approaches to this problem, utilising {\em Artificial Neural Networks} (ANNs). We quote results…
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…
Galaxies of rare morphology are of paramount scientific interest, as they carry important information about the past, present, and future universe. Once a rare galaxy is identified, studying it more effectively requires a set of galaxies of…
Galaxy morphologies provide valuable insights into their formation processes, tracing the spatial distribution of ongoing star formation and encoding signatures of dynamical interactions. While such information has been extensively…
Structural properties posses valuable information about the formation and evolution of galaxies, and are important for understanding the past, present, and future universe. Here we use unsupervised machine learning methodology to analyze a…
Mergers play a complex role in galaxy formation and evolution. Continuing to improve our understanding of these systems require ever larger samples, which can be difficult (even impossible) to select from individual surveys. We use the new…
Leveraging the wide area coverage of the COSMOS-Web survey, we quantify the abundance of different morphological types from $z\sim 7$ with unprecedented statistics and establish robust constraints on the epoch of emergence of the Hubble…
The classification of radio galaxies is central to understanding galaxy evolution, active galactic nuclei dynamics, and the large-scale structure of the universe. However, traditional manual techniques are inadequate for processing the…
We present a quantitative method to classify galaxies, based on multi-wavelength data and elaborated from the properties of nearby galaxies. Our objective is to define an evolutionary method that can be used for low and high redshift…
Galaxy morphology reflects structural properties which contribute to understand the formation and evolution of galaxies. Deep convolutional networks have proven to be very successful in learning hidden features that allow for unprecedented…
We apply a friends-of-friends algorithm to an enhanced SDSS DR12 spectroscopic catalog including redshift from literature to construct a catalog of $1588~N\ge3$ compact groups of galaxies containing 5179 member galaxies and covering the…
The morphology of radio galaxies is indicative of their interaction with their surroundings, among other effects. Since modern radio surveys contain a large number of radio sources that would be impossible to analyse and classify manually,…
Context. Convolutional neural networks (CNNs) are widely used for automated galaxy morphological classification in large surveys. However, projection effects, image artefacts, and intrinsic degeneracies limit reliable identification of…
We present a machine learning analysis of five labelled galaxy catalogues from the Galaxy And Mass Assembly (GAMA): The SersicCatVIKING and SersicCatUKIDSS catalogues containing morphological features, the GaussFitSimple catalogue…
We present mock JWST observations for more than 250,000 different galaxies from the Astrid simulation with $3 \leq z \leq 6$. The mock observations are made using the BPASS stellar SED model, and a simple dust model. They are then viewed…
We present a catalog of true edge-on disk galaxies automatically selected from the Seventh Data Release (DR7) of the Sloan Digital Sky Survey. A visual inspection of the $g$, $r$ and $i$ images of about 15000 galaxies allowed us to split…
We present a new galaxy cluster catalog constructed from SDSS DR9 using an Adaptive Matched Filter technique. Our main catalog has 46,479 galaxy clusters with richness $\Lambda_{200} > 20$ in the redshift range 0.045 $\le z <$ 0.641 in…
We investigate the morphological properties of 494 galaxies selected from the GMASS survey at z>1, primarily in their optical rest frame, using HST images, from the CANDELS survey. We propose that the Hubble sequence of galaxy morphologies…