Related papers: Revisiting the Hubble sequence in the SDSS DR7 spe…
We present a catalog of 799 clusters of galaxies in the redshift range z_est = 0.05 - 0.3 selected from ~400 deg^2 of early SDSS commissioning data along the celestial equator. The catalog is based on merging two independent selection…
In order to explore the statistical properties of galaxy morphological types in compact groups (CGs), we construct a random group sample which has the same distributions of redshift and number of member galaxies as those of the CG sample.…
Clustering objects into synthetic groups is a natural activity of any science. Astrophysics is not an exception and is now facing a deluge of data. For galaxies, the one-century old Hubble classification and the Hubble tuning fork are still…
Recent application of the Bayesian algorithm BORG to the Sloan Digital Sky Survey (SDSS) main sample galaxies resulted in the physical inference of the formation history of the observed large-scale structure from its origin to the present…
Encoded within the morphological structure of galaxies are clues related to their formation and evolutionary history. Recent advances pertaining to the statistics of galaxy morphology include sophisticated measures of concentration (C),…
We present the results from adaptive optics (AO) assisted imaging in the Ks band of an area of 15 arcmin^2 for SWAN (Survey of a Wide Area with NACO). We derive the high resolution near-IR morphology of ~400 galaxies up to Ks~23.5 in the…
The Hubble sequence is a common classification scheme for the structure of galaxies. Despite the tremendous usefulness of this diagnostic, we still do not fully understand when, where, and how this morphological ordering was put in place.…
The availability of high-quality spectra for a large number of galaxies in the SDSS survey allows for a more sophisticated extraction of information about their stellar populations than, e.g., the luminosity weighted age. Indeed,…
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…
Classifying galaxies is an essential step for studying their structures and dynamics. Using GalaxyZoo2 (GZ2) fractions thresholds, we collect 545 and 11,735 samples in non-galaxy and galaxy classes, respectively. We compute the Zernike…
We have carried out a systematic search for galaxy-scale strong lenses in multiband imaging from the Hyper Suprime-Cam (HSC) survey. Our automated pipeline, based on realistic strong-lens simulations, deep neural network classification, and…
Ram pressure stripped galaxies are rare cases of environmental evolution in action. However, our ability to understand these galaxies is limited by the small number of identified galaxies experiencing ram pressure stripping (RPS). Our aim…
We present results on the morphological and structural evolution of a total of 4265 galaxies observed with JWST at $1.5 < z < 8$ in the JWST CEERS observations that overlap with the CANDELS EGS field. This is the biggest visually classified…
In this work we present an atlas of composite spectra of galaxies based on the data of the Sloan Digital Sky Survey Data Release 7 (SDSS DR7). Galaxies are classified by colour, nuclear activity and star-formation activity to calculate…
This is the first paper in a series devoted to review the main properties of galaxies designated S0 in the Hubble classification system. Our aim is to gather abundant and, above all, robust information on the most relevant physical…
The typical galaxy in the local universe is expected to be in a self-regulated quasi-equilibrium, displaying a settled morphology that falls within the Hubble Sequence. The Arp and Arp-Madore catalogs are filled with striking examples of…
The Sloan Digital Sky Survey (SDSS) was foundational to the study of galaxy evolution, having revealed the bimodality of galaxies and the relationship between their structure and star-forming activity. However, ground-based optical surveys…
We investigate the integrated spectra of a sample of 24 normal galaxies. A principal component analysis suggests that most of the variance present in the spectra is due to the differences in morphology of the galaxies in the sample. We show…
We report an automated morphological classification of galaxies into S-wise spirals, Z-wise spirals, and non-spirals using big image data taken from Subaru/Hyper Suprime-Cam (HSC) Survey and a convolutional neural network(CNN)-based deep…
Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies…