Related papers: Galaxy Morphological Classification with Zernike M…
The estimation of the bulge and disk massses, the main baryonic components of a galaxy, can be performed using various approaches, but their implementation tend to be challenging as they often rely on strong assumptions about either the…
We examine morphology-separated color-mass diagrams to study the quenching of star formation in $\sim 100,000$ ($z\sim0$) Sloan Digital Sky Survey (SDSS) and $\sim 20,000$ ($z\sim1$) Cosmic Assembly Near-Infrared Deep Extragalactic Legacy…
Being able to distinguish between galaxies that have recently undergone major merger events, or are experiencing intense star formation, is crucial for making progress in our understanding of the formation and evolution of galaxies. As…
Machine learning techniques have been increasingly useful in astronomical applications over the last few years, for example in the morphological classification of galaxies. Convolutional neural networks have proven to be highly effective in…
We present a machine learning search for local, low-mass galaxies ($z < 0.02$ and $10^6 M_\odot < M_* < 10^9 M_\odot$) using the combined photometric data from the DESI Imaging Legacy Surveys and the WISE survey. We introduce the spectrally…
In this paper we present a novel method for an automated diagnosis of breast carcinoma through multilevel iterative variational mode decomposition (VMD) and textural features encompassing Zernaike moments, fractal dimension and entropy…
Ground-based optical surveys such as PanSTARRS, DES, and LSST, will produce large catalogs to limiting magnitudes of r > 24. Star-galaxy separation poses a major challenge to such surveys because galaxies---even very compact…
The total masses of galaxy clusters characterize many aspects of astrophysics and the underlying cosmology. It is crucial to obtain reliable and accurate mass estimates for numerous galaxy clusters over a wide range of redshifts and mass…
We applied computer analysis to classify the broad morphological type of ~3,000,000 SDSS galaxies. The catalog provides for each galaxy the DR8 object ID, right ascension, declination, and the certainty of the automatic classification to…
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 morphological classification of galaxies is considered a relevant issue and can be approached from different points of view. The increasing growth in the size and accuracy of astronomical data sets brings with it the need for the use of…
We provide classifications for all 143 million non-repeat photometric objects in the Third Data Release of the Sloan Digital Sky Survey (SDSS) using decision trees trained on 477,068 objects with SDSS spectroscopic data. We demonstrate that…
Model fitting is frequently used to determine the shape of galaxies and the point spread function, for examples, in weak lensing analyses or morphology studies aiming at probing the evolution of galaxies. However, the number of parameters…
We suggest a set of morphological measures that we believe can help in quantifying the shapes of two-dimensional cosmological images such as galaxies, clusters, and superclusters of galaxies. The method employs non-parametric morphological…
We present a study on galaxy detection and shape classification using topometric clustering algorithms. We first use the DBSCAN algorithm to extract, from CCD frames, groups of adjacent pixels with significant fluxes and we then apply the…
Testing theories of hierarchical structure formation requires estimating the distribution of galaxy morphologies and its change with redshift. One aspect of this investigation involves identifying galaxies with disturbed morphologies (e.g.,…
Knowing the redshift of galaxies is one of the first requirements of many cosmological experiments, and as it's impossible to perform spectroscopy for every galaxy being observed, photometric redshift (photo-z) estimations are still of…
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…
We study the properties of galaxies at z=2 in a Lambda CDM universe, using two different types of hydrodynamic simulation methods (Eulerian TVD and SPH) and a spectrophotometric analysis in the Un, G, R filter set. The simulated galaxies at…
The statistical properties of the ellipticities of galaxy images depend on how galaxies form and evolve, and therefore constrain models of galaxy morphology, which are key to the removal of the intrinsic alignment contamination of…