Related papers: Galaxy Morphological Classification with Manifold …

We present the data release for Galaxy Zoo 2 (GZ2), a citizen science project with more than 16 million morphological classifications of 304,122 galaxies drawn from the Sloan Digital Sky Survey. Morphology is a powerful probe for…

(abridged) In the last decade, the advent of enormous galaxy surveys has motivated the development of automated morphological classification schemes to deal with large data volumes. Existing automated schemes can successfully distinguish…

Most existing star-galaxy classifiers use the reduced summary information from catalogs, requiring careful feature extraction and selection. The latest advances in machine learning that use deep convolutional neural networks allow a machine…

We present a star/galaxy classification for the Southern Photometric Local Universe Survey (S-PLUS), based on a Machine Learning approach: the Random Forest algorithm. We train the algorithm using the S-PLUS optical photometry up to $r$=21,…

Distinguishing active galaxies from star-forming galaxies is essential for understanding galaxy evolution. Diagnostic methods like the BPT (Baldwin, Phillips, and Terlevich) diagram use optical emission-line ratios to separate galaxies.…

The morphology of a galaxy stems from secular and environmental processes during its evolutionary history. Thus galaxy morphologies have been a long used tool to gain insights on galaxy evolution. We visually classify morphologies on…

[abridged] New near-infrared surveys, using the HST, offer an unprecedented opportunity to study rest-frame optical galaxy morphologies at z>1 and to calibrate automated morphological parameters that will play a key role in classifying…

Joint lensing and dynamical mass profile determinations of galaxy clusters are an excellent tool to constrain modification of gravity at cosmological scales. However, search for tiny departures from General Relativity calls for an accurate…

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 use the Millennium Simulation, a 10 billion particle simulation of the growth of cosmic structure, to construct a new model of galaxy clustering. We adopt a methodology that falls midway between the traditional semi-analytic approach and…

We present the ROGER (Reconstructing Orbits of Galaxies in Extreme Regions) code, which uses three different machine learning techniques to classify galaxies in, and around, clusters, according to their projected phase-space position. We…

Quickly growing computing facilities and an increasing number of extragalactic observations encourage the application of data-driven approaches to uncover hidden relations from astronomical data. In this work we raise the problem of…

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 present a catalog of visual like H-band morphologies of $\sim50.000$ galaxies ($H_{f160w}<24.5$) in the 5 CANDELS fields (GOODS-N, GOODS-S, UDS, EGS and COSMOS). Morphologies are estimated with Convolutional Neural Networks (ConvNets).…

Next-generation radio surveys will yield an unprecedented amount of data, warranting analysis by use of machine learning techniques. Convolutional neural networks are the deep learning technique that has proven to be the most successful in…

We follow the evolution of the galaxy population in a Lambda-CDM cosmology by means of high-resolution N-body simulations in which the formation of galaxies and their observable properties are calculated using a semi-analytic model. We…

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…

We determine the concentration-mass relation of 19 X-ray selected galaxy clusters from the CLASH survey in theories of gravity that directly modify the lensing potential. We model the clusters as NFW haloes and fit their lensing signal, in…

We describe and test a method to quantitatively classify clusters of galaxies according to their projected morphologies. This method will be subsequently used to place constraints on cosmological parameters ($\Omega$ and the power spectrum…

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…