Related papers: Unsupervised classification of SDSS galaxy spectra

Galaxy morphology is a fundamental quantity, that is essential not only for the full spectrum of galaxy-evolution studies, but also for a plethora of science in observational cosmology. While a rich literature exists on…

We have observed 28 local galaxies in the wavelength range between 1 and 2.4 mic in order to define template spectra of the normal galaxies along the Hubble sequence. Five galaxies per morphological type were observed in most cases, and the…

We apply four statistical learning methods to a sample of $7941$ galaxies ($z<0.06$) from the Galaxy and Mass Assembly (GAMA) survey to test the feasibility of using automated algorithms to classify galaxies. Using $10$ features measured…

The two-step galaxy morphology classification framework {\tt USmorph} successfully combines unsupervised machine learning (UML) with supervised machine learning (SML) methods. To enhance the UML step, we employed a dual-encoder architecture…

We present a robust method to estimate the redshift of galaxies using Pan-STARRS1 photometric data. Our method is an adaptation of the one proposed by Beck et al. (2016) for the SDSS Data Release 12. It uses a training set of 2313724…

We combine Sloan Digital Sky Survey spectra of 22,000 luminous, red, bulge-dominated galaxies to get high S/N average spectra in the rest-frame optical and ultraviolet (2600A to 7000A). The average spectra of these massive, quiescent…

Accurate photometric redshifts are among the key requirements for precision weak lensing measurements. Both the large size of the Sloan Digital Sky Survey (SDSS) and the existence of large spectroscopic redshift samples that are…

With current and upcoming experiments such as WFIRST, Euclid and LSST, we can observe up to billions of galaxies. While such surveys cannot obtain spectra for all observed galaxies, they produce galaxy magnitudes in color filters. This data…

Abridged] We present here new results on the space density of rich, optically-selected, clusters of galaxies at low redshift (z<0.15). These results are based on the application of the matched filter cluster-finding algorithm to 1067 deg2…

Weak lensing surveys are emerging as an important tool for the construction of "mass selected" clusters of galaxies. We evaluate both the efficiency and completeness of a weak lensing selection by combining a dense, complete redshift…

Unsupervised feature selection (UFS) is an important task in data engineering. However, most UFS methods construct models from a single perspective and often fail to simultaneously evaluate feature importance and preserve their inherent…

The recently initiated SPHEREx and 7DS surveys will deliver low-resolution spectra ($R\approx 30-130$) for hundreds of millions of galaxies over the optical to near-infrared range ($0.4-5.0\mu m$), covering a wide sky area without sample…

Template fits to observed galaxy fluxes allow calculation of K-corrections and conversions among observations of galaxies at various wavelengths. We present a method for creating model-based template sets given a set of heterogeneous…

We present results from a spectroscopic study of ~4000 galaxies in a 6.2 square degree field in the direction of the Aquarius supercluster and a smaller typical field region in Cetus, down to R<19.5. Galaxy redshifts were measured using the…

There exist a variety of star-galaxy classification techniques, each with their own strengths and weaknesses. In this paper, we present a novel meta-classification framework that combines and fully exploits different techniques to produce a…

We explore the degrees of freedom required to jointly fit projected and redshift-space clustering of galaxies selected in three bins of stellar mass from the Sloan Digital Sky Survey Main Galaxy Sample (SDSS MGS) using a subhalo abundance…

We compile a sample of X-ray-selected galaxy groups and clusters from the XMM-Newton serendipitous source catalogue (2XMMi-DR3) with optical confirmation and redshift measurement from the Sloan Digital Sky Survey (SDSS). The X-ray cluster…

We built an optimal basis of low resolution templates for galaxies over the wavelength range from 0.2 to 10 $\mu$m using a variant of the algorithm presented by Budavari et al. (2000). We derived them using eleven bands of photometry from…

We present an application of unsupervised Machine Learning Clustering to the PAU Survey of galaxy spectral energy distribution (SED) within the COSMOS field. The clustering algorithm is implemented and optimized to get the relevant groups…

(abridged) We describe the automated spectral classification, redshift determination, and parameter measurement pipeline in use for the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III (SDSS-III) as of Data…