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Related papers: Galaxy Zoo: Morphologies based on UKIDSS NIR Imagi…

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Methods. We used different galaxy classification techniques: human labeling, multi-photometry diagrams, Naive Bayes, Logistic Regression, Support Vector Machine, Random Forest, k-Nearest Neighbors, and k-fold validation. Results. We present…

Astrophysics of Galaxies · Physics 2021-06-09 I. B. Vavilova , D. V. Dobrycheva , M. Yu. Vasylenko , A. A. Elyiv , O. V. Melnyk , V. Khramtsov

The DEEP2 project will obtain redshifts for ~60,000 galaxies between z~0.7-1.5 in a comoving volume of 7 10^6 Mpc/h^3 for an LCDM universe. The survey will map four separate 2 by 0.5 degree strips of the sky. To study the expected…

Astrophysics · Physics 2009-11-07 Alison L. Coil , Marc Davis , Istvan Szapudi

By applying our previously developed two-step scheme for galaxy morphology classification, we present a catalog of galaxy morphology for H-band selected massive galaxies in the COSMOS-DASH field, which includes 17292 galaxies with stellar…

Astrophysics of Galaxies · Physics 2023-07-07 Yao Dai , Jun Xu , Jie Song , Guanwen Fang , Chichun Zhou , Shuo Ba , Yizhou Gu , Zesen Lin , Xu Kong

We present the results of an imaging programme of distant galaxies (z~0.8) at high spatial resolution (~0.1").We observed 7 fields of 1'*1' with the NACO Adaptive Optics system (VLT) in Ks (2.16um) band with typical V ~ 14 guide stars and…

Astrophysics · Physics 2010-11-11 M. Huertas-Company , D. Rouan , G. Soucail , O. Le Fèvre , L. Tasca , T. Contini

There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a…

We revisit the evolution of galaxy morphology in the COSMOS field over the redshift range $0.2\leq z \leq 1$, using a large and complete sample of 33,605 galaxies with a stellar mass of log($M_{\ast}$/M$_{\odot} )>9.5$ with significantly…

Astrophysics of Galaxies · Physics 2023-09-29 Jian Ren , Nan Li , F. S. Liu , Qifan Cui , Mingxiang Fu , Xian Zhong Zheng

Following the study of Darg et al. (2009; hereafter D09a) we explore the environments, optical colours, stellar masses, star formation and AGN activity in a sample of 3003 pairs of merging galaxies drawn from the SDSS using visual…

We present morphological classifications obtained using machine learning for objects in SDSS DR6 that have been classified by Galaxy Zoo into three classes, namely early types, spirals and point sources/artifacts. An artificial neural…

We study a sample of 112 galaxies of various Hubble types imaged in the Two Micron All Sky Survey (2MASS) in the Near-Infra Red (NIR; 1-2 $\mu$m) $J$, $H$, and $K_s$ bands. The sample contains (optically classified) 32 elliptical, 16…

Astrophysics · Physics 2009-11-10 Nurur Rahman , Sergei F. Shandarin

We studied a sample of 38 intermediate redshift MgII absorption-selected galaxies using (1) Keck/HIRES and VLT/UVES quasar spectra to measure the halo gas kinematics from MgII absorption profiles and (2) HST/WFPC-2 images to study the…

Astrophysics · Physics 2009-11-11 Glenn G. Kacprzak , Christopher W. Churchill , Charles C. Steidel

We present a comprehensive set of mock 2dF and SDSS galaxy redshift surveys constructed from a set of large, high-resolution cosmological N-body simulations. The radial selection functions and geometrical limits of the catalogues mimic…

Astrophysics · Physics 2009-06-16 Shaun Cole , Steve Hatton , David H. Weinberg , Carlos S. Frenk

In recent decades, large-scale sky surveys such as Sloan Digital Sky Survey (SDSS) have resulted in generation of tremendous amount of data. The classification of this enormous amount of data by astronomers is time consuming. To simplify…

Instrumentation and Methods for Astrophysics · Physics 2022-11-02 Sarvesh Gharat , Yogesh Dandawate

The images of 229 galaxies in the Canada France Redshift Survey have been classified on the DDO system. These observations were combined with previous classifications of galaxies with known redshifts in the Hubble Deep Field. The combined…

Astrophysics · Physics 2009-11-06 Sidney van den Bergh

(Abridged) We compared the quantified morphological properties of 37 intermediate redshift MgII absorption selected galaxies to the properties of the absorbing halo gas, observed in the spectra of background quasars. The galaxy morphologies…

We investigate colour selection techniques for high redshift galaxies in the UKIDSS Ultra Deep Survey Early Data Release (UDS EDR). Combined with very deep Subaru optical photometry, the depth (K_AB = 22.5) and area (0.62 deg^2) of the UDS…

We re-examine the evidence for a violation of large-scale statistical isotropy in the distribution of projected spin vectors of spiral galaxies. We have a sample of $\sim 37,000$ spiral galaxies from the Sloan Digital Sky Survey, with their…

A galaxy group catalog is constructed from the 2MASS Redshift Survey (2MRS) with the use of a halo-based group finder. The halo mass associated with a group is estimated using a `GAP' method based on the luminosity of the central galaxy and…

Astrophysics of Galaxies · Physics 2016-11-23 Yi Lu , Xiaohu Yang , Feng Shi , H. J. Mo , Dylan Tweed , Huiyuan Wang , Youcai Zhang , Shijie Li , S. H. Lim

The challenge of consistent identification of internal structure in galaxies - in particular disc galaxy components like spiral arms, bars, and bulges - has hindered our ability to study the physical impact of such structure across large…

The DENIS survey is currently imaging the entire southern sky in the I, J, and K wavebands. The current star/galaxy separation algorithm is presented and the galaxy counts are nearly perfectly Euclidean. 95% complete and reliable galaxy…

Astrophysics · Physics 2007-05-23 Gary A. Mamon

We extend a recently developed galaxy morphology classification method, Quantitative Multiwavelength Morphology (QMM), to connect galaxy morphologies to their underlying physical properties. The traditional classification of galaxies…

Astrophysics of Galaxies · Physics 2015-05-18 D. B. Wijesinghe , A. M. Hopkins , B. C. Kelly , N. Welikala , A. J. Connolly