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Related papers: Exploring the Morphologies of High Redshift Galaxi…

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I review progress in understanding the evolution of normal field and cluster galaxies through the combination of HST imaging and ground-based spectroscopy. These data suggest that the bulk of the star formation producing the present-day…

Astrophysics · Physics 2007-05-23 Richard Ellis

This review discusses three ways in which radio galaxies and other high-redshift objects can give us information on the nature and statistics of cosmological inhomogeneities, and how they have evolved between high redshift and the present:…

Astrophysics · Physics 2007-05-23 J. A. Peacock

Galaxy morphology is a product of how galaxies formed, how they interacted with their environment, how they were influenced by internal perturbations, AGN, and dark matter, and of their varied star formation histories. This article reviews…

Cosmology and Nongalactic Astrophysics · Physics 2011-02-03 Ronald J. Buta

(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…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-20 Judy Y. Cheng , S. M. Faber , Luc Simard , Genevieve J. Graves , Eric D. Lopez , Renbin Yan , Michael C. Cooper

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…

Astrophysics of Galaxies · Physics 2023-03-01 M. S. Rosito , L. A. Bignone , P. B. Tissera , S. E. Pedrosa

Galaxy clusters are important cosmological probes that have helped to establish the $\mathrm{\Lambda}$CDM paradigm as the standard model of cosmology. However, recent tensions between different types of high-accuracy data highlight the need…

Cosmology and Nongalactic Astrophysics · Physics 2025-11-04 Nikolaos Triantafyllou , Giorgos Korkidis , Vasiliki Pavlidou , Paolo Bonfini

Classification of galaxy morphology is a challenging but meaningful task for the enormous amount of data produced by the next-generation telescope. By introducing the adaptive polar coordinate transformation, we develop a rotationally…

Astrophysics of Galaxies · Physics 2023-01-11 G. W. Fang , S. Ba , Y. Z. Gu , Z. S. Lin , Y. J. Hou , C. X. Qin , C. C. Zhou , J. Xu , Y. Dai , J. Song , X. Kong

The observed properties of galaxies are strongly dependent on both their total stellar mass and their morphology. Furthermore, the environment is known to play a strong role in shaping them. The galaxy population in the local universe that…

We have studied the evolution of galaxian morphologies from ground-based, good-seeing images of 9 clusters at z=0.09-0.25. The comparison of our data with those relative to higher redshift clusters (Dressler et al. 1997) allowed us to trace…

We discuss the state of the assembly of the Hubble Sequence in the mix of bright galaxies at redshift 1.4< z \le 2.5 with a large sample of 1,671 galaxies down to H_{AB}~26, selected from the HST/ACS and WFC3 images of the GOODS--South…

We describe application of the `shapelet' linear decomposition of galaxy images to morphological classification using images of $\sim$ 3000 galaxies from the Sloan Digital Sky Survey. After decomposing the galaxies we perform a principal…

Astrophysics · Physics 2009-11-10 Brandon C. Kelly , Timothy A. McKay

Machine learning (ML) is a standard approach for estimating the redshifts of galaxies when only photometric information is available. ML photo-z solutions have traditionally ignored the morphological information available in galaxy images…

Instrumentation and Methods for Astrophysics · Physics 2019-09-25 Kristen Menou

The evolution of our Universe is strongly influenced by the attractive force of gravity. A key aspect of this evolution, therefore, is the merging of galaxies. Here, we explore the role of mergers in shaping the properties of massive…

Astrophysics of Galaxies · Physics 2025-06-12 Sugata Kaviraj

We discuss a new method for inferring the stellar mass of a distant galaxy of known redshift based on the combination of a near-infrared luminosity and multi-band optical photometry. The typical uncertainty for field galaxies with I<22 in…

Astrophysics · Physics 2009-10-31 Jarle Brinchmann , Richard Ellis

Understanding the impact of halo properties beyond halo mass on the clustering of galaxies (namely galaxy assembly bias) remains a challenge for contemporary models of galaxy clustering. We explore the use of machine learning to predict the…

Cosmology and Nongalactic Astrophysics · Physics 2021-09-15 Xiaoju Xu , Saurabh Kumar , Idit Zehavi , Sergio Contreras

Recent extensive, multi-color deep surveys of galaxies open a possibility to get observational estimation of sizes for the largest structures in the Universe. Photometric redshift accuracy (about 0.03(1+z)) allows directly study clustering…

Astrophysics · Physics 2008-09-16 N. V. Nabokov , Yu. V. Baryshev

We study morphology and luminosity segregation of galaxies in loose groups. We analyze the two catalogs of groups which have been identified in the Nearby Optical Galaxy (NOG) sample, by means of hierarchical and percolation…

Astrophysics · Physics 2009-11-07 M. Girardi , E. Rigoni , F. Mardirossian , M. Mezzetti

Making mock simulated catalogs is an important component of astrophysical data analysis. Selection criteria for observed astronomical objects are often too complicated to be derived from first principles. However the existence of an…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-22 Amir Hajian , Marcelo Alvarez , J. Richard Bond

We investigate mass-dependent galaxy evolution based on a large sample of (more than 50,000) K-band selected galaxies in a multi-wavelength catalog of the Subaru/XMM-Newton Deep Survey (SXDS) and the UKIRT Infrared Deep Sky Survey…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-27 Junko Furusawa , Kazuhiro Sekiguchi , Tadafumi Takata , Hisanori Furusawa , Kazuhiro Shimasaku , Chris Simpson , Masayuki Akiyama
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