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Related papers: Multiband galaxy morphologies for CLASH: a convolu…

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We present accurate photometric redshifts for galaxies observed by the Cluster Lensing and Supernova survey with Hubble (CLASH). CLASH observed 25 massive galaxy cluster cores with the Hubble Space Telescope in 16 filters spanning 0.2 - 1.7…

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).…

The morphological diversity of galaxies is a relevant probe of galaxy evolution and cosmological structure formation, but the classification of galaxies in large sky surveys is becoming a significant challenge. We use data from the…

The Cluster Lensing And Supernovae survey with Hubble (CLASH) is an Hubble Space Telescope (HST) Multi-Cycle Treasury program observing 25 massive galaxy clusters. CLASH observations are carried out in 16 bands from UV to NIR to derive…

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 utilize 16 band Hubble Space Telescope (HST) observations of 18 lensing clusters obtained as part of the Cluster Lensing And Supernova survey with Hubble (CLASH) Multi-Cycle Treasury program to search for $z\sim6-8$ galaxies. We report…

We utilize the CLASH (Cluster Lensing And Supernova survey with Hubble) observations of 25 clusters to search for extreme emission-line galaxies (EELGs). The selections are carried out in two central bands: F105W (Y105) and F125W (J125), as…

Morphology is often used to infer the state of relaxation of galaxy clusters. The regularity, symmetry, and degree to which a cluster is centrally concentrated inform quantitative measures of cluster morphology. The Cluster Lensing and…

The next generation of data-intensive surveys are bound to produce a vast amount of data, which can be dealt with using machine-learning methods to explore possible correlations within the multi-dimensional parameter space. We explore the…

We examine the inner mass distribution of the relaxed galaxy cluster Abell 383 in deep 16-band HST/ACS+WFC3 imaging taken as part of the CLASH multi-cycle treasury program. Our program is designed to study the dark matter distribution in 25…

We present a new determination of the concentration-mass relation for galaxy clusters based on our comprehensive lensing analysis of 19 X-ray selected galaxy clusters from the Cluster Lensing and Supernova Survey with Hubble (CLASH). Our…

We present a strong lensing system in which a double source is imaged 5 times by 2 early-type galaxies. We take advantage in this target of the multi-band photometry obtained as part of the CLASH program, complemented by the spectroscopic…

Autonomous digital sky surveys such as Pan-STARRS have the ability to image a very large number of galactic and extra-galactic objects, and the large and complex nature of the image data reinforces the use of automation. Here we describe…

Astrophysics of Galaxies · Physics 2020-12-16 Hunter Goddard , Lior Shamir

Galaxy-scale strong lenses in galaxy clusters provide a unique tool to investigate their inner mass distribution and the sub-halo density profiles in the low-mass regime, which can be compared with the predictions from cosmological…

Cosmology and Nongalactic Astrophysics · Physics 2023-08-09 G. Angora , P. Rosati , M. Meneghetti , M. Brescia , A. Mercurio , C. Grillo , P. Bergamini , A. Acebron , G. Caminha , M. Nonino , L. Tortorelli , L. Bazzanini , E. Vanzella

Classifying the morphologies of galaxies is an important step in understanding their physical properties and evolutionary histories. The advent of large-scale surveys has hastened the need to develop techniques for automated morphological…

Astrophysics of Galaxies · Physics 2021-12-28 Mitchell K. Cavanagh , Kenji Bekki , Brent A. Groves

The Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) is designed to document the first third of galactic evolution, over the approximate redshift (z) range 8--1.5. It will image >250,000 distant galaxies using three…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-28 Norman A. Grogin , Dale D. Kocevski , S. M. Faber , Henry C. Ferguson , Anton M. Koekemoer , Adam G. Riess , Viviana Acquaviva , David M. Alexander , Omar Almaini , Matthew L. N. Ashby , Marco Barden , Eric F. Bell , Frédéric Bournaud , Thomas M. Brown , Karina I. Caputi , Stefano Casertano , Paolo Cassata , Marco Castellano , Peter Challis , Ranga-Ram Chary , Edmond Cheung , Michele Cirasuolo , Christopher J. Conselice , Asantha Roshan Cooray , Darren J. Croton , Emanuele Daddi , Tomas Dahlen , Romeel Davé , Duília F. de Mello , Avishai Dekel , Mark Dickinson , Timothy Dolch , Jennifer L. Donley , James S. Dunlop , Aaron A. Dutton , David Elbaz , Giovanni G. Fazio , Alexei V. Filippenko , Steven L. Finkelstein , Adriano Fontana , Jonathan P. Gardner , Peter M. Garnavich , Eric Gawiser , Mauro Giavalisco , Andrea Grazian , Yicheng Guo , Nimish P. Hathi , Boris Häussler , Philip F. Hopkins , Jia-Sheng Huang , Kuang-Han Huang , Saurabh W. Jha , Jeyhan S. Kartaltepe , Robert P. Kirshner , David C. Koo , Kamson Lai , Kyoung-Soo Lee , Weidong Li , Jennifer M. Lotz , Ray A. Lucas , Piero Madau , Patrick J. McCarthy , Elizabeth J. McGrath , Daniel H. McIntosh , Ross J. McLure , Bahram Mobasher , Leonidas A. Moustakas , Mark Mozena , Kirpal Nandra , Jeffrey A. Newman , Sami-Matias Niemi , Kai G. Noeske , Casey J. Papovich , Laura Pentericci , Alexandra Pope , Joel R. Primack , Abhijith Rajan , Swara Ravindranath , Naveen A. Reddy , Alvio Renzini , Hans-Walter Rix , Aday R. Robaina , Steven A. Rodney , David J. Rosario , Piero Rosati , Sara Salimbeni , Claudia Scarlata , Brian Siana , Luc Simard , Joseph Smidt , Rachel S. Somerville , Hyron Spinrad , Amber N. Straughn , Louis-Gregory Strolger , Olivia Telford , Harry I. Teplitz , Jonathan R. Trump , Arjen van der Wel , Carolin Villforth , Risa H. Wechsler , Benjamin J. Weiner , Tommy Wiklind , Vivienne Wild , Grant Wilson , Stijn Wuyts , Hao-Jing Yan , Min S. Yun

In order to obtain morphological information of unlabeled galaxies, we present an unsupervised machine-learning (UML) method for morphological classification of galaxies, which can be summarized as two aspects: (1) the methodology of…

Astrophysics of Galaxies · Physics 2022-02-02 C. C. Zhou , Y. Z. Gu , G. W. Fang , Z. S. Lin
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