Candels Multiwavelength Catalogs: Source Identification And
                    Photometry in the Candels Ukidss Ultra-Deep Survey Field

Galametz, A.; Grazian, A.; Fontana, A.; Ferguson, Henry C.; Ashby, M. L. N.; Barro, Guillermo; Castellano, M.; Dahlén, T.; Donley, J. L.; Faber, S. M.; Grogin, Norman A.; Guo, Y.; Huang, Kuang-Han; Kocevski, Dale D.; Koekemoer, Anton M.; Lee, Kyoung-Soo; McGrath, Elizabeth J.; Peth, Michael; Willner, S. P.; Almaini, O.; Cooper, Michael C.; Cooray, Asantha; Conselice, Christopher J.; Dickinson, Mark; Dunlop, James; Fazio, G. G.; Foucaud, S.; Gardner, Jonathan P.; Giavalisco, Mauro; Hathi, N. P.; Hartley, W. G.; Koo, David C.; Lai, Kamson; Mello, D. F. de; McLure, R. J.; Lucas, Ray A.; Paris, D.; Pentericci, L.; Santini, P.; Simpson, Chris; Sommariva, V.; Targett, T. A.; Weiner, Benjamin J.; Wuyts, Stijn

doi:10.1088/0067-0049/206/2/10

Cited by 286 publications

(367 citation statements)

References 52 publications

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“…First, we used SExtractor (Bertin et al 1996) on the processed H160 image with a revised HOT+COLD approach (Galametz et al 2013;Guo et al 2013). We then added the additional objects detected in a median average of the Y105+ J125+ JH140+ H160 bands, which are undetected in the H band.…”

Section: Detection Catalogue and Hst Photometrymentioning

confidence: 99%

“…In order to minimize this effect, we dilated the SExtractor output map with the same procedure described in Galametz et al (2013) before feeding this map to T-PHOT, thereby enlarging the size of the segmented area of each source by a given factor, depending on the original area. We then prepared the measurement image by applying, to the rms and background, a corrective factor via injection of fake PSF-shaped sources in about 200 positions in empty regions without detected sources.…”

Section: K and Irac Photometry With T-photmentioning

confidence: 99%

“…The magnified number counts are shown in Fig. 7 compared with total number counts from CANDELS GOODS-South (Guo et al 2013) and UDS (Galametz et al 2013) surveys normalized to FF area. For magnitudes brighter then H160 = 26 mag, the number counts are consistent with the CANDELS counts once magnification is taken into account and when sources with z phot within 0.1 the redshift of the relative cluster are removed.…”

Section: Demagnified Number Counts and Rest-frame Physical Propertiesmentioning

confidence: 99%

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The ASTRODEEP Frontier Fields catalogues

Criscienzo

Merlin

Castellano

et al. 2017

A&A

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Aims. We present the multiwavelength photometry of two Frontier Fields massive galaxy clusters, MACS-J0717 and MACS-J1149, and their parallel fields, ranging from Hubble Space Telescope (HST) to ground-based K and Spitzer IRAC bands, and the public release of photometric redshifts and rest-frame properties of galaxies found in cluster and parallel pointings. This work was carried out within the ASTRODEEP project and aims to provide a reference for future investigations of extragalactic populations. Methods. To fully exploit the depth of the images and detect faint sources, we used an accurate procedure, which carefully removes the foreground light of bright cluster sources and the intra-cluster light thus enabling detection and measurement of accurate fluxes in crowded cluster regions. This same procedure has been successfully used to derive the photometric catalogue of MACS-J0416 and Abell-2744. Results. The obtained multiband photometry was used to derive photometric redshifts, magnification, and physical properties of sources. In line with the first two FF catalogues released by ASTRODEEP, the photometric redshifts reach ∼4% accuracy. Moreover we extend the presently available samples to galaxies intrinsically as faint as H160 ∼ 32-34 mag thanks to the magnification factors induced by strong gravitational lensing. Our analysis allows us to probe galaxy masses larger than 10 7 M and/or SFR = 0.1-1 M /yr out to redshift z > 6.

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Section: Detection Catalogue and Hst Photometrymentioning

confidence: 99%

Section: K and Irac Photometry With T-photmentioning

confidence: 99%

Section: Demagnified Number Counts and Rest-frame Physical Propertiesmentioning

confidence: 99%

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The ASTRODEEP Frontier Fields catalogues

Criscienzo

Merlin

Castellano

et al. 2017

A&A

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“…The CANDELS data span five different fields and in this work we use data from all five: COS- et al, in prep. ), and UDS (Galametz et al 2013) (see these references for details about data processing and catalog creation for each of the CANDELS fields.) With this multiwavelength data we are able to study the star formation properties and structure of galaxies out to z ∼ 2.5 at high resolution.…”

Section: High Redshift: Candelsmentioning

confidence: 99%

The relationship between star formation activity and galaxy structural properties in CANDELS and a semi-analytic model

Brennan

Pandya

Somerville

et al. 2016

Mon. Not. R. Astron. Soc.

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We study the correlation of galaxy structural properties with their location relative to the SFR-M * correlation, also known as the star formation "main sequence" (SFMS), in the CANDELS and GAMA surveys and in a semi-analytic model (SAM) of galaxy formation. We first study the distribution of median Sérsic index, effective radius, star formation rate (SFR) density and stellar mass density in the SFR-M * plane. We then define a redshift dependent main sequence and examine the medians of these quantities as a function of distance from this main sequence, both above (higher SFRs) and below (lower SFRs). Finally, we examine the distributions of distance from the main sequence in bins of these quantities. We find strong correlations between all of these galaxy structural properties and the distance from the SFMS, such that as we move from galaxies above the SFMS to those below it, we see a nearly monotonic trend towards higher median Sérsic index, smaller radius, lower SFR density, and higher stellar density. In the semi-analytic model, bulge growth is driven by mergers and disk instabilities, and is accompanied by the growth of a supermassive black hole which can regulate or quench star formation via Active Galactic Nucleus (AGN) feedback. We find that our model qualitatively reproduces the trends described above, supporting a picture in which black holes and bulges co-evolve, and AGN feedback plays a critical role in moving galaxies off of the SFMS.

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“…Such accuracy has been obtained both in the work from Dieleman, Willett, & Dambre (2015) using data from the Galaxy Zoo project and at high redshift in Huertas-Company et al (2015) for CANDELS fields (Galametz et al 2013) galaxies. Two-dimensional profile fitting is often used to measure the properties of galaxies .…”

Section: Introductionmentioning

confidence: 78%

Deep learning for studies of galaxy morphology

et al. 2016

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Abstract. Establishing accurate morphological measurements of galaxies in a reasonable amount of time for future big-data surveys such as EUCLID, the Large Synoptic Survey Telescope or the Wide Field Infrared Survey Telescope is a challenge. Because of its high level of abstraction with little human intervention, deep learning appears to be a promising approach. Deep learning is a rapidly growing discipline that models high-level patterns in data as complex multilayered networks. In this work we test the ability of deep convolutional networks to provide parametric properties of Hubble Space Telescope like galaxies (half-light radii, Sérsic indices, total flux etc..). We simulate a set of galaxies including point spread function and realistic noise from the CANDELS survey and try to recover the main galaxy parameters using deep-learning. We compare the results with the ones obtained with the commonly used profile fitting based software GALFIT. This way showing that with our method we obtain results at least equally good as the ones obtained with GALFIT but, once trained, with a factor 5 hundred time faster.

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Candels Multiwavelength Catalogs: Source Identification And Photometry in the Candels Ukidss Ultra-Deep Survey Field

Abstract: We present the multiwavelength -ultraviolet to mid-infrared

Cited by 286 publications

References 52 publications

The ASTRODEEP Frontier Fields catalogues

The ASTRODEEP Frontier Fields catalogues

The relationship between star formation activity and galaxy structural properties in CANDELS and a semi-analytic model

Deep learning for studies of galaxy morphology

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