GMASS ultradeep spectroscopy of galaxies at<i>z</i> ~  2

Kurk, J. D.; Cimatti, A.; Daddi, E.; Mignoli, M.; Pozzetti, L.; Dickinson, Mark; Bolzonella, M.; Zamorani, G.; Cassata, P.; Rodighiero, G.; Franceschini, A.; Renzini, A.; Rosati, P.; Halliday, C.; Berta, S.

doi:10.1051/0004-6361/201117847

Cited by 111 publications

(106 citation statements)

References 108 publications

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“…Our first galaxy sample contains 2422 galaxies with secure spectroscopic redshifts (z spec ) from the ESO public compilation in the Chandra Deep Field South (CDFS; Cristiani et al 2000;Croom et al 2001;Bunker et al 2003;Dickinson et al 2004;Stanway et al 2004aStanway et al , 2004bStrolger et al 2004;Szokoly et al 2004;van der Wel et al 2004;Doherty et al 2005;Le Fèvre et al 2005;Mignoli et al 2005;Ravikumar et al 2007;Popesso et al 2009;Balestra et al 2010;Silverman et al 2010;Kurk et al 2013;Vanzella et al 2014) and from Morris et al (2015). In order to obtain multiwavelength photometry for these galaxies, we cross-matched this sample with the public Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS; Grogin et al 2011;Koekemoer et al 2011) catalog for the Great Observatory Origins Deep Survey South field (GOODS-S) obtained by Guo et al (2013).…”

Section: Samplementioning

confidence: 99%

The Impact of JWST Broadband Filter Choice on Photometric Redshift Estimation

Bisigello

Caputi

Colina

et al. 2016

ApJS

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The determination of galaxy redshifts in the James Webb Space Telescope's (JWST) blank-field surveys will mostly rely on photometric estimates, based on the data provided by JWST's Near-Infrared Camera (NIRCam) at 0.6-5.0 μm and Mid Infrared Instrument (MIRI) at l m > 5.0 m. In this work we analyze the impact of choosing different combinations of NIRCam and MIRI broadband filters (F070W to F770W), as well as having ancillary data at l m < 0.6 m, on the derived photometric redshifts (z phot ) of a total of 5921 real and simulated galaxies, with known input redshifts z=0-10. We found that observations at l m < 0.6 m are necessary to control the contamination of high-z samples by low-z interlopers. Adding MIRI (F560W and F770W) photometry to the NIRCam data mitigates the absence of ancillary observations at l m < 0.6 m and improves the redshift estimation. At z=7-10, accurate z phot can be obtained with the NIRCam broadbands alone when  S N 10, but the z phot quality significantly degrades at  S N 5. Adding MIRI photometry with 1 mag brighter depth than the NIRCam depth allows for a redshift recovery of 83%-99%, depending on spectral energy distribution type, and its effect is particularly noteworthy for galaxies with nebular emission. The vast majority of NIRCam galaxies with [F150W]=29AB mag at z=7-10 will be detected with MIRI at [F560W, F770W] < 28 mag if these sources are at least mildly evolved or have spectra with emission lines boosting the mid-infrared fluxes.

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Section: Samplementioning

confidence: 99%

The Impact of JWST Broadband Filter Choice on Photometric Redshift Estimation

Bisigello

Caputi

Colina

et al. 2016

ApJS

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“…To search for more redshifts and updates, we checked spectroscopic redshifts in recent works (Cooper et al 2011;Coppin et al 2012;Kurk et al 2013). Finally, in four cases, redshifts have been estimated by the clear presence of an iron emission line (Iwasawa et al 2012;Georgantopoulos et al 2013).…”

Section: Chandra and Optical Identification And Redshiftsmentioning

confidence: 99%

The XMM deep survey in the CDF-S

Ranalli¹,

Comastri²,

Vignali³

et al. 2013

A&A

128

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Nuclear obscuration plays a key role in the initial phases of AGN growth, yet not many highly obscured active galactic nuclei (AGN) are currently known beyond the local Universe, and their search is an active topic of research. The XMM-Newton survey in the Chandra Deep Field South (XMM-CDFS) aims at detecting and studying the spectral properties of a significant number of obscured and Compton-thick (N H > ∼ 10 24 cm −2 ) AGN. The large effective area of XMM-Newton in the 2-10 and 5-10 keV bands, coupled with a 3.45 Ms nominal exposure time (2.82 and 2.45 Ms after light curve cleaning for MOS and PN, respectively), allows us to build clean samples in both bands, and makes the XMM-CDFS the deepest XMM-Newton survey currently published in the 5-10 keV band. The large multi-wavelength and spectroscopic coverage of the CDFS area allows for an immediate and abundant scientific return. In this paper, we present the data reduction of the XMM-CDFS observations, the method for source detection in the 2-10 and 5-10 keV bands, and the resulting catalogues. A number of 339 and 137 sources are listed in the above bands with flux limits of 6.6 × 10 −16 and 9.5× 10 −16 erg s −1 cm −2 , respectively. The flux limits at 50% of the maximum sky coverage are 1.8× 10 −15 and 4.0× 10 −15 erg s −1 cm −2 , respectively. The catalogues have been cross-correlated with the Chandra ones: 315 and 130 identifications have been found with a likelihood-ratio method, respectively. A number of 15 new sources, previously undetected by Chandra, is found; 5 of them lie in the 4 Ms area. Redshifts, either spectroscopic or photometric, are available for ∼95% of the sources. The number counts in both bands are presented and compared to other works. The survey coverage has been calculated with the help of two extensive sets of simulations, one set per band. The simulations have been produced with a newly-developed simulator, written with the aim of the most careful reproduction of the background spatial properties. For this reason, we present a detailed decomposition of the XMM-Newton background into its components: cosmic, particle, and residual soft protons. The three components have different spatial distributions. The importance of these three components depends on the band and on the camera; the particle background is the most important one (80-90% of the background counts), followed by the soft protons (4-20%).

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“…Its wavelength coverage is exceptional, combining photometric observations from the UV to the IR 1 and spectral surveys to measure as many redshifts as possible (Kurk et al 2013, and reference therein). We select galaxies in this field with accurate measurements of the UV, visible, NIR, and IR rest frame emissions.…”

Section: Observations and Sample Usedmentioning

confidence: 99%

Ultraviolet to infrared emission ofz> 1 galaxies: Can we derive reliable star formation rates and stellar masses?

Buat

Heinis

Boquien

et al. 2013

A&A

115

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Aims. Our knowledge of the cosmic mass assembly relies on measurements of star formation rates (SFRs) and stellar masses (M star ), of galaxies as a function of redshift. These parameters must be estimated in a consistent way with a good knowledge of systematics before studying their correlation and the variation of the specific SFR. Constraining these fundamental properties of galaxies across the Universe is of utmost importance if we want to understand galaxy formation and evolution. Methods. We seek to derive SFRs and stellar masses in distant galaxies and to quantify the main uncertainties affecting their measurement. We explore the impact of the assumptions made in their derivation with standard calibrations or through a fitting process, as well as the impact of the available data, focusing on the role of infrared emission originating from dust. Results. We build a sample of galaxies with z > 1, all observed from the ultraviolet to the infrared in their rest frame. The data are fitted with the code CIGALE, which is also used to build and analyse a catalogue of mock galaxies. Models with different star formation histories are introduced: an exponentially decreasing or increasing SFR and a more complex one coupling a decreasing SFR with a younger burst of constant star formation. We define different sets of data, with or without a good sampling of the ultraviolet range, near-infrared, and thermal infrared data. Variations of the metallicity are also investigated. The impact of these different cases on the determination of stellar mass and SFR are analysed. Conclusions. Exponentially decreasing models with a redshift formation of the stellar population z f 8 cannot fit the data correctly. All the other models fit the data correctly at the price of unrealistically young ages when the age of the single stellar population is taken to be a free parameter, especially for the exponentially decreasing models. The best fits are obtained with two stellar populations. As long as one measurement of the dust emission continuum is available, SFR are robustly estimated whatever the chosen model is, including standard recipes. The stellar mass measurement is more subject to uncertainty, depending on the chosen model and the presence of near-infrared data, with an impact on the SFR-M star scatter plot. Conversely, when thermal infrared data from dust emission are missing, the uncertainty on SFR measurements largely exceeds that of stellar mass. Among all physical properties investigated here, the stellar ages are found to be the most difficult to constrain and this uncertainty acts as a second parameter in SFR measurements and as the most important parameter for stellar mass measurements.

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GMASS ultradeep spectroscopy of galaxies atz ~ 2

Cited by 111 publications

References 108 publications

The Impact of JWST Broadband Filter Choice on Photometric Redshift Estimation

The Impact of JWST Broadband Filter Choice on Photometric Redshift Estimation

The XMM deep survey in the CDF-S

Ultraviolet to infrared emission ofz> 1 galaxies: Can we derive reliable star formation rates and stellar masses?

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