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Register a new userHubble Frontier Field Clusters and their Parallel Fields: Photometric and Photometric Redshift Catalogs
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We present a multi-band analysis of the six Hubble Frontier Field clusters and their parallel fields, producing catalogs with measurements of source photometry and photometric redshifts. We release these catalogs to the public along with maps of intracluster light and models for the brightest galaxies in each field. This rich data set covers a wavelength range from 0.2 to 8 $mu m$, utilizing data from the Hubble Space Telescope, Keck Observatories, Very Large Telescope array, and Spitzer Space Telescope. We validate our products by injecting into our fields and recovering a population of synthetic objects with similar characteristics as in real extragalactic surveys. The photometric catalogs contain a total of over 32,000 entries with 50% completeness at a threshold of $mathrm{mag_{AB}}sim 29.1$ for unblended sources, and $mathrm{mag_{AB}}sim 29$ for blended ones, in the IR-Weighted detection band. Photometric redshifts were obtained by means of template fitting and have an average outlier fraction of 10.3% and scatter $sigma = 0.067$ when compared to spectroscopic estimates. The software we devised, after being tested in the present work, will be applied to new data sets from ongoing and future surveys.
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The 3D-HST and CANDELS programs have provided WFC3 and ACS spectroscopy and photometry over ~900 square arcminutes in five fields: AEGIS, COSMOS, GOODS-North, GOODS-South, and the UKIDSS UDS field. All these fields have a wealth of publicly available imaging datasets in addition to the HST data, which makes it possible to construct the spectral energy distributions (SEDs) of objects over a wide wavelength range. In this paper we describe a photometric analysis of the CANDELS and 3D-HST HST imaging and the ancillary imaging data at wavelengths 0.3um to 8um. Objects were selected in the WFC3 near-IR bands, and their SEDs were determined by carefully taking the effects of the point spread function in each observation into account. A total of 147 distinct imaging datasets were used in the analysis. The photometry is made available in the form of six catalogs: one for each field, as well as a master catalog containing all objects in the entire survey. We also provide derived data products: photometric redshifts, determined with the EAZY code, and stellar population parameters determined with the FAST code. We make all the imaging data that were used in the analysis available, including our reductions of the WFC3 imaging in all five fields. 3D-HST is a spectroscopic survey with the WFC3 and ACS grisms, and the photometric catalogs presented here constitute a necessary first step in the analysis of these grism data. All the data presented in this paper are available through the 3D-HST website.
This paper presents multiwavelength photometric catalogues of the last two Hubble Frontier Fields (HFF), the massive galaxy clusters Abell 370 and RXC J2248.7-4431. The photometry ranges from imaging performed on the Hubble Space Telescope (HST) to ground based Very Large Telescope (VLT) and Spitzer/IRAC, in collaboration with the ASTRODEEP team, and using the ASTRODEEP pipeline. While the main purpose of this paper is to release the catalogues, we also perform, as a proof of concept, a brief analysis of z > 6 objects selected using drop-out method, as well as spectroscopically confirmed sources and multiple images in both clusters. While dropout methods yield a sample of high-z galaxies, the addition of longer wavelength data reveals that as expected the samples have substantial contamination at the ~30-45% level by dusty galaxies at lower redshifts. Furthermore, we show that spectroscopic redshifts are still required to unambiguously determine redshifts of multiply imaged systems. Finally, the now publicly available ASTRODEEP catalogues were combined for all HFFs and used to explore stellar properties of a large sample of 20,000 galaxies across a large photometric redshift range. The powerful magnification provided by the HFF clusters allows us an exploration of the properties of galaxies with intrinsic stellar masses as low as $M_* gtrsim 10^7M_{odot}$ and intrinsic star formation rates $mbox{SFRs}sim 0.1mbox{-}1M_odot/mbox yr$ at z > 6.
MiniJPAS is a ~1 deg^2 imaging survey of the AEGIS field in 60 bands, performed to demonstrate the scientific potential of the upcoming JPAS survey. Full coverage of the 3800-9100 AA range with 54 narrow and 6 broad optical filters allow for extremely accurate photo-z, which applied over 1000s of deg^2 will enable new applications of the photo-z technique such as measurement of baryonic acoustic oscillations. In this paper we describe the method used to obtain the photo-z included in the publicly available miniJPAS catalogue, and characterise the photo-z performance. We build 100 AA resolution photo-spectra from the PSF-corrected forced-aperture photometry. Systematic offsets in the photometry are corrected by applying magnitude shifts obtained through iterative fitting with stellar population synthesis models. We compute photo-z with a customised version of LePhare, using a set of templates optimised for the J-PAS filter-set. We analyse the accuracy of miniJPAS photo-z and their dependence on multiple quantities using a subsample of 5,266 galaxies with spectroscopic redshifts from SDSS and DEEP, that we find to be representative of the whole r<23 miniJPAS sample. Formal uncertainties for the photo-z that are calculated with the deltachi^2 method underestimate the actual redshift errors. The odds parameter has the stronger correlation with |Dz|, and accurately reproduces the probability of a redshift outlier (|Dz|>0.03) irrespective of the magnitude, redshift, or spectral type of the sources. We show that the two main summary statistics characterising the photo-z accuracy for a population of galaxies (snmad and eta) can be predicted by the distribution of odds in such population, and use this to estimate them for the whole miniJPAS sample. At r<23 there are 17,500 galaxies/deg^2 with valid photo-z estimates, of which 4,200 are expected to have |Dz|<0.003 (abridged).
We present photometry and derived redshifts from up to eleven bandpasses for 9927 galaxies in the Hubble Ultra Deep field (UDF), covering an observed wavelength range from the near-ultraviolet (NUV) to the near-infrared (NIR) with Hubble Space Telescope observations. Our Wide Field Camera 3 (WFC3)/UV F225W, F275W, and F336W image mosaics from the ultra-violet UDF (UVUDF) imaging campaign are newly calibrated to correct for charge transfer inefficiency, and use new dark calibrations to minimize background gradients and pattern noise. Our NIR WFC3/IR image mosaics combine the imaging from the UDF09 and UDF12 campaigns with CANDELS data to provide NIR coverage for the entire UDF field of view. We use aperture-matched point-spread function corrected photometry to measure photometric redshifts in the UDF, sampling both the Lyman break and Balmer break of galaxies at z~0.8-3.4, and one of the breaks over the rest of the redshift range. Our comparison of these results with a compilation of robust spectroscopic redshifts shows an improvement in the galaxy photometric redshifts by a factor of two in scatter and a factor three in outlier fraction over previous UDF catalogs. The inclusion of the new NUV data is responsible for a factor of two decrease in the outlier fraction compared to redshifts determined from only the optical and NIR data, and improves the scatter at z<0.5 and at z>2. The panchromatic coverage of the UDF from the NUV through the NIR yields robust photometric redshifts of the UDF, with the lowest outlier fraction available.
We introduce Z-Sequence, a novel empirical model that utilises photometric measurements of observed galaxies within a specified search radius to estimate the photometric redshift of galaxy clusters. Z-Sequence itself is composed of a machine learning ensemble based on the k-nearest neighbours algorithm. We implement an automated feature selection strategy that iteratively determines appropriate combinations of filters and colours to minimise photometric redshift prediction error. We intend for Z-Sequence to be a standalone technique but it can be combined with cluster finders that do not intrinsically predict redshift, such as our own DEEP-CEE. In this proof-of-concept study we train, fine-tune and test Z-Sequence on publicly available cluster catalogues derived from the Sloan Digital Sky Survey. We determine the photometric redshift prediction error of Z-Sequence via the median value of $|Delta z|/(1+z)$ (across a photometric redshift range of $0.05 le textit{z} le 0.6$) to be $sim0.01$ when applying a small search radius. The photometric redshift prediction error for test samples increases by 30-50 per cent when the search radius is enlarged, likely due to line-of-sight interloping galaxies. Eventually, we aim to apply Z-Sequence to upcoming imaging surveys such as the Legacy Survey of Space and Time to provide photometric redshift estimates for large samples of as yet undiscovered and distant clusters.
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