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Register a new userUVUDF: Ultraviolet Through Near-infrared Catalog and Photometric Redshifts of Galaxies in the Hubble Ultra Deep Field
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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.
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The catalog from the first high resolution U-band image of the Hubble Ultra Deep Field, taken with Hubbles Wide Field Planetary Camera 2 through the F300W filter, is presented. We detect 96 U-band objects and compare and combine this catalog with a Great Observatories Origins Deep Survey (GOODS) B-selected catalog that provides B, V, i, and z photometry, spectral types, and photometric redshifts. We have also obtained Far-Ultraviolet (FUV, 1614 AA) data with Hubbles Advanced Camera for Surveys Solar Blind Channel (ACS/SBC) and with Galaxy Evolution Explorer (GALEX). We detected 31 sources with ACS/SBC, 28 with GALEX/FUV, and 45 with GALEX/NUV. The methods of observations, image processing, object identification, catalog preparation, and catalog matching are presented.
We present deep $J$ and $H$-band images in the extended Great Observatories Origins Deep Survey-North (GOODS-N) field covering an area of 0.22 $rm{deg}^{2}$. The observations were taken using WIRCam on the 3.6-m Canada France Hawaii Telescope (CFHT). Together with the reprocessed $K_{rm s}$-band image, the $5sigma$ limiting AB magnitudes (in 2 diameter apertures) are 24.7, 24.2, and 24.4 AB mag in the $J$, $H$, and $K_{rm s}$ bands, respectively. We also release a multi-band photometry and photometric redshift catalog containing 93598 sources. For non-X-ray sources, we obtained a photometric redshift accuracy $sigma_{mathrm{NMAD}}=0.036$ with an outlier fraction $eta = 7.3%$. For X-ray sources, which are mainly active galactic nuclei (AGNs), we cross-matched our catalog with the updated 2M-CDFN X-ray catalog from Xue et al. (2016) and found that 658 out of 683 X-ray sources have counterparts. $GALEX$ UV data are included in the photometric redshift computation for the X-ray sources to give $sigma_{mathrm{NMAD}} = 0.040$ with $eta=10.5%$. Our approach yields more accurate photometric redshift estimates compared to previous works in this field. In particular, by adopting AGN-galaxy hybrid templates, our approach delivers photometric redshifts for the X-ray counterparts with fewer outliers compared to the 3D-HST catalog, which fit these sources with galaxy-only templates.
We derive photometric redshifts (zp) for sources in the entire ($sim0.4$ deg$^2$) Hawaii-Hubble Deep Field-North (hdfn) field with the EAzY code, based on point spread function-matched photometry of 15 broad bands from the ultraviolet (bandu~band) to mid-infrared (IRAC 4.5 $mu$m). Our catalog consists of a total of 131,678 sources. We evaluate the zp~quality by comparing zp~with spectroscopic redshifts (zs) when available, and find a value of normalized median absolute deviation sigm$=$0.029 and an outlier fraction of 5.5% (outliers are defined as sources having $rm |zp - zs|/(1+zs) > 0.15$) for non-X-ray sources. More specifically, we obtain sigm$=0.024$ with 2.7% outliers for sources brighter than $R=23$~mag, sigm$=0.035$ with 7.4% outliers for sources fainter than $R=23$~mag, sigm$=$0.026 with 3.9% outliers for sources having $z<1$, and sigm$=$0.034 with 9.0% outliers for sources having $z>1$. Our zp quality shows an overall improvement over an earlier zp work that focused only on the central hdfn area. We also classify each object as star or galaxy through template spectral energy distribution fitting and complementary morphological parametrization, resulting in 4959 stars and 126,719 galaxies. Furthermore, we match our catalog with the 2~Ms {it Chandra} Deep Field-North main xray~catalog. For the 462 matched non-stellar xray~sources (281 having zs), we improve their zp~quality by adding three additional AGN templates, achieving sigm$=0.035$ and an outlier fraction of 12.5%. We make our catalog publicly available presenting both photometry and zp, and provide guidance on how to make use of our catalog.
We present a robust method to estimate the redshift of galaxies using Pan-STARRS1 photometric data. Our method is an adaptation of the one proposed by Beck et al. (2016) for the SDSS Data Release 12. It uses a training set of 2313724 galaxies for which the spectroscopic redshift is obtained from SDSS, and magnitudes and colours are obtained from the Pan-STARRS1 Data Release 2 survey. The photometric redshift of a galaxy is then estimated by means of a local linear regression in a 5-dimensional magnitude and colour space. Our method achieves an average bias of $overline{Delta z_{rm norm}}=-2.01 times 10^{-4}$, a standard deviation of $sigma(Delta z_{rm norm})=0.0298$, and an outlier rate of $P_o=4.32%$ when cross-validating on the training set. Even though the relation between each of the Pan-STARRS1 colours and the spectroscopic redshifts is noisier than for SDSS colours, the results obtained by our method are very close to those yielded by SDSS data. The proposed method has the additional advantage of allowing the estimation of photometric redshifts on a larger portion of the sky ($sim 3/4$ vs $sim 1/3$). The training set and the code implementing this method are publicly available at www.testaddress.com.
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