ner_tags: O O O O B-Wavelength O O O B-Wavelength O O O O O O O O O O O O B-Dataset I-Dataset I-Dataset I-Dataset O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O B-Dataset I-Dataset I-Dataset O O O B-Wavelength O B-Wavelength O O O O O O O B-Instrument B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O B-CelestialRegion I-CelestialRegion O O O O O O O O O O O B-Wavelength I-Wavelength O O O B-Survey O B-Survey I-Survey O O B-Survey O O O O O B-Model O O O O O O O O O O O O O O O B-Wavelength O B-Survey O O O O O B-Wavelength I-Wavelength O O B-Survey O O O O O O B-Survey I-Survey O O O O O O O O O O O O O O O O O O O O O O O B-Survey O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Survey O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Survey B-Wavelength O O O O O O B-Survey I-Survey O O O O O B-Survey I-Survey O B-Survey O O O O O O B-Survey O O O O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O B-Dataset I-Dataset I-Dataset O O O O O O O O O O O O O B-Dataset I-Dataset I-Dataset I-Dataset O O O O O O O B-Model O O O B-CelestialRegion O O O O B-Wavelength I-Wavelength O O O O O O O O O O B-Survey O B-Survey I-Survey O O B-Survey O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O B-Survey O O B-Survey I-Survey O O O O O O O O O O O O O O O O O O O O O O O O O B-Dataset I-Dataset I-Dataset O O O O O O B-CelestialRegion B-CelestialRegion I-CelestialRegion B-CelestialRegion B-CelestialRegion O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O
tokens: either the use _ f160w or use _ f850lp flags, as noted in each subsequent case. We further compare to the CANDELS GOODS-S photometric catalog released by Guo et al. ( 2013 ), adopting flags equal to zero for non-contaminated sources. The CANDELS GOODS-S catalog presents the multiwavelength (UV to mid-IR) photometry, with source detection performed in the WFC3 H F160W mosaic using a “hot” and “cold” detection methodology. We first present the number counts in Section 3.1 and then cross-match all catalogs within a 05 radius to compare aperture photometry in Section 3.2 . Finally, in Section 3.3 , we show several example SEDs to showcase the high quality of the photometry. 3.1. Number Counts The number densities of galaxies that satisfy the use _ f160w criterion in the GOODS-S field are shown in Figure 13 as a function of the total H F160W magnitude for both HLF (black), 3D- HST (red), and CANDELS (blue). The error bars are Poisson. Though completely independent data reductions, the three data sets are fairly similar in terms of F160W coverage; HLF covers 207 arcmin 2 in H F160W , whereas CANDELS covers 173 arcmin 2 , and 3D- HST covers 171 arcmin 2 . It is therefore not surprising that the number counts are consistent. The deficit of sources with ABmag in CANDELS relative to the two other fields is likely the result of using a deeper multi-band combined detection image. The further excess of objects at the faint end in HLF results from a combination of effects. In part, this population of faint sources will arise due to the more aggressive source detection settings adopted. But in some cases, it is clear that the HLF F160W imaging is deeper than the earlier 3D- HST version (i.e., explaining why both 3D- HST and HLF have more faint number counts), but HLF appears to further reveal an exciting new population of extremely faint sources. Figure 14 shows 15 × 15 postage stamps (, , H F160W ) of 48 ultra-faint sources with magnitudes between 28 and 29 ABmag rank-ordered by S/N that are identified in the HLF photometric catalog but do not have a match within a radius of 04 in the 3D- HST photometric catalog. Figure 13. Number counts of galaxies with Poisson errors in the GOODS-S field as a function H F160W total magnitude, with no correction for incompleteness. The agreement between HLF (black), 3D- HST (red) and CANDELS (blue) is excellent. Figure 14. Example postage stamps (, , H F160W ) of 48 ultra-faint sources between 28 and 29 ABmag identified in HLF but not 3D- HST . The objects are rank-ordered by S/N, with the outline of the segmentation map shown as a white contour for reference. The depths in the HLF GOODS-S mosaic vary significantly within the field (i.e., HUDF, CANDELS deep, wide, ERS, etc.). Such a heterogeneous weight map implies that the single number count histogram shown in Figure 13 is simply the superposition of the histograms at different depths. In order to better understand the improvement, we separate the weight map into four