Deep Hyper Suprime-Cam Images and a Forced Photometry Catalog in W-CDF-S

TL;DR

This paper presents a deep optical catalog of approximately 2 million objects in the W-CDF-S field using Hyper Suprime-Cam data, enhancing the multiwavelength dataset for studying faint, high-redshift objects.

Contribution

The authors provide a new, deep optical catalog in W-CDF-S with improved depth and coverage, complementing existing NIR data for better astrophysical investigations.

Findings

Catalog contains ~2 million objects.

Optical data reach depths of ~25.9 mag in g-band.

Coverage of ~5.7 square degrees.

Abstract

The Wide Chandra Deep Field-South (W-CDF-S) field is one of the SERVS fields with extensive multiwavelength datasets, which can provide insights into the nature and properties of objects in this field. However, the public optical data from DES ($grizy$ to $m\rm_{AB} \approx 21.4-24.3$) are not sufficiently deep to match well the NIR data from VIDEO ($ZYJHK_s$ to $m\rm_{AB} \approx 23.5-25.7$), which limits the investigation of fainter objects at higher redshifts. Here, we present an optical catalog of $\approx$ 2,000,000 objects in W-CDF-S utilizing archival Hyper Suprime-Cam observations in the $g,r,i,z$ bands covering $\approx5.7 \rm~deg^2$. The estimated depth is $\approx$ 25.9 for $g$-band, 25.6 for $r$-band, 25.8 for $i$-band, and 25.2 for $z$-band, which is deep enough to complement the NIR data, and will benefit AGN/galaxy studies in W-CDF-S in the future.

Full text

catalogs — surveys — galaxies: general — galaxies: active

1

The Wide Chandra Deep Field-South (W-CDF-S) region is a $\approx$ 4.5 deg2 field in the SERVS (Mauduit et al., 2012) CDF-S footprint. W-CDF-S has extensive multiwavelength coverage that is publicly available, such as ATLAS (Franzen et al., 2015) in the radio, HerMES (Oliver et al., 2012) in the FIR, SERVS and VIDEO (Jarvis et al., 2013) in the NIR, and DES (Abbott et al., 2018) in the optical. PRIMUS (Coil et al., 2011) also provides more than 30,000 spectroscopic redshifts in the field (see Table 1 of Chen et al. 2018 for more details). Furthermore, W-CDF-S will have $\approx$ 2.2 Ms of XMM-Newton coverage by 2020 covering the whole field, in addition to the archival X-ray coverage in the $\approx$ 0.3 deg2 CDF-S (Comastri et al., 2016; Xue et al., 2016; Luo et al., 2017). However, the current public optical data from DES (grizy to $m\rm_{AB}\approx 21.4-24.3$) do not delve as deep as the NIR data from VIDEO ($ZYJHK_{s}$ to $m\rm_{AB}\approx 23.5-25.7$). Thus, optical data at least as deep as the NIR data will benefit the investigation of fainter objects at higher redshifts.

Here, we present an optical catalog of archival Hyper Suprime-Cam (HSC; Miyazaki et al. 2012) observations in W-CDF-S. HSC is an optical digital camera attached to the Subaru Telescope. We obtained the publicly available raw image data in the g,r,i,z bands (taken between January 2015 and March 2017) and relevant calibration files via SMOKA.111https://smoka.nao.ac.jp The coverage of HSC is shown in Figure 1 along with some other key multiwavelength data in the W-CDF-S region. Observations in the g,i,z bands cover the full $\approx 5.7\rm~{}deg^{2}$ area shown in Figure 1, while observations in the $r$-band only cover the central $\approx 2.0\rm~{}deg^{2}$ region. These observations have exposure times close to the Deep fields in the HSC Subaru Strategic Program (Aihara et al., 2018).

We analyzed the HSC data with hscPipe v5.4 (Bosch et al., 2018), a version of the LSST Software Stack (Ivezić et al., 2008; Axelrod et al., 2010; Jurić et al., 2017), following the hscPipe user manual.222https://hsc.mtk.nao.ac.jp/pipedoc_5_e/ The pipeline first performs single-visit processing, which includes the subtraction of overscan, bias, and dark, and also flatfielding. Then, it calibrates the relative position and flux scale of each CCD against the PanSTARRS1 (PS1) PV3 catalog (Magnier et al., 2013). Utilizing the corrected position and flux scale, CCD images are warped and combined using a weighted average to reduce contamination. Sources are then detected and measured in the g,r,i,z bands separately, and a list of sources is generated by merging the object information from all the bands. Finally, forced photometry is performed in the four bands simultaneously with source positions and shape parameters fixed to the values of a well-detected reference band selected by hscPipe (see Bosch et al. 2018 for details).

We present the coadded images and the forced photometry catalog at10.5281/zenodo.2225161 (catalog 10.5281/zenodo.2225161). Corresponding weight maps and mask images are also provided, which contain information about the coadded image quality pixel by pixel. To use the catalog products, users should use the suggested flag cuts (e.g., Table 4 of Aihara et al. 2018) to select objects with clean photometry. We also created a flag_clean column to mark “clean” objects (the selection criteria are shown in the catalog schema).

We also provide a few diagnostic plots to demonstrate the astrometric and photometric quality of the catalog in the Appendix. In Figure S1, we show the number of sources as a function of the PSF magnitude in each band for “clean” objects. The estimated depth is $\approx$ 25.9 for g-band, 25.6 for r-band, 25.8 for i-band, and 25.2 for z-band. The depths as a function of the patch location are shown in Figure S2. Also, HSC-to-$Gaia$ (Gaia Collaboration, 2018) positional offsets are presented in Figure S3, demonstrating the astrometric quality of the HSC data products. Other diagnostic plots are also available.

Finally, we provide a preliminary match of the HSC sources to their infrared counterparts. We matched the “clean” HSC objects as well as detections in VIDEO to the SERVS source positions within 1*′′* to generate an optical-IR catalog of sources in W-CDF-S.

We note that the VOICE Survey (Vaccari et al., 2016) data will be released in the near future, which has $u,g,r,i$ bands down to $m\rm_{AB}\approx 25-26$ for a somewhat different 4 deg2 footprint. Also, the “Cosmic Dawn Survey” will provide deeper Spitzer (PI: P. Capak) and HSC (PIs: D. Sanders & P. Capak) coverage in W-CDF-S in the coming years.

We thank the anonymous PI of the HSC data products we used in W-CDF-S. We thank Yoshihiko Yamada at the hscPipe help desk, for assistance with hscPipe. We thank Ian Smail and Michael Strauss for helpful discussions.