The SSA22 H i Tomography Survey (SSA22-HIT). I. Data Set and Compiled Redshift Catalog

In this study, we focus on the ∼34 × 27 arcmin² region centered at the LAE density peak, referred to as the SSA22-Sb1 field (Hayashino et al. 2004; Yamada et al. 2012b; Mawatari et al. 2017). We use the following multiband imaging data: Canada–France–Hawaii Telescope/Megacam (Boulade et al. 2003) u*-band image (Kousai 2011); Subaru/Suprime-Cam (Miyazaki et al. 2002) B, V, R_c , $i^{\prime}$, $z^{\prime}$, NB359 (central wavelength λ_cen = 3596 Å and FWHM = 152 Å), NB497 (λ_cen = 4977 Å and FWHM = 78 Å), and NB816 (λ_cen = 8150 Å and FWHM = 118 Å) band images (Hayashino et al. 2004; Iwata et al. 2009; Nakamura et al. 2011; Yamada et al. 2012b); Subaru/Hyper Suprime-Cam (HSC; Miyazaki et al. 2012, 2018) Y-band image from the Subaru strategic program with HSC (HSC-SSP; Aihara et al. 2018; Furusawa et al. 2018; Kawanomoto et al. 2018; Komiyama et al. 2018; Miyazaki et al. 2018) in its internal data products (S14A0b) generated from raw data taken in 2014; Subaru/Multi-Objects Infra-Red Camera and Spectrograph (MOIRCS; Ichikawa et al. 2006) J-, H-, and K_s -band images (Uchimoto et al. 2012); and Spitzer/IRAC (Fazio et al. 2004) 3.6 μm and 4.5 μm band images. The entire SSA22-Sb1 field is covered by the above imaging data, except for the MOIRCS and IRAC data.

We also created a composite image of the B and V bands (hereafter, the BV image) as BV = (2B + V)/3 following Yamada et al. (2012b) to estimate the continuum flux at the NB497 wavelength. The Suprime-Cam NB816 raw images captured by Hu et al. (2004) were reduced by us using the pipeline "SDFRED" (Yagi et al. 2002; Ouchi et al. 2004). For the IRAC images, we collected raw images via the NASA/IPAC Infrared Science Archive and reduced them using a standard pipeline MOPEX. ²⁵ Since astrometric correction in the used images was applied independently by different authors, we again calibrated astrometry to that of the stars in the USNO-B1.0 catalog (Monet et al. 2003) using NOAO/IRAF. ²⁶ The resultant astrometric uncertainties are typically less than 1'', whereas the relative offsets among the different band images are much smaller.

Object extraction was performed on the $i^{\prime}$- and $z^{\prime}$-band images using SExtractor (Bertin & Arnouts 1996) version 2.5.0. We constructed multiband photometry catalogs for objects detected in the $i^{\prime}$ and $z^{\prime}$ bands, adopting 22 diameter apertures in all band photometry. In aperture photometry, the ${u}^{* },B,V,{R}_{c},i^{\prime} ,z^{\prime} ,Y,J,H$, and K_s -band images are smoothed such that their point-spread function (PSF) sizes are matched to the FWHM of 11. We also created another set of $i^{\prime}$- and $z^{\prime}$-band images smoothed to match their PSFs to those of the IRAC images (FWHM = 2''). We measured $i^{\prime} -[3.6]$, $i^{\prime} -[4.5]$, $z^{\prime} -[3.6]$, and $z^{\prime} -[4.5]$ colors on the FWHM = 2'' images using 22 diameter apertures. By adding these colors to the $i^{\prime}$ or $z^{\prime}$ band magnitudes measured on the FWHM = 11 images, we obtained the 3.6 and 4.5 μm magnitudes of all detected objects. These multiband photometric measurements were corrected for Galactic extinction based on Schlegel et al. (1998) with R_V = 3.1. Our multiband photometry catalog in the SSA22-Sb1 field is the same as the "SSA22HIT master catalog" used in Yamanaka et al. (2020).

We define five major categories for spectroscopic targets based on their expected redshifts (z_ex). Categories T1, T2, and T3 consist of galaxies at 2.7 < z_ex < 3.2, 3.2 < z_ex < 3.7, and 3.7 < z_ex < 4.5, respectively, which can be used as background light sources for the H i tomography at 2.5 ≲ z ≲ 4. In particular, we prioritize the T2 category, which provides us with the spectra probing the HI absorption in the z = 3.1 protocluster. Categories T4 and T5 are defined to be at 4.3 < z_ex < 4.8 and 4.8 < z_ex < 5.6, respectively, which are used to search for galaxy overdensity regions at higher redshifts.

We developed our own color criteria for these categories. They were more carefully designed than the commonly used dropout (e.g., Steidel et al. 1995; Giavalisco 2002) and BX (Steidel et al. 2004) selection criteria such that they were more sensitive to the specific redshift intervals of our target categories. The filters used in the color selection and model galaxy spectra (Bruzual & Charlot 2003; hereafter, BC03) with representative redshifts of the categories are shown in Figure 1. For BC03 model templates, we assumed a Chabrier initial mass function (Chabrier 2003) with a mass range of 0.1–100 M_⊙. For dust and IGM attenuation, we applied the Calzetti law (Calzetti et al. 2000) and the analytic model of Inoue et al. (2014), respectively. Figure 2 shows the color behaviors of the BC03 model galaxies, Galactic stars (Pickles 1998), and observed galaxies whose redshifts were spectroscopically confirmed by previous studies (Steidel et al. 2003; Kousai 2011; Saez et al. 2015; Hayashino et al. 2019). We determined the color criteria (gray shaded regions) described below to select the BC03 model galaxies with 10 < age [Myr] < 100 and E(B − V) ≲ 0.2.

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

For T1, we adopted

$$\begin{eqnarray}&&23.5\leqslant i^{\prime} \leqslant 25.5,\end{eqnarray} \tag{ 1 }$$

$$\begin{eqnarray}&&2.2({R}_{c}-z^{\prime} )+1\leqslant {u}^{* }-V\leqslant 2.2({R}_{c}-z^{\prime} )+1.6,\end{eqnarray} \tag{ 2 }$$

$$\begin{eqnarray}&&-0.8\leqslant {R}_{c}-z^{\prime} \leqslant 0.1,\end{eqnarray} \tag{ 3 }$$

$$\begin{eqnarray}&&-0.4\leqslant i^{\prime} -z^{\prime} \leqslant 0.1,\end{eqnarray} \tag{ 4 }$$

$$\begin{eqnarray}&&-1\leqslant V-z^{\prime} \leqslant 0.3.\end{eqnarray} \tag{ 5 }$$

The faint limit in the $i^{\prime}$-band magnitude was determined to collect sufficient background galaxies for H i tomography with a mapping resolution of several cMpc. We also set a bright limit in the $i^{\prime}$-band magnitude because many bright objects with $i^{\prime} \lt 23.5$ showed low-z contamination in our previous observations (Kousai 2011; Hayashino et al. 2019) using the visible multiobject spectrograph (VIMOS; Le Fèvre et al. 2003) on the VLT. Strict ${R}_{c}-z^{\prime}$, $i^{\prime} -z^{\prime}$, and $V-z^{\prime}$ criteria are required to avoid contamination from the galactic stars and low-z passive galaxies dominated by the matured stellar population (Figure 2) as well as possible artifacts such as satellite trails and stellar spikes that can make the colors extremely red or blue. Such magnitude and color constraints at wavelengths longer than the Lyman break were also adopted for the other categories.

For T2, we adopted

$$\begin{eqnarray}&&23.5\leqslant i^{\prime} \leqslant 25.5,\end{eqnarray} \tag{ 6 }$$

$$\begin{eqnarray}&&{u}^{* }-V\geqslant 1.2,\end{eqnarray} \tag{ 7 }$$

$$\begin{eqnarray}&&{u}^{* }-V\geqslant 2.2({R}_{c}-z^{\prime} )+1.6,\end{eqnarray} \tag{ 8 }$$

$$\begin{eqnarray}&&-0.8\leqslant {R}_{c}-z^{\prime} \leqslant 0.3,\end{eqnarray} \tag{ 9 }$$

$$\begin{eqnarray}&&-0.4\leqslant i^{\prime} -z^{\prime} \leqslant 0.15,\end{eqnarray} \tag{ 10 }$$

$$\begin{eqnarray}&&{BV}-{NB}497\leqslant 0.5,\end{eqnarray} \tag{ 11 }$$

where the BV − NB497 criterion was adopted to remove LAEs at z = 3.1. In the T1 and T2 target selections, we avoided imposing a criterion for a B-band depression compared to the longer-wavelength bands. For z ∼ 3 galaxies, the B band samples the wavelength range between the Lyα and Lyβ (Figure 1) where the foreground Lyα absorption is imprinted. Because the main aim of this work is to collect the background sight-lines for H i absorption analysis, we avoided introducing any bias in the B-band flux due to the foreground absorption.

For T3, we adopted

$$\begin{eqnarray}&&24\leqslant i^{\prime} \leqslant 25.5,\end{eqnarray} \tag{ 12 }$$

$$\begin{eqnarray}&&B-{R}_{c}\geqslant 0.8,\end{eqnarray} \tag{ 13 }$$

$$\begin{eqnarray}&&B-{R}_{c}\geqslant 4.3(i^{\prime} -z^{\prime} )+1.2,\end{eqnarray} \tag{ 14 }$$

$$\begin{eqnarray}&&-0.4\leqslant i^{\prime} -z^{\prime} \leqslant 0.2,\end{eqnarray} \tag{ 15 }$$

$$\begin{eqnarray}&&{u}^{* }\gt 26.9(2\sigma ),\end{eqnarray} \tag{ 16 }$$

$$\begin{eqnarray}&&{NB}359\gt 26.6(2.5\sigma ).\end{eqnarray} \tag{ 17 }$$

For T4, we adopted

$$\begin{eqnarray}&&24\leqslant z^{\prime} \leqslant 25.8,\end{eqnarray} \tag{ 18 }$$

$$\begin{eqnarray}&&V-z^{\prime} \geqslant 0.6,\end{eqnarray} \tag{ 19 }$$

$$\begin{eqnarray}&&V-z^{\prime} \geqslant 4.5(i^{\prime} -z^{\prime} )+1.1,\end{eqnarray} \tag{ 20 }$$

$$\begin{eqnarray}&&-0.4\leqslant i^{\prime} -z^{\prime} \leqslant 0.2,\end{eqnarray} \tag{ 21 }$$

$$\begin{eqnarray}&&B\gt 28.35(1.5\sigma ).\end{eqnarray} \tag{ 22 }$$

For T5, we adopted

$$\begin{eqnarray}&&z^{\prime} \leqslant 25.75,\end{eqnarray} \tag{ 23 }$$

$$\begin{eqnarray}&&{R}_{c}-z^{\prime} \geqslant 1.1,\end{eqnarray} \tag{ 24 }$$

$$\begin{eqnarray}&&{R}_{c}-z^{\prime} \geqslant 4.5({NB}816-z^{\prime} )+1.7,\end{eqnarray} \tag{ 25 }$$

$$\begin{eqnarray}&&{NB}816-z^{\prime} \leqslant 0.2,\end{eqnarray} \tag{ 26 }$$

$$\begin{eqnarray}&&B\gt 28.35(1.5\sigma ).\end{eqnarray} \tag{ 27 }$$

Note that the above criteria were slightly relaxed for a small number of objects so that we could effectively fill the spectroscopic slits. We made it possible to distinguish the objects selected by the relaxed color criteria in our published catalog (see Appendix B).

Galaxies that are brighter than 25.5 mag in the $i^{\prime}$ band and spectroscopically confirmed as z_spec > 3.2 in previous studies (Steidel et al. 2003; Kousai 2011; Saez et al. 2015; Hayashino et al. 2019; see also Section 4.2) were added to the T2 and T3 categories, which are referred to as T2prevz and T3prevz, respectively. Unless specified otherwise, the T2/T3 categories include the T2prevz/T3prevz subcategories throughout this paper. We also estimated the photometric redshifts (photo-z) for the $i^{\prime}$- or $z^{\prime}$-band detected objects using a public software "HYPERZ" (Bolzonella et al. 2000) to increase spectroscopic target candidates. In this photo-z estimation for the target selection, we did not use the three Subaru narrowband data. We used composite spectral templates of stellar components (BC03) and nebular emission lines (Inoue 2011), which are the same as those used in Mawatari et al. (2016b).

We used the DSIMULATOR ²⁷ software to design six DEIMOS slit masks (Mask01, 02, 03, 04, 05, and 06). The six masks were arranged within 26 × 15 arcmin² of the SSA22-Sb1 field, and they overlap in the central 7.7 × 15 arcmin² (Figure 3). We achieved a doubled surface density of the targets in the overlapped area where no target was shared among the different masks. We prioritized the categories as T2 and T3 with previously confirmed redshift (T2prevz and T3prevz) > T5 > T2 > T4 > T3 > T1, considering their number densities. We also prioritized the targets in each category in the following order: objects satisfying both the color criteria and the photo-z range, objects satisfying the color criteria, and objects satisfying only the photo-z range. Eventually, on average, 85 slits per mask were assigned, excluding alignment stars. Out of the total 513 slits, 8%, 58%, 12%, 7%, and 6% are in T1, T2, T3, T4, and T5, respectively.

Zoom In Zoom Out Reset image size

A small part of the slits were also assigned to the following interesting targets: candidate Lyman continuum leakers identified with NB359 (LyC; Iwata et al. 2009), SMGs detected with AzTEC and Atacama Large Millimeter/submillimeter Array (ALMA; Umehata et al. 2014, 2018), LAEs with the K_s -band detection indicating old stellar age (oldLAEs; Yamada et al. 2012b), LAEs lying within the LAEs low-density region (LDRLAEs; Yamada et al. 2012b), a damped Lyα system identified along a galaxy sight-line (galDLA; Mawatari et al. 2016a), and its counterpart candidates. We also assigned the remaining slits to protocluster members (PCs) that were brighter than 25.5 mag in the $i^{\prime}$ band and were spectroscopically confirmed as 3.04 ≤ z ≤ 3.12 in previous observations (Steidel et al. 2003; Kousai 2011; Saez et al. 2015; Hayashino et al. 2019; see also Section 4.2). The PC slits are limited to the 8 × 10 arcmin² area around the z = 3.1 LAE density peak, which roughly corresponds to the overlapped region by Mask03, Mask04, Mask05, and Mask06. We assigned these PC slits to perform high spatial resolution H i tomography at 2.5 ≲ z ≲ 3. The sky distributions of all of the targets for the spectroscopic observations are shown in Figure 3.

We performed spectroscopic observations of the targets described above with DEIMOS (Faber et al. 2003) on the Keck II telescope in 2015 and 2016 using S274D (PI: T. Yamada), U066D (PI: D. Schlegel), S313D (PI: T. Yamada), and S290D (PI: T. Yamada). We were awarded four full nights and 10 half nights in total. Because some nights were lost due to bad weather, the effective observation time corresponded to 41 h.

We used a 600ZD grating with a slit width of 1'', which yielded a spectral resolution of Δλ ∼ 4.7 Å or resolving power R ∼ 1000. The pixel scales along the wavelength and spatial directions are ∼0.62 Å pix⁻¹ and 01185 pix⁻¹, respectively. We chose the GG400 order blocking filter and set a central wavelength of 6300 Å or 6500 Å, which provided a wavelength coverage of 4000 Å ≲λ ≲ 9000 Å. The observed coordinates, number of slits, date, exposure time, and seeing are listed in Table 1. The raw data were classified by their slit masks and continuous observation dates (observing dates (observing "runs"). The data reduction of each slit mask and each observing run was performed separately (see Section 3 and Table 1).

Table 1. Summary of DEIMOS Observations in the SSA22 Field

	R.A. a (J2000)	Decl. a (J2000)	Ndata b	Dates c (UT)	Exposure Time (s)	Seeing d (arcsec)
Mask01	22h17m480	$+00^\circ 08^{\prime} 04\buildrel{\prime\prime}\over{.} 8$	92	2015 Oct 12	7200	0.9–1.0
Mask02	22h17m123	$+00^\circ 07^{\prime} 43\buildrel{\prime\prime}\over{.} 2$	84	2015 Oct 12	7200	0.9
Mask03	22h17m480	$+00^\circ 12^{\prime} 57\buildrel{\prime\prime}\over{.} 7$	89	2015 Oct 10	7200	0.7–0.8
				2016 Aug 3–4	19,230	0.7–1.3
				2016 Oct 9	1800	0.9
Mask04	22h17m12.3s	$+00^\circ 12^{\prime} 56\buildrel{\prime\prime}\over{.} 3$	92	2015 Oct 10	7200	0.6–0.8
				2016 Aug 1–3	21,600	0.7–1.3
Mask05	22h17m48.0s	$+00^\circ 17^{\prime} 59\buildrel{\prime\prime}\over{.} 4$	99	2015 Aug 16–17 e	3600	0.7–0.8
				2015 Sep 7	6579	0.7–0.9
				2015 Oct 13	3000	0.7–1.1
				2016 Jul 31–Aug 1	15,600	1.0–1.5
Mask06	22h17m12.3s	$+00^\circ 17^{\prime} 59\buildrel{\prime\prime}\over{.} 2$	91	2015 Aug 15–16 e	6868	0.7–1.2
				2015 Oct 10–13	9700	0.7–1.1
				2016 Jul 31	12,600	0.9–1.1
				2016 Oct 8–9	19,500	0.8–1.0

Notes.

^a The mask R.A. and decl. coordinates are defined as the geometrical center positions of the 167 × 5' fields of view. ^b The number of slits for which we actually obtained spectral data. Slits that are designed but fall into the CCD gap are not included in N_data, while slits for the alignment stars are included. ^c Wavelength and flux calibrations were performed for each data set of the continuous observing dates. ^d Seeing sizes were measured for raw spectra of the alignment stars at λ ∼ 5500 Å. ^e The background sky level was very high due to the cloudy conditions in 2015 August.

Download table as:  ASCIITypeset image

The DEIMOS standard procedure for flat and arc data is not optimal for our main science focusing on the H i Lyα absorptions at λ ≲ 5500 Å because of the low counts and limited number of arc lines at the blue wavelengths. Instead, we used two types of flat and arc data optimized for the red and blue wavelengths using the operational script "calib_blue." ²⁸ Two types of spectroscopic standard stars, blue early-type stars (Feige110, BD+33d2642, BD+25d4655, and Hz44) and red late-type stars (Hilt102 and Cyg OB2 No.9.) were observed to correct for contamination from second-order light in the flux calibration (see Section 3).

We determined the spectroscopic redshifts of the target objects using a "specpro" software (Masters & Capak 2011), which adopts cross-correlation routines for the observed and template spectra. The observed spectra were smoothed with a 5 pixel box-car kernel for cross-correlation. We used the following 10 spectral templates:

• 1.  
  VLBG: an LBG template from VIMOS VLT Deep Survey (VVDS; Le Fevre et al. 2005).
• 2.  
  SLBG: a composite spectrum of z ∼ 3 LBGs (Shapley et al. 2003).
• 3.  
  VI08eLBG: a composite spectrum of LBGs with strong Lyα emission line from the previous VIMOS survey (Hayashino et al. 2019).
• 4.  
  VI08aLBG: a composite spectrum of LBGs with no Lyα emission line from the previous VIMOS survey (Hayashino et al. 2019).
• 5.  
  HITdr1eLBG: a composite of the SSA22-HIT spectra of LBGs with strong Lyα emission line, of which redshifts are easily identified (e.g., they are already confirmed in the previous works; multiple emission/absorption lines are obviously seen).
• 6.  
  HITdr1aLBG: a composite of the SSA22-HIT spectra of LBGs with no Lyα emission line, of which redshifts are easily identified (e.g., they are already confirmed in the previous works; multiple emission/absorption lines are obviously seen).
• 7.  
  VSBurst: a low-z starburst galaxy template with extremely strong nebular lines from the VVDS.
• 8.  
  VEs: a low-z elliptical galaxy template from the VVDS.
• 9.  
  SDSSQSO: a broad line quasar template from the Sloan Digital Sky Survey (Schneider et al. 2010).
• 10.  
  M6star: an M6 type stellar template (Pickles 1998).

The VLBG, SLBG, VSBurst, VEs, SDSSQSO, and M6star templates are the same as those in the original specpro library (Masters & Capak 2011).

For many observed galaxies at z > 2, similar redshift solutions can be obtained by multiple templates among VLBG, SLBG, VI08eLBG, VI08aLBG, HITdr1eLBG, and HITdr1aLBG. To determine the best-fit template, we set the priority as follows. The SLBG, HITdr1eLBG, and HITdr1aLBG templates are more prioritized than the VLBG, VI08eLBG, and VI08aLBG templates because the former have spectral resolutions comparable to the observed DEIMOS spectra. The HITdr1eLBG and HITdr1aLBG templates, which are generated from subsets of the observed objects to be fitted, are less prioritized than the SLBG template. As a result, most of the spectroscopically confirmed galaxies at z > 2 with and without the Lyα emission line were fit by the SLBG and HITdr1aLBG templates, respectively.

We also visually inspected the spectra because the cross-correlation scheme sometimes fails to find the redshift solution, as suggested by the code developers (Masters & Capak 2011). The spectral features that we carefully searched for are the Lyα emission/absorption (1215.67 Å in the rest frame ³⁰ ) line, He ii (1640.35 Å), and C iii] (1906.68 Å and 1908.73 Å) emission lines, and Si ii (1260.42 Å), O i (1302.17 Å), Si ii (1304.37 Å), C ii (1334.53 Å), Si iv (1393.76 Å and 1402.77 Å), Si ii (1526.71 Å), C iv (1548.19 Å and 1550.77 Å), Fe ii (1608.45 Å), and Al ii (1670.79 Å) absorption lines. We also searched [O ii] (3727.3 Å and 3729.2 Å), Hβ (4861.3 Å), [O iii] (4958.9 and 5006.8 Å), and Hα (6562.8 Å) emission lines as a signature of low-redshift contamination. In the visual inspection, we set four types of flags for the determined redshifts based on their reliability and their spectral features (redshift quality flags): Ae (firm redshifts are obtained from clear emission lines), Aa (firm redshifts are obtained from clear absorption lines), B (probable redshifts are obtained from emission lines), and C (possible redshifts are obtained from absorption lines). The flag C objects should be treated carefully for scientific use, because they may include redshift misidentifications. Figure 4 shows the example spectra of the four redshift-quality flags. All of the spectra of the spectroscopically confirmed objects are shown in Appendix A.

Zoom In Zoom Out Reset image size

We eventually obtained spectroscopic redshifts for 198 objects, of which the redshift and sky distributions are shown in Figures 5 and 6, respectively. Table 2 summarizes their detailed numbers using masks and redshift quality flags. Success rates in the redshift determination, which are defined as the number fractions of objects whose redshifts are confirmed over all of the observed targets, are roughly inversely proportional to the depths. Figure 7 shows the broadband magnitude histograms of spectroscopically confirmed objects as well as for all targets. The fainter the continuum of an object, the harder it is to determine its redshift. This tendency is more pronounced in objects identified by absorption lines (Aa and C) than in those identified by emission lines (Ae and B). Figure 8 also shows the magnitude histograms for each of the five major categories. Their magnitude dependencies in the success rates seem similar to those of all objects, which is, however, not statistically significant except for the T2 category. The number summary for each target category is listed in Table 3. To evaluate the accuracy of the prior redshift expectations (z_ex) for the targets in the five major categories (T1, T2, T3, T4, and T5; Section 2.2), we define a recovery rate as the number fraction of each category of objects whose spectroscopic redshifts are found to be within the expected range over those spectroscopically confirmed redshifts (irrespective of the expected redshift range). To calculate the recovery rates, we excluded the objects with previous spectroscopic redshift measurements in the T2/T3 categories (T2prevz/T3prevz; Section 2.2). The recovery rates in T1, T2, T3, T4, and T5 were 82%, 40%, 75%, 67%, and 75%, respectively. As shown in Figure 5, the spectroscopic redshift distribution in each major category extends beyond the low and high boundaries of the prior expectation. We have published the properties of all of the observed targets, including the redshift measurements, redshift quality flags, and target categories (see Appendix B).

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

The cross-correlation technique is expected to provide systemic redshifts unless the spectral properties of the templates used are very different from those of observed objects. The majority of our redshift measurements are determined by cross-correlation with the SLBG and HITdr1aLBG templates. The SLBG template is a composite of LBGs whose redshift and magnitude ranges are similar to those of our HIT sample (Shapley et al. 2003; Steidel et al. 2003). We then consider our redshift measurements to be systemic.

The error estimation of the redshifts measured using the cross-correlation technique is not trivial, a conservative estimate for the redshift uncertainty can be given by the spectral resolution of our HIT data (Δλ ∼ 4.7 Å; see Section 2.3), resulting in Δz ∼ 0.001(1 + z) or Δv ∼ 280 km s⁻¹. After comparing with previous redshift measurements from the literature and archival catalogs (see Sections 4.2), there were 148 objects whose redshifts were newly determined in our SSA22-HIT survey. For the remaining 50 objects, we investigated the redshift differences between those measured in the present study and those of previous works, z_HIT − z_previous, where the latter redshifts are also observed or expected systemic ones (Sections 4.2). Some objects were observed in multiple previous studies, and there were 84 pairs of z_HIT and z_previous. Their redshift differences were found to be ≈0.0002 on average, with a standard deviation of ≈0.004. Considering the redshift uncertainties of our and previous measurements (see Section 4.2 and Table 4), we conclude that our redshift measurements are consistent with those of previous studies.

We collected the redshift catalogs available in the SSA22-Sb1 field, which are summarized in Table 4. Numerous published works have conducted follow-up spectroscopy of rest-frame UV-selected star-forming galaxies. Hayashino et al. (2019) reported 82 LBGs and AGNs at 2 < z < 4 in the SSA22-Sb1 field, which was based on a deep spectroscopic survey performed with VLT/VIMOS in 2008 (VIMOS08). They measured redshifts in two ways using the Lyα emission line (z_em) and multiple interstellar absorption lines (z_abs). Because both often offset from the systemic redshift (z_sys) owing to the outflowing interstellar gas (e.g., Pettini et al. 2001; Shapley et al. 2003), they estimated the systemic redshifts by adopting the calibration formulae proposed by Adelberger et al. (2005). The calibration formulae from z_em and/or z_abs to z_sys were obtained by linear fitting to the measurements of the three types of redshifts for 138 galaxies at 2 < z < 3.5, where the systemic redshifts were precisely determined through near-infrared (NIR) observations of rest-frame optical nebular emission lines (Adelberger et al. 2005). Steidel et al. (2003) conducted a large spectroscopic survey of LBGs using the Keck Low Resolution Imaging Spectrometer (LRIS; Oke et al. 1995). They released 940 spectroscopic redshifts at 2 < z < 4, of which 133 lie in the SSA22-Sb1 field. Two QSOs were found in the SSA22-Sb1 field. Their catalog contains two types of redshifts, z_em and z_abs, from which we estimated the systemic redshifts by adopting the calibration formulae of Adelberger et al. (2005). Nestor et al. (2013) confirmed redshifts for 51 LBGs at 2.4 < z < 3.4 and 101 LAEs at z ≈ 3.1 using Keck LRIS. Both or either of z_em and z_abs are contained in their catalog, from which we estimated z_sys by adopting the calibration formulae of Adelberger et al. (2005). Erb et al. (2014) used the Multi-Object Spectrometer For Infra-Red Exploration on the Keck telescope (MOSFIRE; McLean et al. 2010, 2012) to confirm redshifts of 19 LAEs in the z ≈ 3.1 SSA22 protocluster. While their targets overlap with those of Steidel et al. (2003) and Nestor et al. (2013), their systemic redshifts determined from the rest-frame optical nebular emission lines ([O iii] 5007 and Hα) are more reliable, and no extra calibration is applied. Matsuda et al. (2005, 2006), and Yamada et al. (2012a) confirmed redshifts for 64, 39, and 91 LAEs at z ≈ 3.1 using the Subaru Faint Object Camera and Spectrograph (FOCAS; Kashikawa et al. 2002) and Keck DEIMOS, some of which are LABs. Their redshifts are all determined from the peaks of the Lyα emission lines, from which we estimated z_sys by adopting the calibration formulae of Adelberger et al. (2005). Yamanaka et al. (2020) conducted spectroscopic observations with the Keck MOSFIRE-targeting LyCs (Iwata et al. 2009; Micheva et al. 2017b), LBGs (this work), and LAEs (Yamada et al. 2012a, 2012b). They detected multiple lines among [O iii] 5007, [O iii] 4959, and H β for the two LyCs, 10 LBGs, and one LAE, which provide accurate systemic redshifts. For our catalog compilation, we also took an LBG, SSA22-LBG-05 in Yamanaka et al. (2020), for which only [O iii] 5007 is detected in the MOSFIRE observations, but Lyα is identified in our SSA22-HIT survey.

In the SSA22 field, galaxies selected at NIR or longer wavelengths have also been actively investigated. They are massive quenched or dust-obscured galaxies at z ≳ 2. Kubo et al. (2015) used Subaru MOIRCS to observe candidate PCs with K_s < 24 mag and 2.6 < photo-z <3.6 (Kdet), distant red galaxies (DRGs; J − K > 1.4; van Dokkum et al. 2003), hyper extremely red objects (HEROs; J − K > 2.1; Totani et al. 2001), Spitzer MIPS 24 μm sources (M24), AzTEC/ASTE 1.1 mm sources (SMGs), Chandra X-ray sources (XRs), LAEs, and LABs. They confirmed systemic redshifts of 39 galaxies at 2.0 < z < 3.4 from their rest-frame optical nebular emission lines. We ignore J221737.3+001816.0, whose redshift was determined from the Balmer break with large uncertainty. In Kubo et al. (2016), the authors intensively investigated groups of massive galaxies associated with an SMG and LABs at z = 3.1 through their NIR spectroscopic observations and archival redshift catalogs. We catalog the six galaxies from Kubo et al. (2016), avoiding duplication of the source catalogs with the other archival data used in this study. The ALMA deep field in the SSA22 (ADF22) survey is a deep 20 arcmin² survey at 1.1 mm using ALMA Band 6 (Umehata et al. 2017, 2018). Among the 35 ALMA-detected SMGs, 21 were spectroscopically confirmed at 2 ≲ z ≲ 3 by the ALMA observations and archival redshift catalogs. We cataloged the 19 galaxies whose redshifts originally come from Bothwell et al. (2013) and Umehata et al. (2015, 2018, 2019), avoiding duplication of the source catalogs with the other archival data used in this study. Their redshift identifications were based on the NIR or FIR observations of the rest-frame optical or longer-wavelength emission lines, which ensures systemic redshifts. Chapman et al. (2005) performed a redshift survey of SMGs using the Keck/LRIS and Echellette Spectrograph and Imager (ESI; Sheinis et al. 2002). Spectroscopic redshifts were confirmed for 73 SMGs, of which 10 were in the SSA22-Sb1 field. The SMGs of Chapman et al. (2005) were originally selected using the Submillimeter Common-User Bolometer Array-2 (Holland et al. 2013) equipped with the James Clerk Maxwell Telescope, which has a large beam size of ≳10''. They attempted to accurately identify the optical counterparts for spectroscopic observations by cross-matching with radio sources in the finer-resolution Karl G. Jansky Very Large Array 20 cm map, but this identification method is not complete (Hodge et al. 2013). Chapman et al. (2004) measured spectroscopic redshifts for 18 optical-faint, submillimeter-faint, and radio-bright galaxies (OFRGs) using Keck/LRIS, among which two are in the SSA22-Sb1 field. The redshifts in the catalogs of Chapman et al. (2004, 2005) were determined based on a comparison with the template spectra in multiple features such as the Lyα emission line, interstellar absorption lines, and continuum breaks, to which extra calibration was not applied.

Saez et al. (2015) conducted a large spectroscopic survey of X-ray sources (XRs), bright objects with R < 22.5 (bright), and LBGs in the SSA22-Sb1 field using the VLT/VIMOS, Keck/DEIMOS, and LRIS. They confirmed redshifts of the 247 extragalactic sources and 120 Galactic stars using the same cross-correlation technique as we adopted for the SSA22-HIT data. We did not apply extra calibration to redshift measurements. They adopted their AGN criteria for XR sources spectroscopically confirmed by their observations as well as by Lehmer et al. (2009a), identifying a total of 84 AGNs. The VIMOS VLT Deep Survey in its Wide layer (VVDS-Wide; Garilli et al. 2008; Le Fèvre et al. 2013) confirmed ∼26,000 bright galaxies and AGNs with 17.5 < i < 22.5. We extracted 912 objects in the SSA22-Sb1 field from the public catalog, ³¹ where we removed objects whose redshifts were tentatively determined with their flags of 1, 11, 21, or 211. The majority of the 912 objects are at z < 2, where only 10 lie beyond z > 2 and the median redshift is z ≈ 0.6. Their redshifts were measured based on the cross-correlation technique, followed by careful inspection by multiple people, to which extra calibration was not applied. We consider the cataloged objects with any broad (≳1000 km s⁻¹) emission lines resolved at the VIMOS resolution as AGNs, which were selected by the cataloged flags of 10 < flag < 20 or flag > 200.

We also utilized the following archival redshift catalogs that are not publicly available. The VIMOS06 survey (Kousai 2011; Hayashino et al. 2019) was a pilot observation for the VIMOS08 survey using VLT/VIMOS with LR-blue grism under the program ID 077.A-0787 (PI: R. Yamauchi), where a wider area was surveyed with a shorter integration time than VIMOS08. We performed redshift determination for 98 spectra that were reduced by Kousai (2011) and Hayashino et al. (2019) in the same manner as that adopted for the SSA22-HIT data. Eventually, we confirm redshifts for 70 LBGs and six AGNs, where the AGN identification is based on Steidel et al. (2003) and Hayashino et al. (2019). H. Umehata et al. (2023, in preparation) conducted a spectroscopic survey of SMGs, LBGs, and LyCs using VLT/VIMOS with LR-blue grism (VIMOS12) under the program ID 089.A-0740 (PI: H. Umehata). They measured both z_em and z_abs, from which we estimated the systemic redshifts by adopting the calibration formulae of Adelberger et al. (2005). Using Keck/DEIMOS with the 900ZD grating under the program ID of S275D, T. Yamada et al. performed spectroscopic observations (DEIMOS08) of LAEs, LBGs, Lyα absorbers (LAAs; Hayashino et al. 2004), and K_s -detected objects (Kdet) not only in the SSA22-Sb1 field but also in a wider area. We conducted reduction and redshift identification in the same manner as that adopted for the SSA22-HIT data. Out of 94 galaxies whose redshifts were confirmed, 42 lie in the SSA22-Sb1 field. M. Ouchi and colleagues (Momcheva et al. 2013; Higuchi et al. 2019) conducted a large spectroscopic survey of high-z galaxies using the Inamori Magellan Areal Camera and Spectrograph (IMACS; Dressler et al. 2011) on the Magellan I Baade Telescope between 2007 and 2010 (oIMACS; Momcheva et al. 2013; Higuchi et al. 2019). We analyzed the spectra of the objects in the SSA22 field that were obtained using Gri-300-17.5 and Gri-300-4.3 grisms. Redshifts were determined from their Lyα emission lines, from which we estimated the systemic redshifts by adopting the calibration formulae of Adelberger et al. (2005). In this work, we used 29 LAEs, LABs, LBGs, and LyCs in the SSA22-Sb1 field.

The determination schemes for the above redshifts were divided into three types. The redshift determination based on the NIR or FIR observations of the rest-frame optical or longer-wavelength emission lines yielded the most reliable systemic redshifts (Erb et al. 2014; Kubo et al. 2015, 2016; Yamanaka et al. 2020; ADF22). The cross-correlation or comparison with spectral templates, which was adopted in SSA22-HIT, Chapman et al. (2004, 2005), Saez et al. (2015), VVDS-Wide, VIMOS06, and DEIMOS08, is expected to provide systemic redshifts when the spectral properties of the used templates are similar to those of the observed objects. The empirical calibration formulae from z_em and/or z_abs to z_sys, which were applied to the data of VIMOS08, Steidel et al. (2003), Nestor et al. (2013), Matsuda et al. (2005, 2006), Yamada et al. (2012a), VIMOS12, and oIMACS, are reliable within σ_z ≈ 0.003 for star-forming galaxies at 2 < z < 3.5 (Adelberger et al. 2005). In Table 4, we list the uncertainties of the systemic redshifts in the individual works. If uncertainties are described in the original literature or references therein, we use them only. Otherwise, we conservatively expect the redshift errors to be (1 + z)Δλ/λ = (1 + z)/R, where Δλ and R correspond to the spectral resolutions in the individual works. If the calibration formulae of Adelberger et al. (2005) are adopted, we include the associated uncertainty (σ_z ≈ 0.003) by taking the root sum squares.

We merged our SSA22-HIT redshift catalog (Section 4.1) and ancillary catalogs (Section 4.2). We here excluded 23 objects with the redshift quality flag = C (possible redshift cases) in SSA22-HIT to match the redshift quality with the other catalogs. For the same reason, the objects with the flag = C were also excluded from the VIMOS06 and DEIMOS08 samples whose redshifts were determined in the same manner as that adopted for the SSA22-HIT data (Section 4.2). The individual catalogs follow their own astrometry, which is slightly offset by ∼1'' at maximum. We first searched for counterparts and extracted their coordinates in the V image for the LBGs in the Steidel et al. (2003) and Nestor et al. (2013) catalogs; the NB497 image for the LAEs; the K_s image for galaxies selected at NIR or longer wavelengths in Kubo et al. (2015, 2016), ADF22 catalog, and the $i^{\prime}$ image for the other catalog objects.

We found 228 objects duplicated in multiple catalogs with a matching radius of 10, which yields 490 pairs of redshifts measured by different works. We estimated the average and standard deviation of the redshift differences to be ≈ − 0.001 and ≈0.003, respectively. The redshifts in our compilation are roughly consistent with each other within the uncertainties (see Section 4.2 and Table 4). On the other hand, there are 32 outlier pairs for 21 objects with redshift differences as large as Δz > 0.02. Approximately one-third of them are due to the misidentification of their emission lines (e.g., Lyα at z ≈ 3.1 and [O ii] 3727 at z ≈ 0.33). For the duplicated objects, representative redshifts are selected according to the following order of priority: Erb et al. (2014); Yamanaka et al. (2020), ADF22, Kubo et al. (2015, 2016); Chapman et al. (2004, 2005); Steidel et al. (2003); Nestor et al. (2013), SSA22-HIT, VIMOS08, VIMOS12, VIMOS06, Matsuda et al. (2006, 2005); Yamada et al. (2012b), DEIMOS08, VVDS, Saez et al. (2015), and oIMACS. This priority order is determined by whether the redshift determination is based on the rest-frame optical nebular emission lines, the survey depth, the spectral resolution, and/or the details of the classification of the object types.

We isolated AGNs by matching our compiled catalogs with AGN catalogs. Saez et al. (2015) performed secure AGN selection for Chandra XR sources of Lehmer et al. (2009b, 2009a) based on the X-ray luminosity, spectral shape, X-to-optical, and X-to-radio flux ratios. Hayashino et al. (2019) selected AGNs based on visual inspection of the optical spectra. Micheva et al. (2017a) searched for LyC leakers among 14 AGNs at z ≥ 3.06 selected by detection in X-ray (Lehmer et al. 2009b; Saez et al. 2015) or by emission lines in the optical spectra. We also visually inspected the SSA22-HIT spectra to identify four AGNs with strong rest-UV emission lines, namely, C iv (1548.20 Å and 1550.78 Å), He ii (1640.4 Å), and C iii] (1906.68 Å and 1908.73 Å). We eventually found 105 AGNs, including 34 at z ≥ 2.

We compiled a final catalog of 1941 unique objects with spectroscopic redshifts in the SSA22-Sb1 field, among which 730 are at z ≥ 2. The sky distribution is shown in Figure 9. The redshift histograms are shown in Figure 10, where representative redshifts were used. The number of galaxies at z > 3.2, which can be used as background light sources for the H i tomography at z = 3.1 or more, is significantly increased by a factor of 1.7 owing to the SSA22-HIT survey. We have made the compiled redshift catalog public (see Appendix C). The SSA22 field is one of the most extensively investigated regions with various types of galaxies. Our compiled redshift catalog is useful for a variety of applications. For example, one of our future works will be to investigate the dependency of the different types of galaxies on the IGM H i environment, which will be complementary to the study in a general field by Momose et al. (2021).

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size