catalogs — dark ages, reionization, first stars — galaxies: high-redshift —
surveys

# CHORUS. I. Cosmic HydrOgen Reionization Unveiled with Subaru: Overview

Akio K. Inoue11affiliation: Department of Physics, School of Advanced Science
and Engineering, Faculty of Science and Engineering, Waseda University, 3-4-1,
Okubo, Shinjuku, Tokyo 169-8555 22affiliation: Waseda Research Institute for
Science and Engineering, Faculty of Science and Engineering, Waseda
University, 3-4-1, Okubo, Shinjuku, Tokyo 169-8555 33affiliation: Department
of Environmental Science and Technology, Faculty of Design Technology, Osaka
Sangyo University, 3-1-1 Nakagaito, Daito, Osaka 574-8530
<EMAIL_ADDRESS>Satoshi Yamanaka22affiliationmark:  33affiliationmark:
Masami Ouchi44affiliation: National Astronomical Observatory of Japan, 2-21-1,
Osawa, Mitaka, Tokyo, 181-8588 55affiliation: Institute for Cosmic Ray
Research, The University of Tokyo, 5-1-5 Kashiwa-no-ha, Kashiwa, Chiba
277-8582 66affiliation: Kavli Institute for the Physics and Mathematics of the
Universe (Kavli IPMU), WPI, The University of Tokyo, Kashiwa, Chiba 277-8583
Ikuru Iwata44affiliationmark:  77affiliation: Department of Astronomical
Science, The Graduate University for Advanced Studies, SOKENDAI, 2-21-1,
Osawa, Mitaka, Tokyo 181-8588 Kazuhiro Shimasaku88affiliation: Department of
Astronomy, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo,
Bunkyo-ku, Tokyo 113-0033 99affiliation: Research Center for the Early
Universe, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo,
Bunkyo-ku, Tokyo 113-0033 Yoshiaki Taniguchi1010affiliation: The Open
University of Japan, 2-11 Wakaba, Mihama-ku, Chiba, Chiba 261-8586
1111affiliation: Research Center for Space and Cosmic Evolution, Ehime
University, Matsuyama, Ehime 790-8577 Tohru Nagao1111affiliationmark:
Nobunari Kashikawa88affiliationmark:  Yoshiaki Ono55affiliationmark:  Ken
Mawatari55affiliationmark:  33affiliationmark:  Takatoshi
Shibuya1212affiliation: Kitami Institute of Technology, 165 Koen-cho, Kitami,
Hokkaido 090-8507 Masao Hayashi44affiliationmark:  Hiroyuki
Ikeda1313affiliation: National Institute of Technology, Wakayama College,
Gobo, Wakayama 644-0023 Haibin Zhang1414affiliation: Department of Astronomy,
Tsinghua University, No.1 Qinghuayuan, Beijing 100084, China
55affiliationmark:  Yongming Liang77affiliationmark:  44affiliationmark:
88affiliationmark:  C.-H. Lee1515affiliation: NSF’s National Optical-Infrared
Astronomy Research Laboratory, Tucson, AZ 85719, USA Miftahul
Hilmi55affiliationmark:  88affiliationmark:  Satoshi Kikuta1616affiliation:
Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai,
Tsukuba, Ibaraki 305-8577 Haruka Kusakabe1717affiliation: Observatoire de
Genève, Université de Genève, 51 chemin de Pégase, 1290 Versoix, Switzerland
Hisanori Furusawa44affiliationmark:  77affiliationmark:  Tomoki
Hayashino1818affiliation: Research Center for Neutrino Science, Tohoku
University, Aramaki, Aoba-ku, Sendai 980-8578 Masaru
Kajisawa1111affiliationmark:  Yuichi Matsuda44affiliationmark:
77affiliationmark:  Kimihiko Nakajima44affiliationmark:  Rieko
Momose88affiliationmark:  Yuichi Harikane1919affiliation: Department of
Physics and Astronomy, University College London, Gower Street, London WC1E
6BT, UK 44affiliationmark:  Tomoki Saito2020affiliation: Nishi-Harima
Astronomical Observatory, Centre for Astronomy, University of Hyogo, 407-2
Nishigaichi, Sayo, Sayo-gun, Hyogo 679-5313 Tadayuki Kodama2121affiliation:
Astronomical Institute, Tohoku University, 6-3 Aramaki, Aoba-ku, Sendai
980-8578 Shotaro Kikuchihara55affiliationmark:  88affiliationmark:  Masanori
Iye44affiliationmark:  Tomotsugu Goto2222affiliation: Institute of Astronomy,
National Tsing Hua University, 101 Section 2 Kuang Fu Road, Hsinchu 300,
Taiwan, R. O. C.

###### Abstract

To determine the dominant sources for cosmic reionization, the evolution
history of the global ionizing fraction, and the topology of the ionized
regions, we have conducted a deep imaging survey using four narrow-band (NB)
and one intermediate-band (IB) filters on the Subaru/Hyper Suprime-Cam (HSC),
called Cosmic HydrOgen Reionization Unveiled with Subaru (CHORUS). The central
wavelengths and full-widths-at-half-maximum of the CHORUS filters are,
respectively, 386.2 nm and 5.5 nm for NB387, 526.0 nm and 7.9 nm for NB527,
717.1 nm and 11.1 nm for NB718, 946.2 nm and 33.0 nm for IB945, and 971.2 nm
and 11.2 nm for NB973. This combination, including NB921 (921.5 nm and 13.5
nm) from the Subaru Strategic Program with HSC (HSC SSP), are carefully
designed, as if they were playing a chorus, to observe multiple spectral
features simultaneously, such as Lyman continuum, Ly$\alpha$, C iv, and He ii
for $z=2$–$7$. The observing field is the same as that of the deepest
footprint of the HSC SSP in the COSMOS field and its effective area is about
1.6 deg2. Here, we present an overview of the CHORUS project, which includes
descriptions of the filter design philosophy, observations and data reduction,
multiband photometric catalogs, assessments of the imaging quality,
measurements of the number counts, and example use cases of the data. All the
imaging data, photometric catalogs, masked pixel images, data of limiting
magnitudes and point spread functions, results of completeness simulations,
and source number counts are publicly available through the HSC SSP database.

##  1 Introduction

Understanding cosmic reionization is one of the most important objectives in
observational cosmology. Measurements of the Thomson scattering optical depth
of free electrons in the intergalactic medium (IGM) in the cosmic microwave
background with Wilkinson Microwave Anisotropy Probe and Planck satellites
place the epoch of hydrogen reionization at $z\sim 10$ (Komatsu et al., 2011;
Planck collaboration, 2018). Detection of the Gunn-Peterson trough in the
spectra of quasars at $z>6$ (e.g., Fan et al. (2006); Becker et al. (2007))
and the decrement in the luminosity functions (LFs) of Ly$\alpha$ emitters
(LAEs) at $z>6$ (e.g., Kashikawa et al. (2006); Ouchi et al. (2010); Hu et al.
(2010); Kashikawa et al. (2011); Nakamura et al. (2011); Konno et al. (2014);
Matthee et al. (2015); Santos et al. (2016); Konno et al. (2018); Itoh et al.
(2018); Hu et al. (2019); Taylor et al. (2020)) suggest a rapid increase in
the hydrogen neutral fraction, $x_{\rm HI}$, beyond $z=6$. The $x_{\rm HI}$
measurements obtained so far still has a large scatter due to the small
statistics and the systematic uncertainty in each measurement (e.g., Robertson
et al. (2015); Greig & Mesinger (2017); Inoue et al. (2018); Finkelstein et
al. (2019); Naidu et al. (2020)). New $x_{\rm HI}$ measurements near $z\sim 7$
based on large samples of galaxies over large cosmic volumes are required to
reach a concordance in the history of reionization.

Galaxies, such as LAEs and Lyman break galaxies (LBGs), at $z>6$ can be the
dominant ionizing sources if their Lyman continuum (LyC) emissivity or escape
fraction $f_{\rm esc}$, is sufficiently high. The required $f_{\rm esc}$ is
$\sim 20\%$, assuming a standard population synthesis model (e.g., Inoue et
al. (2006); Robertson et al. (2015); Finkelstein et al. (2019); Naidu et al.
(2020)). Measuring the LyC emissivity of these galaxies, which is still quite
uncertain, is the most critical step in the determination of the ionization
sources for reionization. Bright quasars do not contribute much to the LyC
emissivity for reionization owing to their rarity (e.g., Bianchi et al.
(2001)), whereas faint Active Galactic Nuclei (AGNs) might contribute to or
even dominate (Giallongo et al., 2015; Madau & Haardt, 2015). However, other
observations suggest that faint AGNs are not sufficiently abundant (Kashikawa
et al., 2015; Onoue et al., 2017; Matsuoka et al., 2018; Parsa et al., 2018).
Measuring the LyC emissivity of AGNs is also required to resolve their role in
reionization (Micheva et al., 2017; Grazian et al., 2018). The metal-free
stellar population, the so-called Population III (Pop III) stars (e.g.,
Carlberg (1981)), can be an important ionizing source, particularly in the
early phase of the reionization process (e.g., Sokasian et al. (2004)).
Because their characteristics, such as the initial mass function (IMF), are
unknown observationally owing to the lack of information (Nagao et al., 2005,
2008; Kashikawa et al., 2012; Vanzella et al., 2020), identifying Pop III
clusters and revealing their nature are highly relevant to understanding their
role in reionization.

Depending on the dominant ionizing source, the topology of reionization is
expected to be different: “inside-out” (Iliev et al., 2006) by galaxies or
“outside-in” (Miralda-Escudé et al., 2000) by X-ray sources, such as AGNs.
Observationally, the spatial inhomogeneity of $x_{\rm HI}$ at $z\sim 6$ has
been reported to be based on quasar spectra (Becker et al., 2015) and LAE LFs
(Ouchi et al., 2010; Nakamura et al., 2011). Obtaining the overdensities of
LAEs at $z\gtrsim 6.5$ may support the concept that these LAEs are located in
the ionized bubbles produced by the galaxy overdensities (e.g., Castellano et
al. (2016); Bagley et al. (2017); Higuchi et al. (2019); Harikane et al.
(2019); Tilvi et al. (2020)). Resolving the ionization topology is one of the
main scientific goals for future H i 21 cm tomography with the Square
Kilometer Array (SKA) (e.g., Hasegawa et al. (2016)). However, with a
sufficiently large survey of LAEs and LBGs, we may visualize the $x_{\rm HI}$
map before the SKA era. Such topology observations will be important
consistency checks of the ionizing source observations, by comparing the
observed topology with the prediction based on the identified dominant
ionizing sources.

The Hyper Suprime-Cam (HSC) (Miyazaki et al., 2018; Komiyama et al., 2018;
Kawanomoto et al., 2018; Furusawa et al., 2018) has the widest field-of-view
(FoV), 1.75 deg2, on an 8m-class telescope. This unique capability with a
well-considered set of narrowband (NB) filters, for the first time, allows
dealing with the central questions of reionization by an unprecedented wide
and deep NB survey. Since 2007, we have studied the specifications of HSC NBs
carefully (see section 2) and developed them under strict scientific reviews
with the financial support of approximately 100 M yen from the Japan Society
for the Promotion of Science. Four NBs (NB387, NB816, NB921, and NB101) among
them are included in the on-going HSC Subaru Strategic Program (SSP) (Aihara
et al., 2018a) for deep surveys of LAEs at $z\simeq 2.2$, 5.7, 6.6, and 7.3
(Ouchi et al., 2018). The latter three high-$z$ surveys provide new estimates
of the cosmic average of $x_{\rm HI}$ at $z\simeq 6.6$ and 7.3 from comparison
with LAE LFs (Ouchi et al., 2018; Shibuya et al., 2018a, b; Konno et al.,
2018; Inoue et al., 2018). However, the HSC SSP cannot address the LyC
emissivity and the $x_{\rm HI}$ topology directly.

Thus, we initiated a Subaru intensive program, Cosmic HydrOgen Reionization
Unveiled with Subaru (CHORUS), with NB387, NB527, NB718, IB945, and NB973
(Table 2; see Fig. 1). Supplying the data of the NB921 and broadband (BB)
filters from the HSC SSP, we aim to answer the questions of the ionization
source and the topology, in addition to the history, by measuring the LyC
emissivity values of galaxies and AGNs, abundance of Pop III stars, and LF of
faint AGNs, and visualizing the $x_{\rm HI}$ map directly see sections 6.1-6.5
for more information). These measurements are realized only in combination
with our NBs. This program will become a legacy survey at least for a decade
because no other deep and wide-area survey, such as the Large Synoptic Survey
Telescope, has a set of NBs like this program.

This paper presents an overview of the CHORUS project and its first public
data release: CHORUS PDR1. In section 2, we describe the CHORUS filter set in
detail. Section 3 is a summary of the observations, data reduction, and
photometric catalogs of the CHORUS data. Section 4 presents a summary of
imaging quality, such as the size of the point spread function and the
limiting magnitude of each NB. In section 5, the number counts in the five
CHORUS NBs are given as a set of fundamental measurements of the NB imaging
data. Section 6 gives a brief instruction of the usage of the CHORUS PDR1 data
and some example science cases. A summary of this paper is found in the final
section.

We assume a standard set of cosmological parameters of $H_{0}=70$ km s-1
Mpc-1, $\Omega_{M}=0.3$ and $\Omega_{\Lambda}=0.7$ and use the AB magnitude
system (Oke, 1990) throughout the study.

##  2 Filter set

Figure 1: Filter efficiency functions (narrowbands and broadbands are shown in
red and black, respectively) with example spectra of a galaxy at $z=3.35$
(top) and an AGN at $z=4.93$ (bottom). For the $r2/r$ and $i2/i$ bands, the
solid lines show the $r2$ and $i2$ transmissions and the dashed lines show the
$r$ and $i$ transmissions. The effects considered in addition to the filter
transmission are as follows: atmospheric transmission at the summit of Mauna
Kea (airmass of 1.2 and water vapor column of 1.6 mm), the primary mirror
reflectance, and the instrumental throughput of the HSC including the CCD
quantum efficiency and an average vignetting effect in the field-of-view.

Summary of filter properties.  Area-weighted mean (Central position) Redshift
range of targeted featuresd Filter CWa FWHMb TPc LyC Ly$\alpha$ C iv He ii
Papers which used the NBs.e NB387 386.2 (385.8) 5.5 (5.7) 0.842 (0.871)
$>$3.27 2.15–2.20 — — A18a, L20 NB527 526.0 (525.5) 7.9 (7.5) 0.956 (0.922)
$>$4.81 3.29–3.36 — 2.18–2.23 H20 NB718 717.1 (716.8) 11.1 (11.1) 0.927
(0.911) — 4.85–4.94 — 3.34–3.41 Z20, H20 NB921f 921.5 (920.4) 13.5 (13.4)
0.935 (0.937) — 6.52–6.64 4.90–4.99 — A18a, O18, H20 IB945 946.2 (944.7) 33.0
(32.2) 0.955 (0.952) — 6.65–6.92 — — NB973 971.2 (969.9) 11.2 (11.0) 0.878
(0.834) — 6.94–7.04 — 4.88–4.95 I18, H20 a The central wavelength (CW) of the
transmission function in units of nm.
b The full-width-at-half-maximum (FWHM) of the transmission function in units
of nm.
c The transmission peak (TP) of the transmission function itself (i.e., not
including the instrumental and atmospheric throughput).
d (CW$\pm$FWHM/2)/$\lambda$-1. Adopted rest-frame wavelength ($\lambda$) of
the features: Lyman limit: 91.175 nm, Ly$\alpha$: 121.567 nm, C iv: 154.949
nm, and He ii: 164.033 nm.
e References: A18a: Aihara et al. (2018a), L20: Liang et al. (2020), H20:
Hayashi et al. (2020), Z20: Zhang et al. (2020), O18: Ouchi et al. (2018),
I18: Itoh et al. (2018)
f The imaging data collected and presented in SILVERRUSH (Ouchi et al. 2018)
of the HSC SSP (Aihara et al. 2018a).

The CHORUS filter set consists of four NBs (NB387, NB527, NB718, and NB973)
and one IB (IB945) in addition to NB921 from HSC SSP. Table 2 is a summary of
the characteristics of the filters and the targeted spectral features of
high-$z$ galaxies and the redshift ranges. Fig. 1 shows the total efficiency
of the NBs as well as HSC BBs.111In the UD COSMOS field of the HSC SSP, there
are two filters each for the $r$\- and $i$-bands, namely $r2/r$ and $i2/i$
(Kawanomoto et al., 2018). The newer $r2$ and $i2$ filters were used about 60%
in the data according to the HSC PDR2 web page (https://hsc-
release.mtk.nao.ac.jp/doc/index.php/data-2/). These two filter images were all
combined to make final coadd images of the $r$\- and $i$-bands (Aihara et al.,
2019). The CHORUS filter set not only covers a wide redshift range of
$2\lesssim z\lesssim 7$ of Ly$\alpha$ but also enables us to observe multiple
spectral features at specific redshifts at the same time. As found in Fig. 1,
the LyC and He ii 1640 line for $z\simeq 3.3$ LAEs selected with NB527 can be
observed with NB387 and NB718, respectively, and similarly, the LyC, C iv
line, and He ii line for $z\simeq 4.9$ LAEs selected with NB718 can be
observed with NB527, NB921, and NB973, respectively. For $z\simeq 2.2$ LAEs
selected with NB387, the He ii line can be observed with NB527 (see Table 2).
The last CHORUS filter, IB945, is a filter to select LBGs within a redshift
range similar to that of LAEs selected with NB921 ($z\simeq 6.6$) and NB973
($z\simeq 7.0$) (see section 6.4 for its science case). It is also useful to
trace the line-free continuum between the C iv and He ii lines at $z\simeq
4.9$ (see Fig. 1). In the following, we further describe the philosophy of the
HSC SSP and CHORUS filter specifications and the characteristics of the CHORUS
filters measured in the laboratory.

The NB filter set for the HSC imaging survey was designed very carefully
(Ouchi et al., 2018). The filter wavelengths in the redder wavelength range
were determined to pass through OH sky windows at 816, 921, 973, and 1010 nm.
The three filters, except for the one at 973 nm, were used for the NB imaging
observations in the HSC SSP survey (Aihara et al., 2018a) called SILVERRUSH
(Ouchi et al., 2018). The remaining NB973 filter became a CHORUS filter. The
filter wavelengths in the blue wavelength range were determined to ensure that
multiple spectral features of the LAEs selected by an NB filter were captured
by the other NB filters and strong rest-frame optical emission lines of the
LAEs passed through the OH sky windows in the near-infrared range maximally.
The selected wavelengths were 387, 527, and 718 nm, which became the CHORUS
filters.222Although NB387 was also used for the ‘Deep’ layer observations in
the HSC SSP (Aihara et al., 2018a; Ouchi et al., 2018), there was no data
taken in the footprint of the ‘UltraDeep’ layer in the COSMOS field, where the
CHORUS observations were performed. This combination allows us to observe LyC,
Ly$\alpha$, and He ii at $2\lesssim z\lesssim 5$ as described above. The [O
ii] 3727 and H$\alpha$ lines for $z\simeq 2.2$ LAEs selected with NB387 fall
in the OH sky windows at 1.19 and 2.10 . The [O iii] 4959/5007 for $z\simeq
3.3$ LAEs selected with NB527 are also observable at 2.15/2.17 in the middle
of the $K$-band.

The full-width-at-half-maximum (FWHM) of each filter was also determined
carefully (Ouchi et al., 2018). The FWHM of NB921 was first determined, to
cover the full width of the OH sky window. The FWHMs of the other NB filters,
except for NB973 and IB945, were subsequently determined to ensure the same
efficiency for the Ly$\alpha$ line detection as NB921. Because the observed
equivalent width of a line is $EW_{\rm obs}=(1+z)EW_{0}$, where $EW_{0}$ is
the intrinsic equivalent width and $z$ is the source redshift, the FWHMs were
determined by the relation, $FWHM=FWHM_{921}\times(1+z)/(1+6.58)$. Note that
6.58 is the redshift of the LAEs selected with NB921. NB973 has a narrower
FWHM than the relation to enhance the efficiency of the Ly$\alpha$ line
detection and compensate for the shallower depth in the band. IB945 has an
FWHM to fill the wavelength gap between NB921 and NB973.

The HSC filter is 600 mm in diameter, making it a challenging task to realize
a uniform multi-layer interferometric coating to produce narrow bandpass
filters with sharp cut-on and cut-off wavelengths. Therefore, there was a
small deviation from the specifications during the production process. We
examined the performance of the NB filters produced by the manufacturers,
Optical Coatings Japan (NB387, NB527, NB718, NB921, and NB973) and Materion
(IB945), using the method described in Kawanomoto et al. (2018). Slight non
uniformities in the central wavelength (CW), FWHM, and transmission peak (TP)
were found along the radial direction. The CW tended to increase with the
radius, except for NB387 where the CW variation was a complex way. The FWHM
also tended to increase in the outer part, except for NB387 where it decreased
with the radius. The overall CW variation was less than 0.3–0.5% (the worst
case was found in NB527), whereas the FWHM variation is ranging from a few–10%
(NB387). The TP also tended to increase with the radius, except for NB387
again, where the TP decreased with the radius. The overall TP variation was
less than 1–10% (NB973). A higher degree of uniformity was found in the
azimuthal direction. Table 2 presents the CWs, FWHMs, and TPs for the area-
weighted mean transmission functions of the CHORUS filters. The values for the
transmission functions at the center positions of the filters are also
provided for reference. The machine-readable filter transmission curves are
available at the Subaru/HSC web
site.333https://subarutelescope.org/Observing/Instruments/HSC/sensitivity.html

##  3 Observations, data reduction and photometric catalogs

Summary of CHORUS observations and data qualities.  Exposurea PSF FWHMb
$5\sigma$ depthc [AB] Aread Filter Observation dates [h] [′′] $\phi
1.5^{\prime\prime}$ $\phi 2.0^{\prime\prime}$ [deg2] NB387 Jan. 17, 18, 19,
2018 21/17.3 1.01 (0.99) 25.80e (26.07)e 25.42e (25.65)e 1.561 NB527 Dec. 16,
17, 18, 2017; Mar. 15, 16, 18, 2018 10.5/8.9 0.83 (0.82) 26.72 (26.87) 26.30
(26.46) 1.613 NB718 Feb. 25, Mar. 23, 25, 2017 13.5/7.7 0.69 (0.68) 26.29
(26.47) 25.87 (26.06) 1.575 IB945 Dec. 1, 2, 3, 12, 2018 10.2/10.2 0.62 (0.61)
25.77 (25.92) 25.36 (25.49) 1.558 NB973 Jan. 26, 28, 2017 15/14.7 0.64 (0.64)
25.19 (25.37) 24.79 (24.96) 1.603 a On-source exposure time/effective exposure
time for the final coadd image, except for patches at the edge of the field-
of-view, where these times are somewhat shorter due to dithering.
b Full-width-at-half-maximum (FWHM) of the point spread function (PSF): The
area-weighted average value (the value in the central patch 404).
c $5\sigma$ limiting magnitude for circular apertures of $1.5^{\prime\prime}$
or $2.0^{\prime\prime}$ in diameter: The area-weighted average value (the
value in the central patch 404).
d Effective area after removing masked regions.
e Value corrected for zero-point offset ($-0.45$ mag.). See an explanation in
the last paragraph of section 3.

We were awarded 13 nights in the classical mode of the Subaru Telescope for
four consecutive semesters from S16B to S18A (i.e., 2 years) under a Subaru
open-use intensive program, S16B-001I (PI: A. K. Inoue). We were also awarded
11.5 hours in the queue mode in semester S18B under an open-use normal
program, S18B-004 (PI: A. K. Inoue), to supplement the time loss due to the
weather during the original four semesters. Under the two programs, we
performed deep imaging observations using our NB filters on the HSC on the
dates listed in Table 3. The on-source exposure time as well as the effective
exposure time used for the final coadd images are also listed in Table 3. Some
of the observation dates were not under a photometric condition (i.e., low
transparency), and we discarded a fraction of the observed data owing to bad
quality. The observing field was the COSMOS field (Scoville et al., 2007),
which has the same footprint as the HSC SSP Ultra Deep (UD) layer (Aihara et
al., 2018a). Any sky region in the HSC SSP survey is defined by a set of two
numbers of tract and patch (Aihara et al., 2018b). Most of the HSC SSP UD
COSMOS is covered by tract number 9813. There are $9\times 9$ sub-regions —
patches — in a tract. Each patch has a sky area of $12^{\prime}\times
12^{\prime}$ and a tract has that of $1.8^{\circ}\times 1.8^{\circ}$. The
numbers of patches are expressed as 000 (south-east corner), 001, 002, …, 008
(north-east corner), 100, 101, …, 808 (north-west corner). The patch
configuration in the UD COSMOS tract 9813 is found in Fig. 2.

The data reduction was conducted using the HSC SSP pipeline, hscPipe, version
6.7, which is the same as that used for the SSP PDR2 data processing. We used
the obtained imaging data satisfying the following conditions: exposure time
$=1200$ sec, seeing $<1.5^{\prime\prime}$, and transparency $>0.4$ for NB387,
exposure time $=1200$ sec (but 3 frames of 468–1016 sec), seeing
$<1.2^{\prime\prime}$, and transparency $>0.75$ for NB527, exposure time
$=1200$ sec, seeing $<1.2^{\prime\prime}$, and transparency $>0.76$ for NB718,
exposure time $=1200$ sec, seeing $<1.2^{\prime\prime}$, and transparency
$>0.9$ for NB973, and exposure time $=720$ sec, seeing $<1.2^{\prime\prime}$,
and transparency $>0.7$ for IB945. hscPipe generates several multiband
photometric catalogs, which we call “CHORUS PDR1 catalog.” The source
detection is based on the signal-to-noise ratio ($S/N$) within the PSF against
the background noise fluctuation (Bosch et al., 2018) and the detection
criterion is $5\sigma$, the same as the SSP PDR papers (Aihara et al., 2018b,
2019). The readers should refer to pipeline paper (Bosch et al., 2018) and the
SSP PDR2 paper (Aihara et al., 2019) for the detailed procedures of the data
reduction, source detection, and photometry. In the following, we describe
some specific points for the CHORUS data release.

The photometric zero-points for the CHORUS NBs were determined based on the BB
photometry of the Galactic stars in the Pan-STARRS1 (PS1) catalog (Chambers et
al., 2016) similar to the method for the HSC SSP (Aihara et al., 2018b, 2019).
The color terms translating PS1 BB magnitudes to HSC NB magnitudes were
estimated based on the Pickles stellar spectral templates (Pickles, 1998).
This seems work well, except for NB387, where a systematic zero-point offset
was found in Liang et al. (2020) (and see the last paragraph in this section).
The multiband photometry was conducted with the so-called priority order
(Bosch et al., 2018) of the filters, which was defined as $i,r,z,y,g$ for the
BB filters, followed by the order of NB921, NB816, NB973, NB718, NB527,
NB1010, NB387, and IB945 for the NB filters. The priority order of the filters
was used to determine the object positions.444This is the so-called forced
catalog based on multiband photometry at the positions in the most prioritized
band. The hscPipe makes another catalog based on photometry at the positions
in each band separately, called meas (or unforced) catalog (Aihara et al.,
2018b). We do not deal with the meas catalog in this paper because the
photometry may not give reliable colors owing to potentially different
positions in different bands. For the line emitters detected in a single NB
image but not detected in any other BB and NB images, photometry on the NB
image was conducted at the positions of the detections in the NB image.
However, for the line emitters that were also detected in other BB (and NB)
images, the photometry positions were forced to be the positions in the most
prioritized band among the images in which the objects were detected. In such
cases, photometry on the NB image, which includes the line flux, can be
underestimated if there are spatial offsets between the prioritized band and
NB positions. This would not be a problem for the bright objects that are
detected well both in the prioritized band and NB images; however, it might be
an issue for the objects that are marginally detected in the prioritized band
and whose positions in the band have a large uncertainty. Quantifying this
effect would need a large set of pipeline simulations that was reserved for
future line emitter analyses.

There are several different photometric magnitudes in the CHORUS PDR1
multiband catalog. In this paper, we do not recommend using cmodel magnitudes,
which represent the total flux densities obtained by the brightness profile
fitting (Bosch et al., 2018) and were considered representative magnitudes in
SSP PDR1 (Aihara et al., 2018b). This is because there is an issue of
erroneously bright cmodel magnitudes for some objects in SSP PDR2 (Aihara et
al., 2019) and a follow-up study (Hayashi et al., 2020). According to section
6.6.3 of the SSP PDR2 paper (Aihara et al., 2019), this problem is likely to
be caused by a failure in the deblending procedure in crowded regions of
objects. This problem can be severe in the HSC SSP UD footprint in the COSMOS
field, where the CHORUS observations were performed, because the very deep BB
depth yields a very high density of the detected objects.

We instead recommend using the undeblended_convolvedflux magnitudes for
estimates of total magnitudes.555There is another similar measurement called
convolvedflux, for which the source deblender algorithm in hscPipe works. On
the other hand, the source deblending process was turned off for
undeblended_convolvedflux. We have found that the two magnitudes of
undeblended_convolvedflux and convolvedflux are identical in most cases. These
measurements are based on the aperture magnitudes of the final coadd images
smoothed with a Gaussian function (see section 3.6 of the SSP PDR1 paper,
Aihara et al. (2018b)). The Gaussian smoothing size is defined as the
resultant FWHM of the point sources in the smoothed images, which is
$0.59^{\prime\prime}$, $0.84^{\prime\prime}$, $1.1^{\prime\prime}$, or
$1.3^{\prime\prime}$ (Aihara et al., 2019). This process produces a set of the
smoothed BB and NB images with the selected same PSF FWHM. Subsequently, the
flux densities of each object in all the smoothed (i.e., PSF-matched) images
are measured in a circular aperture of diameter size $1.1^{\prime\prime}$,
$1.5^{\prime\prime}$, $2.0^{\prime\prime}$, or Kron-size, and aperture
corrections are also applied assuming a point-source.666The amount of the
aperture correction can be found as undeblended_convolvedflux_X_Y_apcorr in
the catalog database, where X and Y are the numbers indicating the target
convolution size and the aperture size, respectively. This process is
performed for all the detected objects as a function of hscPipe (Aihara et
al., 2018b, 2019). These PSF-matched magnitudes yield better colors in crowded
fields (Aihara et al., 2018b), which is the most important feature to reliably
select LAEs in two-color diagrams. This procedure is very similar to the
method performed in previous studies with SExtractor (Bertin & Arnouts, 1996).
In this study, we adopt $1.5^{\prime\prime}$ ($2.0^{\prime\prime}$)-diameter
apertures on $0.84^{\prime\prime}$ ($1.1^{\prime\prime}$)-smoothed
images.777If the native PSF of a band is larger than the target smoothing
FWHM, any Gaussian smoothing is not applied to the band and simply the native
images are used for the aperture photometry (see section 3.6 of Aihara et al.
(2018b)). Such a case happened for NB387 in the $0.84^{\prime\prime}$ target
FWHM smoothing.

There are two significant known issues in the SSP PDR2 photometric catalog
(Aihara et al., 2019), and they are prevalent in the CHORUS PDR1 catalog also
produced by hscPipe 6.7. The first one is that the uncertainties of the PSF-
matched magnitudes are underestimated (section 5.8.11 of the SSP PDR1 paper,
Aihara et al. (2018b)). This occurs because covariances are introduced by the
Gaussian smoothing process. This problem persists in the SSP PDR2 release
(Aihara et al., 2019). Therefore, we do not recommend using these cataloged
values of uncertainties for the PSF-matched magnitudes. Instead, we estimated
the uncertainties by measuring the rms values of the aperture flux densities
in the actual images. The limiting magnitudes provided in the next section are
based on these measurements.888The uncertainty in a magnitude is given by
$\delta m=(2.5/\ln 10)/(S/N)$. The signal-to-noise ratio, $S/N$, of each
object can be estimated from the ratio of undeblended_apertureflux in the
catalog database to the $1\sigma$ aperture flux density calculated from the
limiting magnitudes in the next section. The second issue is that there is a
systematic offset in the zero-point of NB387 of the SSP PDR2 release (Aihara
et al., 2019). This is due to the metallicity effect of the 4,000 Å break in
stellar spectra on $NB387-g$ color. hscPipe uses the Pickles spectral
templates based on Solar metallicity stars (Pickles, 1998) for zero-point
estimations. However, the actual stars used for the calibration seem to be
dominated by metal-poor halo stars because these stars are faint ($g\sim 20$)
and the HSC survey fields are located in high Galactic latitudes. This
template mismatch causes a systematic offset of the zero-point only for NB387.
A complete description and full analyses are found in appendix of Liang et al.
(2020). We did not correct the NB387 magnitudes in the CHORUS PDR1 catalog but
recommend users to apply a 0.45 mag subtraction correction to the NB387
magnitudes in the catalog, as recommended by the HSC SSP team.999https://hsc-
release.mtk.nao.ac.jp/doc/index.php/known-problems-2/#hsc-link-10

##  4 Imaging data quality

###  4.1 Definition of masked areas

Figure 2: Masked area (gray shade) in NB527 image as an example. HSC SSP UD
COSMOS, tract 9813, is divided into $9\times 9$ patchs as indicated by
lattice. patch numbers are indicated at four corners.

We defined the masked areas in each CHORUS NB image based on the flags from
hscPipe and the visual inspection conducted by one of the authors. Fig. 2
shows the masked area of the NB527 image as an example. Pixels in each image
that satisfied the following conditions of the hscPipe flags were selected as
masked pixels: pixelflags_bright_object is True (pixels affected by bright
objects) or pixelflags_saturatedcenter is True (pixels affected by count
saturation). In addition to these pixels, we also masked the pixels affected
by the halos of bright stars out. Generally, these halos are more prominent in
NB images than in BB images probably owing to the multilayer interferometric
thin film coating of NBs. We supplementary set larger circular (sometimes
elliptical) masks to cover these bright stars’ halos if the pixels with the
above flags do not cover sufficiently large areas. One of the authors (S.Y.)
selected these pixels by eyes. The edge of the FoV was also defined by eyes by
the same author to avoid lower S/N regions. The effective survey area of each
NB was calculated from the total number of non masked pixels in the image and
is listed in Table 3. The exact positions of the masked pixels are available
as image files in a FITS format.

###  4.2 Sizes of point spread functions

Figure 3: FWHMs of PSF and their spatial variation for NB387 (top left), NB527
(top right), NB718 (middle left), NB973 (middle right), and IB945 (bottom).
Black areas indicate patches that have no effective area. Grey areas indicate
patches where there are insufficient number of stars for PSF FWHM measurement
owing to small effective area.

We measured a representative FWHM of the PSF in each patch of the CHORUS NB
images using SExtractor101010http://www.astromatic.net/software/sextractor ver
2.19.5 (Bertin & Arnouts, 1996). We adopted a median of the FWHM_IMAGE
measured by SExtractor for stellar-like objects, which were not in the masked
areas, as the representative FWHM of the PSF. Stellar-like objects were
selected depending on the measurements of SExtractor as those satisfying the
following three criteria: (1) MAG_AUTO in a range of [$18.0,22.0$] for NB387
and NB527, [$18.0,21.0$] for NB718 and NB973, and [$19.0,21.0$] for IB945, (2)
ELONGATION $<1.2$ (i.e., nearly circular shape), and (3) FLAG $<4$ (i.e., not
located in a bad position, such as saturated or truncated pixels; see Bertin &
Arnouts (1996) for the details). If there were insufficient number of stellar-
like objects in a patch because of an extremely small non masked area, we did
not measure the FWHM of the PSF. The measured FWHMs and their spatial
variations are shown in Fig. 3, and the values of the area-weighted average
and the central patch, 404, are listed in Table 3. The FWHM values range from
$1^{\prime\prime}$ to $0.6^{\prime\prime}$, depending on the band. The spatial
variation in the FWHM values in each NB is as small as $<0.02^{\prime\prime}$,
demonstrating the excellent stability of the image quality across the entire
FoV of the HSC.

###  4.3 Limiting magnitudes

Figure 4: Five-$\sigma$ limiting magnitudes and their spatial variation for
NB387 (top left), NB527 (top right), NB718 (middle left), NB973 (middle
right), and IB945 (bottom). Black areas indicate patches that have no
effective area. Grey areas indicate patches where there are insufficient non-
masked pixels for limiting magnitude measurements. Aperture size is
$1.5^{\prime\prime}$ in diameter.

We measured the limiting magnitudes in each patch of the CHORUS NB images by
conducting aperture photometry at random sky positions with Python packages,
Astropy111111https://www.astropy.org//photutils121212https://photutils.readthedocs.io/en/stable/.
A large number of random positions (10,000 as default, and 5,000 or 1,000 at
the edge of the FoV depending on the available area) were prepared in each
patch by avoiding the masked pixels and the pixels of the objects detected by
SExtractor in advance. If the non masked area in a patch was less than
$1~{}\mathrm{arcmin}^{2}$, we did not measure the limiting magnitudes. For
convenience, we measured the limiting magnitudes with two aperture sizes
($1.5^{\prime\prime}$ and $2.0^{\prime\prime}$ in diameter) in each patch of
each CHORUS NB image. We estimated the background brightness locally by
adopting a median count in an annulus of $1.5^{\prime\prime}$
($2.0^{\prime\prime}$) width and $2.5^{\prime\prime}$ ($3.0^{\prime\prime}$)
inner diameter set around the $1.5^{\prime\prime}$ ($2.0^{\prime\prime}$)
aperture and subtracted it from the aperture count as a correction for the
background contribution. The standard deviation, $\sigma$, was obtained from
the histogram of the background-subtracted aperture counts by fitting a
Gaussian function. Note that we did not apply any aperture correction to the
counts. The $5\sigma$ values of the area-weighted average and those in the
central patch, 404, for the two aperture sizes are listed in Table 3. The
spatial variation in the $5\sigma$ values for the
$1.5^{\prime\prime}$-diameter aperture case are shown in Fig. 4. We can see a
radial dependence of the limiting magnitudes; it is $\sim 1$ mag shallower at
the outer edge compared with that at the center. The patch, 403, shows a
shallower depth than the radial trend, which was also reported in Hayashi et
al. (2020). This is probably because a half of the four channels in a CCD chip
(SDO-ID=0_20/DET-ID=33) close to the patch center was unavailable since
November-December 2016 (see the CCD information page of HSC on Subaru
Telescope
website131313https://www.naoj.org/Observing/Instruments/HSC/ccd.html) and the
dithering amount was too small to compensate the low-sensitivity area.

###  4.4 Completeness

Figure 5: Detection completeness of NB387 (top left), NB527 (top right), NB718
(middle left), NB973 (middle right), and IB945 (bottom). Cyan, blue, red, and
green points with error-bars denote results for patches 202, 303, 404, and
606, respectively. In panel of NB973, black solid line indicates result of
Itoh et al. (2018). We also display $5\sigma$ limiting magnitudes measured
with $2.0^{\prime\prime}$-diameter aperture (not total magnitudes) in patch
404 by vertical magenta dashed line in each panel. These results are obtained
with undeblended_convolvedflux magnitudes; however, essentially same results
are obtained with convolvedflux magnitudes.

We estimated the detection completeness based on a simulation of embedding and
recovering numerous mock galaxies in actual CHORUS NB images using hscPipe,
Astropy, and GALSIM (Rowe et al., 2015)141414https://github.com/GalSim-
developers/GalSim. These mock galaxies were assumed to have an intrinsic
brightness profile described by a circular Sersic profile with index $n=1.5$
and a half-light radius of $1$ pix of the HSC images ($0.17^{\prime\prime}$).
The adopted radius corresponds to $1.4$–$0.9$ physical kpc for $2<z<7$ and
very consistent with those of typical LBGs/LAEs (Shibuya et al., 2015;
Kawamata et al., 2018). When embedding the mock galaxies into each patch
image, we convoluted the brightness profile with the PSF of the image. Because
the intrinsic sizes of the mock galaxies were very small compared to the PSF
size, the embedded profiles were similar to the PSF but slightly extended. The
locations to embed the mock galaxies were chosen randomly, not avoiding the
actual objects, to consider the cases in which the extended and bright
galaxies overlap and hide faint ones. We considered nine intrinsic magnitudes
of the mock galaxies in a range of $\pm 2.0$ magnitudes with a 0.5 magnitude
step around the $5\sigma$ limiting magnitude. The number of the input mock
galaxies was 500 for each intrinsic magnitude in each patch of each band. We
ran hscPipe to detect the mock galaxies and measure the magnitudes. The
criteria for successful recovery were detection within a radius of
$0.5^{\prime\prime}$ from the embedded location and a magnitude difference of
less than 0.5 magnitude. We adopted the undeblended_convolvedflux magnitude
($0.84^{\prime\prime}$ FWHM convolution and $\phi 1.5^{\prime\prime}$ aperture
case, except for NB387, where $1.1^{\prime\prime}$ FWHM convolution and $\phi
2.0^{\prime\prime}$ aperture case is adopted) as the output total magnitude
for Fig. 5; however, the results with the convolvedflux magnitude were the
essentially same. Note that the undeblended_convolvedflux and convolvedflux
magnitudes are aperture-corrected by a PSF model and equivalent to the total
magnitude for the point sources. The detection completeness is defined as the
ratio of the number of successfully recovered galaxies to that of embedded
mock galaxies. The mock galaxies placed in the masked areas were excluded from
the analysis in this final step. To moderate the computation time, we
conducted this experiment in only 4 patches of 202, 303, 404, and 606, instead
of all the 81 patches.

Fig. 5 shows the results of the simulations of the detection completeness. We
find that the completeness is $\gtrsim 60\%$ at the $5\sigma$ limiting
magnitude ($\phi 2.0^{\prime\prime}$ not aperture-corrected) in each patch,
which is reasonable. Even at magnitudes brighter than the limiting magnitudes,
the completeness is only 80–95% and does not reach 100% because of the hiding
effect by bright objects. For NB527, the completeness is relatively lower than
that of other bands. This seems to be caused by the source confusion due to
the very deep depth with a moderate PSF size. Indeed, the surface number
density of the detected objects in NB527 up to a $5\sigma$ limit of 26.46 AB
($\phi 2.0^{\prime\prime}$) corresponds to an areal fraction of $\sim 13$%
even if we assume a circular area with a radius equal to the PSF FWHM size
($r=0.82^{\prime\prime}$) per object. For NB973, we also present the average
completeness over all the patches estimated similarly but independently by
Itoh et al. (2018); it is slightly lower than ours but is broadly consistent.
Actually, Itoh et al. (2018) used hscPipe version 4.0.5, and their
$5\sigma$-limiting magnitude in the $1.5^{\prime\prime}$-diameter aperture of
25.0 was 0.4 magnitude shallower than that of this study.

##  5 Number counts

Figure 6: Source number counts in NB387 (top left), NB527 (top middle), NB718
(top right), NB973 (bottom left) and IB945 (bottom right). For each band,
upper panel shows histogram of actual numbers of detected sources and bottom
panel shows number density per magnitude per square arcminutes. Empty
histogram indicates magnitude range where detection completeness is less than
$\sim 10$% and probability of spurious detections may be high. Number counts
taken from literature are also shown in each panel for comparison. For NB387,
we show both number counts with/without zero-point correction for catalog
magnitudes produced by hscPipe version 6.7. References of literature data:
K04: Kashikawa et al. (2004), O08: Ouchi et al. (2008), O10: Ouchi et al.
(2010), Y12: Yamada et al. (2012), N12: Nakajima et al. (2012), S19: Sawicki
et al. (2019).

For the verification of the CHORUS PDR1 catalog, we calculated the source
number counts in the CHORUS NBs and compared the results with those reported
in the literature. We adopted the undeblended_convolvedflux magnitudes
($0.84^{\prime\prime}$ FWHM convolution and $\phi 1.5^{\prime\prime}$ aperture
case, except for NB387, where $1.1^{\prime\prime}$ FWHM convolution and $\phi
2.0^{\prime\prime}$ aperture case is adopted) as the total magnitude of the
objects and excluded the objects and area in the masked regions. The total
magnitudes for each object were corrected for the Galactic extinction using
the values listed in the CHORUS PDR1 catalog which are estimated from Schlegel
et al. (1998) dust maps (see also HSC SSP PDR papers Aihara et al. (2018b,
2019)). These extinction magnitudes are small; for instance, $\sim 0.1$ mag
even in NB387 in which the extinction effect is the severest. We also applied
a catalog flag, forced.merge_peak_XXXX is True, where XXXX $=$ n387, n527,
n718, i945, or n973, to ensure that we count only the sources detected in the
NB that we are considering. Otherwise, the number count included the sources
that were not actually detected in the NB because hscPipe lists all the
sources detected in any single band in the catalogs. Because the BB images of
the HSC SSP are deeper than the CHORUS NB images, numerous faint BB sources,
which are not detected in any of the CHORUS NBs, are also listed in the CHORUS
PDR1 catalog.

Fig. 6 shows the number count measurements. We only present the data points
for those magnitudes at which the completeness (see Fig. 5) is larger than
10%. We also display the literature data of both the BBs and NBs whose
wavelengths are close to those of each NB. There are excellent agreements
between all the CHORUS number counts and the literature data. For example, the
number counts of NB718, NB973, and IB945 present excellent agreement with the
data of Subaru/Suprime-Cam ($i$ from Kashikawa et al. (2004) for NB718, and
$z$ from Kashikawa et al. (2004) and NB921 from Ouchi et al. (2010) for NB973
and IB945). The NB527 number count also agrees with those of Subaru/Suprim-Cam
NB503 from Ouchi et al. (2008) and $V$ from Kashikawa et al. (2004); however,
there are slight differences from those in bluer bands, like $B$ from
Kashikawa et al. (2004) and NB497 from Yamada et al. (2012). Because the
slopes of the number counts reported in the literature are steeper at shorter
wavelengths, the CHORUS results seem to follow this trend. For NB387 after the
zero-point correction (see sec. 3), the number count data agree with those of
Suprime-Cam/NB387 from Nakajima et al. (2012), Suprime-Cam/$B$ from Kashikawa
et al. (2004), and CFHT/MegaCam/$u$ from Sawicki et al. (2019) at magnitudes
fainter than 22. At brighter magnitudes, the NB387 data of ours and Suprime-
Cam lie between the two BB literature data, which is reasonable given the
trend mentioned above, because the wavelength of NB387 is indeed between those
of the $B$\- and $u$-bands. The zero-point uncorrected NB387 number count is
less than those reported in the literature data. These results suggest the
necessity and validity of the zero-point correction.

##  6 How to use the catalog and example use cases of the CHORUS data

The CHORUS PDR1 catalog is available at the Catalog Archive Server
(CAS)151515https://hsc-release.mtk.nao.ac.jp/datasearch/ of the HSC-SSP. An
example SQL query to obtain a list of the coordinates, patch, the Galactic
extinction in NB387, $\phi 2.0^{\prime\prime}$ aperture NB387 magnitudes,
NB387 total magnitudes (undeblended_convolvedflux with $1.1^{\prime\prime}$
FWHM convolution and $\phi 2.0^{\prime\prime}$ aperture), and the
corresponding aperture corrections for the sources detected in NB387 is as
follows:

SELECT

object_id, ra, dec, patch, a_n387

n387_undeblended_apertureflux_20_mag

n387_undeblended_convolvedflux_2_20_mag

n387_undeblended_convolvedflux_2_20_apcorr

FROM

s18a_chorus.forced

LEFT JOIN s18a_chorus.forced3 USING (object_id)

LEFT JOIN s18a_chorus.forced6 USING (object_id)

WHERE

tractSearch(forced.object_id, 9813)

AND forced.nchild = 0

AND forced.detect_ispatchinner IS True

AND forced.merge_peak_n387 IS True

AND forced.n387_pixelflags_saturatedcenter IS False

AND forced.n387_pixelflags_bright_object IS False

The CHORUS PDR1 (forced) catalog consists of 7 files of s18a_chorus.forced,
s18a_chorus.forced2, …, s18a_chorus.forced7. The FITS files of the masked
areas (Fig. 2), spatial maps of PSF sizes (Fig. 3) and limiting magnitudes
(Fig. 4), numerical data of detection completeness simulations (Fig. 5), and
numerical data of measured number counts (Fig. 6) are also available through
the website161616https://hsc-release.mtk.nao.ac.jp/doc/index.php/chorus/.

In the following, we describe four specific studies ongoing with the CHORUS
data and other ancillary studies including results published so far.

###  6.1 Lyman continuum survey of galaxies and AGNs

In the CHORUS project, we are performing a LyC survey for galaxies and AGNs at
$z\simeq 3.3$ and 4.9 using NB387 and NB527, respectively (see Fig. 1). The
samples are mainly the LAEs selected by NB527 ($z\simeq 3.3$) and NB718
($z\simeq 4.9$). An average LyC-to-UV flux density ratio, or $f_{\rm esc}$, of
the LAEs will be estimated by stacking analysis. Combining the LyC-to-UV
ratios corrected for the IGM transmission and the observed UV luminosity
densities, we can estimate the LyC luminosity densities and examine whether
galaxies dominate the LyC emissivity at $z\sim 3$–5. We can also detect the
LyC from individual LAEs and AGNs. The number of such LyC galaxies at $z>3$ is
still limited (e.g., Iwata et al. (2009); Vanzella et al. (2012, 2015);
Steidel et al. (2018); Iwata et al. (2019)). This program will increase that
number significantly. Follow-up spectroscopy of these reliable LyC galaxies
allows an $f_{\rm esc}$ calibration from the non-ionizing properties, such as
a high [O iii]/[O ii] ratio (Nakajima & Ouchi, 2014; de Barros et al., 2016;
Nakajima et al., 2020). Once we establish the relation between the LyC
emissivity (or $f_{\rm esc}$) values and the properties of galaxies observable
at longer wavelengths at $z\lesssim 5$, we can estimate $f_{\rm esc}$ of the
galaxies in the epoch of reionization ($z>6$). In this epoch, direct LyC
observations are impossible owing to the severe absorption caused by the
neutral hydrogen atoms in the IGM (Inoue & Iwata, 2008; Inoue et al., 2014).

###  6.2 Surveys of faint AGNs as dual-emitters

Using NB718 and NB921, we can select a population of faint AGNs at $z\simeq
4.9$ as Ly$\alpha$-C iv dual emitters if we appropriately treat the effects of
broad lines whose line widths are broader than the NB widths (Fig. 1). This
selection method is unique because these faint AGNs with a magnitude range
similar to that discussed by Giallongo et al. (2015) are difficult to be
isolated from the LBGs by any combination of BB colors. Moreover, our NB527
data allows the direct measurement of the LyC of these faint AGNs. The faint-
AGN population reported by Giallongo et al. (2015) can reproduce the LyC
emissivity required to keep the Universe ionized at $z\sim 5$–6 if $f_{\rm
esc}=1$ (Madau & Haardt, 2015). We examine if this is the case not only by
measuring the faint-AGN LF but also by measuring the $f_{\rm esc}$ of this
population. Simultaneously, we measure $f_{\rm esc}$ of galaxies at the same
redshift and study their contribution directly. Subsequently, we identify the
population that dominates the cosmic LyC emissivity at $z\sim 3$–5 and infer
the source of the cosmic reionization at $z>6$.

###  6.3 Surveys of Pop III-dominated galaxies

Pop III stars are expected to have high LyC emissivity and may play a
significant role in the early phase of reionization (e.g., Sokasian et al.
(2004)). However, observational evidence for this stellar population is still
inconclusive (e.g., Kashikawa et al. (2012); Rydberg et al. (2015); Vanzella
et al. (2020)), and its characteristics, e.g., the initial mass function and
the LyC emissivity, are unknown. Theoretically, Pop III star clusters can be
formed even at $z\sim 2$–3, depending on the efficiency of the IGM metal-
enrichment (e.g., Tornatore et al. (2007); Johnson (2010); de Souza et al.
(2011)). Indeed, pristine ($Z<10^{-4}$) gas clouds, from which Pop III stars
may form, are found at $z\simeq 3$ (e.g., Fumagalli et al. (2011)).
Identifying the epoch of the termination of a metal-free star formation is
also a very important problem. The He ii emission line can be an indicator of
Pop III stars (e.g., Tumlinson et al. (2001); Schaerer (2003)). Using our
well-tuned set of NBs, we can search for Ly$\alpha$–He ii dual emitters at
$z\simeq 2.2$, 3.3, and 4.9 (see Table 2 and Fig. 1). Such a dual emitter
search was performed by Nagao et al. (2008) with the Suprime-Cam for $z\sim
4$. We update the upper limit on the He ii line luminosity density or the Pop
III star formation rate density by Nagao et al. (2008) with a 7 times larger
area and up to $\sim 1$ mag deeper imaging data at a wider redshift range of
$z=2$–5. This will enable us to constrain the metal-enrichment efficiency in
the IGM stronger than before.

###  6.4 Mapping spatial distributions of ionized bubbles

Because Ly$\alpha$ photons are sensitive to $x_{\rm HI}$, the distribution of
the LAEs depends on both $x_{\rm HI}$ and the large-scale structure (LSS).
However, LBGs are selected by the continuum and are not very sensitive to
$x_{\rm HI}$ but simply trace the LSS. If we normalize the number density of
the LAEs for each location by that of the LBGs, we can isolate the spatial
distribution of $x_{\rm HI}$; we can visualize the $x_{\rm HI}$ map directly
from the LAE-to-LBG density ratio. An essential point is to select LBGs with a
similar redshift to the NB-selected LAEs whose redshift variation is as small
as $\Delta z\simeq 0.1$. Although such an LBG selection is not feasible by BB
filters, we can reach $\Delta z\simeq 0.3$ using an intermediate filter, IB945
for redshifts around $z=6.6$ and 7.0. From the spatial variation of the
observed number density ratio, we can visualize an $x_{\rm HI}$ map far ahead
of the future 21 cm experiments, such as the SKA. Such an $x_{\rm HI}$ mapping
opens a new pathway to examine the ionization topology, for example, allowing
the measurements of the ionized bubble size directly.

###  6.5 Ancillary sciences

Very wide (1.6 deg2) and very deep ($\gtrsim 0.1L_{*}$) LAE samples at
$z\simeq 2.2$, 3.3, 4.9, 6.8, and 7.0 are obtained by this program. An LAE LF
at $z=7.0$ has already been published as the CHORUS paper II (Itoh et al.,
2018) that reports a very similar LF shape to those at $z=5.7$ and 6.6 with a
small overall decrement compared to the lower-$z$ ones. This indicates that
the reionization process does not alter the shape of the LAE LF in contrast to
a previous claim of a bright-end hump (Zheng et al., 2017). A comprehensive
LAE search in the CHORUS data in conjunction with the HSC SSP data is ongoing,
adopting a machine learning technique (Ono, Y. et al. in preparation). A study
of intensity mapping of Ly$\alpha$ emission is also ongoing (Kikuchihara, S.
et al. in preparation). More LAE related studies including environmental ones
and optical emission line properties in the near-infrared band are also
ongoing. We are also searching for spatially extended LAEs — Ly$\alpha$ blobs
— in the imaging data. A result of a Ly$\alpha$ blob survey at $4.9\leq z\leq
7.0$ has been published recently as the CHORUS paper III (Zhang et al., 2020)
that reports a Ly$\alpha$ blob at $z\simeq 7.0$, the highest-$z$ blob found so
far. [O ii], [O iii], H$\beta$, and H$\alpha$ emitters at various redshifts
are also studied with the CHORUS data in conjunction with the HSC SSP data
(Hayashi et al., 2020) and Spitzer data (Harikane et al., 2018). More line
emitter studies including AGN surveys will be performed in future. The CHORUS
PDR1 data will be useful for various studies performed all over the world. We
strongly encourage the readers’ own studies using the dataset.

##  7 Summary

In this study, we conducted a deep imaging survey using a set of narrow-band
(NB) and intermediate-band (IB) filters, named as Cosmic HydrOgen Reionization
Unveiled with Subaru (CHORUS), with the Hyper Suprime-Cam (HSC) equipped on
the Subaru Telescope. The filter set used in the survey is shown in Figure 1.
The wavelengths, NB387, NB527, NB718, NB973, and IB945, summarized in Table 2,
were chosen in a very well-organized manner to maximize the scientific
outcomes when the filters were used in combination with another NB, NB921,
from the Subaru Strategic Program for HSC (HSC SSP). The observations were
performed on 18 nights during the period from January 2017 to December 2018 in
an intensive program of the Subaru Telescope. The observing field was the
COSMOS field (Scoville et al., 2007). The data reduction, source detection,
and multiband photometry were conducted using hscPipe, the official pipeline
software for the HSC developed by the HSC SSP team (Bosch et al., 2018). The
hscPipe version used was 6.7, the same as that used for HSC SSP public data
release (PDR) 2 (Aihara et al., 2019). Because there is a known problem for
the cmodel magnitudes in this version, we recommended using the
undeblended_convolvedflux magnitudes instead. The imaging data qualities were
examined thoroughly in a spatially dependent manner, as shown in Figures 3 and
4. For each NB/IB, typical values of the size of point spread functions,
$5\sigma$ limiting magnitude, and survey area excluding the carefully defined
masked regions (see Figure 2 as an example) are summarized in Table 3. An
extensive set of mock observation simulations was performed to estimate the
source detection completeness, as shown in Figure 5. We checked the source
number counts and compared them with previous studies in Figure 6. An
excellent agreement with the literature data was obtained in each NB/IB. All
the images and photometric catalogs are publicly available through the HSC SSP
database. This data release is called CHORUS PDR 1.

The CHORUS NB/IB filter development was supported by JSPS KAKENHI Grant
Numbers 23244033 (KS: NB387), 24244018 (II: NB527), 23244025 (MO: NB921 and
NB973), and 23684010 (AKI: IB945), and by a special operating cost grant by
MEXT to Ehime University (YT: NB718). This work was also supported by JSPS
KAKENHI Grant Numbers 26287034 (AKI, KM), 17H01114 (AKI, KM, SY, MO, II, KS,
TN, NK, YO), 15H02064 (MO), and 17H01110 (MO).

The authors would like to thank the referee for constructive comments which
were useful to improve the quality of the manuscript. The authors would like
to acknowledge their specific contributions by the following people: Ryohei
Itoh and Ryota Kakuma for data reduction, Satoshi Kawanomoto and Masakazu A.
R. Kobayashi for filter development and inspection, Karin Shimodate for the
observations, and Masayuki Tanaka for public data release through the HSC SSP
database. The authors would also like to thank the following members of the
CHORUS project for their various contributions: Naoki Yasuda, Masayuki
Umemura, Masao Mori, Yasuhito Shioya, Toru Yamada, Ikkoh Shimizu, Kenji
Hasegawa, Tomoaki Ishiyama, Mana Niida, Akira Konno, Shiro Mukae, Andrea
Schulze, Genoveva Micheva, Masayuki Akiyama, Kenichi Tadaki, Michael Strauss,
Ryo Higuchi, Takashi Kojima, Masafusa Onoue, Yoshiki Matsuoka, Masatoshi
Imanishi, Rhythm Shimakawa, Takuya Hashimoto, Y.-T. Lin, John Silverman, Seiji
Fujimoto, Kohei Iwashita, Takuji Yamashita, Tomoko Suzuki, and Hisakazu
Uchiyama

The Hyper Suprime-Cam (HSC) collaboration includes the astronomical
communities of Japan and Taiwan, and Princeton University. The HSC
instrumentation and software were developed by the National Astronomical
Observatory of Japan (NAOJ), the Kavli Institute for the Physics and
Mathematics of the Universe (Kavli IPMU), the University of Tokyo, the High
Energy Accelerator Research Organization (KEK), the Academia Sinica Institute
for Astronomy and Astrophysics in Taiwan (ASIAA), and Princeton University.
Funding was contributed by the FIRST program from the Japanese Cabinet Office,
the Ministry of Education, Culture, Sports, Science and Technology (MEXT), the
Japan Society for the Promotion of Science (JSPS), Japan Science and
Technology Agency (JST), the Toray Science Foundation, NAOJ, Kavli IPMU, KEK,
ASIAA, and Princeton University.

This paper makes use of software developed for the Large Synoptic Survey
Telescope. We thank the LSST Project for making their code available as free
software at http://dm.lsst.org

This paper is based on data collected at the Subaru Telescope and retrieved
from the HSC data archive system, which is operated by Subaru Telescope and
Astronomy Data Center (ADC) at NAOJ. Data analysis was in part carried out
with the cooperation of Center for Computational Astrophysics (CfCA), NAOJ.

The Pan-STARRS1 Surveys (PS1) and the PS1 public science archive have been
made possible through contributions by the Institute for Astronomy, the
University of Hawaii, the Pan-STARRS Project Office, the Max Planck Society
and its participating institutes, the Max Planck Institute for Astronomy,
Heidelberg, and the Max Planck Institute for Extraterrestrial Physics,
Garching, The Johns Hopkins University, Durham University, the University of
Edinburgh, the Queen’s University Belfast, the Harvard-Smithsonian Center for
Astrophysics, the Las Cumbres Observatory Global Telescope Network
Incorporated, the National Central University of Taiwan, the Space Telescope
Science Institute, the National Aeronautics and Space Administration under
grant No. NNX08AR22G issued through the Planetary Science Division of the NASA
Science Mission Directorate, the National Science Foundation grant No.
AST-1238877, the University of Maryland, Eotvos Lorand University (ELTE), the
Los Alamos National Laboratory, and the Gordon and Betty Moore Foundation.

The authors would like to thank Editage (www.editage.com) for English language
editing.

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