# A massive quiescent galaxy in a group environment at $z=4.53$

Takumi Kakimoto Department of Astronomical Science, The Graduate University
for Advanced Studies, SOKENDAI, 2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan
National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo
181-8588, Japan  Masayuki Tanaka National Astronomical Observatory of Japan,
2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan  Department of Astronomical
Science, The Graduate University for Advanced Studies, SOKENDAI, 2-21-1 Osawa,
Mitaka, Tokyo 181-8588, Japan  Masato Onodera Subaru Telescope, National
Astronomical Observatory of Japan, National Institutes of Natural Sciences
(NINS), 650 North A’ohoku Place, Hilo, HI 96720, USA  Department of
Astronomical Science, The Graduate University for Advanced Studies, SOKENDAI,
2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan  Rhythm Shimakawa Waseda Institute
for Advanced Study (WIAS), Waseda University, 1-21-1, Nishi-Waseda, Shinjuku,
Tokyo 169-0051, Japan  Center for Data Science, Waseda University, 1-6-1,
Nishi-Waseda, Shinjuku, Tokyo 169-0051, Japan  Po-Feng Wu Institute of
Astrophysics, National Taiwan University, Taipei 10617, Taiwan  Department of
Physics and Center for Theoretical Physics, National Taiwan University, Taipei
10617, Taiwan  Physics Division, National Center for Theoretical Sciences,
Taipei 10617, Taiwan  Katriona M. L. Gould Cosmic Dawn Center (DAWN), Denmark
Niels Bohr Institute, University of Copenhagen, Jagtvej 128, DK-2200
Copenhagen N, Denmark  Kei Ito JSPS Research Fellow (PD)  Department of
Astronomy, School of Science, The University of Tokyo, 7-3-1, Hongo, Bunkyo-
ku, Tokyo, 113-0033, Japan  Shuowen Jin Cosmic Dawn Center (DAWN), Denmark
DTU Space, Technical University of Denmark, Elektrovej 327, DK-2800 Kgs.
Lyngby, Denmark  Mariko Kubo Astronomical Institute, Tohoku University, Aoba-
ku, Sendai 980-8578, Japan  Tomoko L. Suzuki Kavli Institute for the Physics
and Mathematics of the Universe (WPI), The University of Tokyo Institutes for
Advanced Study, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan  Sune
Toft Cosmic Dawn Center (DAWN), Denmark  Niels Bohr Institute, University of
Copenhagen, Jagtvej 128, DK-2200 Copenhagen N, Denmark  Francesco Valentino
European Southern Observatory, Karl-Schwarzschild-Str. 2, 85748 Garching,
Germany  Cosmic Dawn Center (DAWN), Denmark  Kiyoto Yabe Subaru Telescope,
National Astronomical Observatory of Japan, National Institutes of Natural
Sciences (NINS), 650 North A’ohoku Place, Hilo, HI 96720, USA

###### Abstract

We report on the spectroscopic confirmation of a massive quiescent galaxy at
$z_{\mathrm{spec}}=4.53$ in the COSMOS field with Keck/MOSFIRE. The object was
first identified as a galaxy with suppressed star formation at
$z_{\mathrm{phot}}\sim 4.65$ from the COSMOS2020 catalog. The follow-up
spectroscopy with MOSFIRE in the $K$-band reveals a faint [O II] emission and
the Balmer break, indicative of evolved stellar populations. We perform the
spectral energy distribution fitting using both the photometry and spectrum to
infer physical properties. The obtained stellar mass is high ($M_{*}\sim
10^{10.8}\,M_{\odot}$) and the current star formation rate is more than 1 dex
below that of main-sequence galaxies at $z=4.5$. Its star formation history
suggests that this galaxy experienced starburst at $z\sim 5$ followed by a
rapid quenching phase. This is one of the youngest quiescent galaxies at $z>3$
and is likely a galaxy in the process of being quenched. An unique aspect of
the galaxy is that it is in an extremely dense region; there are four massive
star-forming galaxies at $4.4<z_{\mathrm{phot}}<4.7$ located within 150
physical kpc from the galaxy. Interestingly, three of them have strongly
overlapping virial radii with that of the central quiescent galaxy ($\sim
70\,\mathrm{kpc}$), suggesting that the over-density region is likely the
highest redshift candidate of a dense group with a spectroscopically confirmed
quiescent galaxy at the center. The group provides us with an unique
opportunity to gain insights into the role of the group environment for
quenching at $z\sim 4$ \- $5$ corresponding to the formation epoch of massive
elliptical galaxies in the local Universe.

Galaxy evolution (594) — High-redshift galaxies (734) — Galaxy quenching
(2040) — Quenched galaxies (2016) — Galaxy environments (2029) — Galaxy groups
(597)

††journal: ApJ††facilities: Keck:I (MOSFIRE)††software: Astropy (Astropy
Collaboration et al., 2013, 2018), Matplotlib (Hunter, 2007), MOSFIRE DRP,
MIZUKI (Tanaka, 2015), numpy (Harris et al., 2020), Prospector (Johnson et
al., 2021), Python-fsps (Conroy et al., 2009; Conroy & Gunn, 2010), emcee
(Foreman-Mackey et al., 2013)

##  1 Introduction

Massive elliptical galaxies in the local Universe are known to be dominated by
old stellar populations with little cold gas and dust, exhibiting no active
ongoing star formation (e.g., Young & Scoville, 1991; Gallazzi et al., 2005;
Bellstedt et al., 2020). Since these massive galaxies likely have played a
major role in cosmic star formation in a high redshift Universe, it is very
important to study their formation mechanisms. The star formation histories
(SFHs) of massive elliptical galaxies inferred from spectroscopic observations
show that they experienced an intense burst of star formation in the early
Universe and then rapidly quenched (stopped their star formation, Nelan et
al., 2005; Thomas et al., 2005, 2010; Renzini, 2006). However, the physical
drivers of their starburst and subsequent quenching remain unclear, which is
one of the most outstanding issues in the field of galaxy formation and
evolution.

To elucidate these problems, a lot of efforts have been put into the search
for progenitors of local elliptical galaxies at high redshifts and examine
them closer to the time of quenching. Over the last $\sim 2$ decades, massive
quiescent galaxies with no significant ongoing star formation at $z\sim 2$,
which are likely the progenitors of local ellipticals, have been extensively
studied (e.g., Kriek et al., 2009; Whitaker et al., 2012; Toft et al., 2012;
Belli et al., 2016, 2019; Stockmann et al., 2019). These galaxies have very
large stellar masses $(M_{*}>10^{11}\,M_{\odot})$ and compact sizes
$(R_{e}<2\,\mathrm{kpc})$ compared to their counterparts in the local
Universe. Also, the previous studies infer SFHs of these galaxies and confirm
the evidence of starburst at $z>3$ and short quenching timescale.

Thanks to the recent development of sensitive near-infrared (NIR)
spectrographs, massive quiescent galaxies at up to $z\sim 4$ are
spectroscopically confirmed (e.g., Glazebrook et al., 2017; Schreiber et al.,
2018; Forrest et al., 2020; Valentino et al., 2020; Nanayakkara et al., 2022;
Antwi-Danso et al., 2023). This epoch is consistent with the formation epoch
inferred from the local elliptical galaxies (Thomas et al., 2010), and the
identification of massive quiescent galaxies at $z>4$ is critical to
understand their quenching mechanism. The number of sources confirmed at $z>4$
is still relatively limited (Tanaka et al., 2019; Carnall et al., 2023a), but
deep ground-based observations and new JWST spectroscopy are about to change
the landscape. Also, recent cosmological simulations have difficulties in
reproducing these galaxies (e.g., Schreiber et al., 2018; Cecchi et al., 2019;
Merlin et al., 2019; Valentino et al., 2020). Observational confirmations of
massive quiescent galaxies at $z>4$ are an important step to constrain the
galaxy formation models.

In terms of the environment in which galaxies reside, it is known that
elliptical galaxies dominate clusters of galaxies in the nearby Universe
(e.g., Dressler, 1980). This morphology-density relation shows that the
surrounding environment may affect physical properties of galaxies. Actually,
massive quiescent galaxies dominate high-density environments at $z<1$ (e.g.,
Gómez et al., 2003; Peng et al., 2010; Kawinwanichakij et al., 2017). These
environments are basic components of large-scale structures in the nearby
Universe, and examining the formation process by observing the high redshift
Universe is crucial. At $z>2$, previous studies confirm “proto-clusters” which
are over-density regions of galaxies and are considered progenitors of local
clusters (e.g., Toshikawa et al., 2014; Lemaux et al., 2018). However, these
proto-clusters are often identified using star-forming galaxies as a tracer,
and there are only a few systems with (confirmed) quiescent galaxies (e.g.,
Kubo et al., 2021, 2022; Kalita et al., 2021; McConachie et al., 2022; Ito et
al., 2023). To understand the role of the environment in galaxy quenching at
high redshift, it is crucial to examine more (proto-)clusters and look for a
sign of environmental effects in the act.

In this paper, we report the confirmation of a massive quiescent galaxy at
$z=4.53$ in the COSMOS field using the Keck/MOSFIRE spectrograph. The galaxy
is located in a group environment, and we discuss a possible role of
environment at this high redshift for the first time. This paper is structured
as follows. First, we introduce the target selection and spectroscopic follow-
up observation in Section 2. In Section 3, physical properties of the
quiescent galaxy inferred from spectral energy distribution (SED) fitting are
summarized. Then, we discuss the galaxy’s surrounding environment as well as
its possible formation scenarios in Section 4. Finally, we conclude the paper
in Section 5. We assume Chabrier (2003) initial mass function (IMF) and a flat
$\mathrm{\Lambda CDM}$ cosmology with
$H_{0}=70\,\mathrm{km\,s^{-1}\,Mpc^{-1}},\Omega_{m}=0.3$, and
$\Omega_{\Lambda}=0.7$. All magnitudes are in the AB system (Oke & Gunn,
1983).

##  2 Observation

###  2.1 Target Selection

Following the successful confirmation of the $z=4.01$ quiescent galaxy in the
Subaru/XMM-Newton Deep Field (Tanaka et al., 2019), we searched for massive
quiescent galaxy candidates at $z>4$ in the COSMOS field. The COSMOS field is
$\sim 2\,\mathrm{deg^{2}}$ and has been extensively observed from the X-ray to
the radio wavelengths, which allows us to obtain highly accurate photometric
redshifts (photo-$z$’s). As summarized in Ito et al. (2022), we applied our
photo-$z$ code (Tanaka, 2015) to the COSMOS2020 Classic catalog (Weaver et
al., 2022a). Our photo-$z$’s are confirmed to be accurate for massive
quiescent galaxies at $2<z<4$ ($\Delta z/(1+z_{\mathrm{spec}})=0.03$: Ito et
al., 2022).

Based on this photo-$z$ catalog, we applied the following cuts to select
quiescent galaxy candidates; (1) $z_{\mathrm{phot}}>4$ with little probability
of being at lower redshifts to ensure that the Balmer break is in the
$K$-band, (2) $M_{*}\gtrsim 5\times 10^{10}\,M_{\odot}$ so that the target is
sufficiently bright for us to trace its continuum, and (3) star formation rate
(SFR) inferred from the SED fitting is more than 1 dex below the star-forming
main sequence (Schreiber et al., 2015). The last criterion is effectively
similar to the rest-frame UVJ selection (Williams et al., 2009). After careful
visual screening, we identify a massive quiescent galaxy candidate at
$z_{\mathrm{phot}}\sim 4.65$ with these cuts. Its SED exhibits a strong Balmer
break, which suggests that the galaxy experienced an intense burst of star
formation in the recent past and that its SFR has been declining since then
(post-starburst phase). This object (COSMOS-1047519) is the subject of the
paper. We note that there are other quiescent galaxy candidates, but most of
them are very faint in the $K_{s}$-band (too high redshifts where the Balmer
break is outside of the $K_{s}$-band or suffer from the dust extinction). The
selected candidate is the brightest candidate after the selection.

###  2.2 Spectroscopic follow-up

We performed spectroscopic follow-up in the $K$-band using the MOSFIRE
spectrograph (McLean et al., 2010, 2012) on the Keck I telescope. We expected
to fully cover the entire Balmer break from the photo-$z$. The target is
rather faint with a $K_{s}$-band magnitude of $23.1\,\mathrm{mag}$, and a long
integration was required to identify absorption features. However, the weather
did not fully cooperate and we could observe roughly half of the allocated
time ($\sim 9$ hour on-source exposure). The observations were performed on 3
half nights in 2022 March and April. We took $\sim 100$ pairs of the ABBA
nodding with a 3 min exposure at each position. We nod $\pm 2^{\prime\prime}$
along the slit for good sky subtraction. We included two bright stars in the
mask to monitor the sky conditions (see below). The mean seeing was around
$0^{\prime\prime}.7$.

We reduced the data in the standard manner using the MOSFIRE Data Reduction
Pipeline (DRP)111https://keck-datareductionpipelines.github.io/MosfireDRP/ as
well as custom-designed code. We reduced each A/B pair using DRP (flat-
fielding, wavelength calibration, and background subtraction). The flux and
the FWHM of the bright stars in each exposure were used to evaluate the
observing conditions. We used the weight of flux/FWHM in the coaddition of the
spectra to give more weight to exposures taken under better conditions. Four
exposures were taken through thick clouds and were thus excluded from the
coadd.

We observed the A0V star (HD50046) as a spectrophotometric standard star on
the first night of the observation. We applied the flux calibration and
correction for the telluric absorption by comparing the alpha-Lyr spectrum
from HST/CALSPEC (Bohlin et al., 2014) and the observed standard star
spectrum. The CALSPEC spectrum was scaled to the standard star using the
$K_{s}$-band photometry from 2MASS.

We performed the optimal extraction (Horne, 1986) to extract the 1D spectra
from the 2D spectra. The spatial profile of the bright star spectrum was fit
by Gaussian, and it was used to extract the flux of the target galaxy. The
error spectrum was estimated using the standard deviation of the background
pixels in the same slit. Finally, the flux of the 1D spectrum is scaled to
match the observed photometry to correct for the slit loss.

###  2.3 Redshift confirmation

Figure 1 shows the observed 2D and 1D spectra re-binned over 5 pixels (10.8
Å). Due to the low S/N of the spectrum, we could not securely identify
absorption lines. For example, the median S/N at
$21000\,\mathrm{\AA}<\lambda<22000\,\mathrm{\AA}$ is only 1.4 per
$2.2\,\mathrm{\AA}$ (original resolution). However, the spectrum exhibits a
faint [O II]$\,\lambda\lambda 3727,3729$ emission with
$\mathrm{S/N_{peak}}\sim 5$. This [O II] line yields a spectroscopic redshift
of this source. We perform a Monte-Carlo run to fit the [O II] doublet with
two Gaussians and adopt the median as a point estimate and the 68% interval as
an uncertainty, $z_{\mathrm{spec}}=4.5313\pm 0.0005$. This redshift is
consistent with the photo-$z$ ($z_{\mathrm{phot}}=4.654^{+0.134}_{-0.104}$).
Based on this redshift estimate, we discuss detailed properties of the galaxy
in the next Section.

Figure 1: Keck/MOSFIRE $K$-band spectrum of COSMOS-1047519 smoothed over 5
pixels (10.8 Å). The top panel shows the two-dimensional spectrum, and the
bottom panel shows the one-dimensional spectrum (the blue line) and the
associated noise spectrum (the yellow line). The red line shows the best-fit
model spectrum from prospector using both the spectrum and photometry (see
Section 3).

##  3 Inferred physical properties

###  3.1 SED Fitting

Figure 2 shows the SED of the galaxy. The black points are the photometry from
the COSMOS2020 Classic catalog with 40 bands from $u$-band to IRAC ch4 (Weaver
et al., 2022a). The blue spectrum is the MOSIFRE spectrum, which shows the
prominent Balmer break, suggesting the post-starburst nature of this galaxy.
The spectrum fully covers the break feature as expected, and we can more
accurately infer its star formation history shown below.

Figure 2: The SED of the target. The black points and error bars show the
photometry from the COSMOS2020 catalog (Weaver et al., 2022a), and the blue
spectrum at $\sim 2\,\mathrm{\mu m}$ is the MOSFIRE spectrum. The red spectrum
is the best-fit model spectrum from prospector.

We fit the observed SED with prospector (Johnson et al., 2021). The MOSIFRE
spectrum is re-binned over 3 pixels to gain S/N (e.g., the median
$\mathrm{S/N}\sim 2.5$ per $6.5\,\mathrm{\AA}$ at
$21000\,\mathrm{\AA}<\lambda<22000\,$Å). The prospector code uses the Flexible
Stellar Population Synthesis model (Conroy et al., 2009; Conroy & Gunn, 2010)
to infer physical properties of the galaxy. We assume Chabrier (2003) IMF,
solar metallicity, and Calzetti et al. (2000) attenuation curve. The redshift
is fixed to the spectroscopic redshift in the fitting. As we detected the weak
[O II] line, we include nebular emission in the model (Fixed the ionization
parameter: $U=0.01$).

We assume two models of star formation history (SFH). One is a parametric SFH
model with a linear rise of SFR followed by an exponential decrease (“delayed
tau-model”, $SFR(t)\propto te^{-t/\tau}$). The parameter $\tau$ represents
decay timescale of star formation. We choose this model because it is widely
used and can compare with other quiescent galaxies from the literature. The
other model is a non-parametric SFH model, which allows the SFR in each age
bin to vary, thus gives more flexibility in the SFH modeling. There are
several priors to use this non-parametric model, and we use “log-mass prior”
and “Dirichlet prior” (Leja et al., 2017, 2019). The log-mass prior is the
most flexible model, but it could lead to a non-physical SFH such as causing
intense burst star formation just after the Big Bang. Thus, we also use the
Dirichlet prior, which forces the SFH to be smoother. As discussed below, the
estimated SFHs are similar regardless of the SFH model used.

For all models, we apply the Markov Chain Monte Carlo (MCMC) using emcee
(Foreman-Mackey et al., 2013) to infer the best-fitting parameters and their
associated errors. We use the TopHat prior to the input parameters such as
$\tau$, age, and $A_{V}$. To be specific, in the parametric SFH model, the
parameters are allowed to vary between
$0.001\,\mathrm{Gyr}<age<1.304\,\mathrm{Gyr}$, which is the age of the
Universe at $z=4.53$, $0<A_{V}<6$, and $0\,\mathrm{Gyr}<\tau<2\,\mathrm{Gyr}$.
For stellar mass, we use the log-uniform prior between
$10^{10}\,M_{\odot}<M_{*}<10^{12}\,M_{\odot}$. In the non-parametric SFH
model, we use the uniform prior to constrain the stellar masses of each age-
bin.

The best-fit model spectrum is shown in red in Figs. 1 and 2. The model
clearly shows the strong Balmer break in the $K$-band, which indicates that
the galaxy recently experienced a starburst and is now in the post-starburst
phase. There is relatively strong rest-frame UV continuum, implying that there
are residual star formation activities in the galaxy. This is thus likely a
young post-starburst and is likely being quenched. We will further discuss
this point using physical properties inferred from the SED fit in the
following subsection.

Table 1: Inferred physical properties of the quiescent galaxy (COSMOS-1047519)

$z_{\mathrm{phot}}$ | $z_{\mathrm{spec}}$ | Model | $\log{M_{*}/M_{\odot}}$ | $SFR_{\mathrm{SED}}$ | $A_{V}$ | $z_{\mathrm{form}}$ | $\tau$ | $SFR_{\mathrm{[O\,{\footnotesize II}]}}$
---|---|---|---|---|---|---|---|---
|  |  |  | [$M_{\odot}\,\mathrm{yr^{-1}}$] | [$\mathrm{mag}$] |  | [$\mathrm{Myr}$] | [$M_{\odot}\,\mathrm{yr^{-1}}$]
|  | Delayed tau | $10.72\pm 0.02$ | $8.97^{+3.35}_{-2.70}$ | $0.73\pm 0.06$ | $4.98^{+0.05}_{-0.04}$ | $22.9^{+2.8}_{-2.9}$ | $19.0^{+3.8}_{-2.9}$
$4.654^{+0.134}_{-0.104}$ | $4.5313\pm 0.0005$ | Log mass | $10.82\pm 0.03$ | $5.06^{+2.32}_{-1.97}$ | $0.39^{+0.07}_{-0.06}$ | $5.30^{+0.02}_{-0.04}$ | – | $11.9^{+2.7}_{-1.8}$
|  | Dirichlet | $10.80\pm 0.01$ | $12.8^{+10.4}_{-5.6}$ | $0.73^{+0.23}_{-0.15}$ | $5.00^{+0.08}_{-0.09}$ | – | $19.2^{+6.3}_{-4.3}$

Note. —

  1. 1.

Photometric redshift infrred from MIZUKI (Tanaka, 2015).

  2. 2.

Spectroscopic redshift from the Keck/MOSFIRE spectrum.

  3. 3.

Name of the star formation history model used in SED fitting (Johnson et al.,
2021).

  4. 4.

Inferred stellar mass.

  5. 5.

Star formation rate from the SED fitting averaged over
$10^{7.5}\,\mathrm{yr}$.

  6. 6.

$V$-band magnitude of dust attenuation from SED fitting.

  7. 7.

Formation redshift at which the galaxy formed 50% of total stellar mass.

  8. 8.

Quenching timescale only in the delayed tau-model.

  9. 9.

Star formation rate from the flux of the [O II] emission corrected for dust
attenuation.

###  3.2 Inferred physical properties and SFH

From the SED fit, we infer physical properties of the galaxy such as stellar
mass, star formation rate (SFR), dust optical depth, and star formation
history. These parameters are summarized in Table 1. We estimate the SFR from
the SED fits and also from [O II] fit using two Gaussians. We use the
following equation to convert the [O II] emission flux to the SFR (Kewley et
al., 2004; Schreiber et al., 2018).

$SFR_{\mathrm{[O\,{\footnotesize
II}]}}\,[M_{\odot}\,\mathrm{yr^{-1}}]=1.59\times
10^{-8}L_{\mathrm{[O\,{\footnotesize II}]}}\,[L_{\odot}].$ (1)

We correct for dust attenuation of $L_{\mathrm{[O\,{\footnotesize II}]}}$
using the dust optical depth from the best-fit model.

Figure 3 shows the location of the object on a SFR vs. stellar mass diagram.
We also plot the normal star-forming galaxies from ALPINE survey (Le Fèvre et
al., 2020; Béthermin et al., 2020; Faisst et al., 2020) for reference. The
galaxy is massive ($M_{*}\approx 6.0\times 10^{10}\,M_{\odot}$), and has a
very low SFR ($SFR\approx 10\,M_{\odot}\,\mathrm{yr^{-1}}$) averaged over
$10^{7.5}\,\mathrm{yr}$. The estimated SFR is more than 1 dex below the star-
forming main sequence (Schreiber et al., 2015). This supports our argument in
the previous subsection that the galaxy is a massive quiescent galaxy based on
Schreiber et al. (2018) criteria. The [O II]-based SFRs are higher than those
obtained by SED fitting, which we interpret as a contribution from active
galactic nuclei (AGN) as we discuss in Section 3.4 (the model spectrum cannot
reproduce [O II] either).

Figure 3: Stellar mass and SFR relation inferred from the three SFH models
(color-coded symbols) compared to the star-forming main sequence (the blue
line: Schreiber et al., 2015). The orange line shows the star-forming main
sequence shifted by -1 dex. Inferred SFRs from both SED and [O II] emission
corrected for dust are located around or below the orange line. The gray
points are the normal star-forming galaxies at $z_{\mathrm{spec}}\sim 4.5$
from the ALPINE survey (Le Fèvre et al., 2020; Béthermin et al., 2020; Faisst
et al., 2020). There are two ALPINE galaxies below the orange line, but the
one at $\log{(M_{*}/M_{\odot})}\sim 10.3$ has a contaminating galaxy nearby,
and the other one is possibly undergoing dust-obscured star formation (Faisst
et al., 2020). We also include massive star forming galaxies around the
quiescent galaxy (the black diamonds, see discussion in Section 4). Figure 4:
Inferred SFHs of the target; the black, blue, and red lines are the non-
parametric SFH model with log-mass prior, non-parametric model with Dirichlet
prior, and the delayed-tau model, respectively. The filled circles and
diamonds with the error bars indicate the epoch when the galaxy formed 50% and
80% of the stars, respectively (the colors correspond to the SFH models).

Figure 4 shows the inferred star formation history of the galaxy. All of the
SFH models are broadly consistent with each other; the galaxy experienced a
starburst at $z\sim 5$ and then rapidly quenched, which is consistent SFH of
massive elliptical galaxies (Thomas et al., 2010). The galaxy is young with a
stellar age of $180^{+18}_{-16}\,\mathrm{Myr}$ from delayed tau-model, and the
observed low SFR is consistent with the SFHs. Inferred physical parameters and
SFH are not significantly changed by the age bins of the non-parametric SFH
model. We conclude that this is a massive quiescent (or being quenched) galaxy
and is likely a progenitor of massive elliptical galaxies in the local
Universe.

The quiescence of the galaxy is also supported by the multi-wavelength data.
We look at the infrared to radio wavelengths to see a sign of dust-obscured
star formation activity. However, the object is not detected in FIR
($S/N_{\mathrm{IR}}\sim 1.25$,
$SFR_{\mathrm{IR}}<300\,M_{\odot}\,\mathrm{yr^{-1}}$ in “Super-deblended”
catalog: Jin et al., 2018) and radio ($f_{\mathrm{10\,\mathrm{cm}}}=6.3\times
10^{-4}\pm 2.8\,\mathrm{\mu Jy}$ in VLA 3GHz: Smolčić et al., 2017). The
object has not been observed by ALMA, and we do not have a strong constraint
on dust emission at this point.

###  3.3 Comparison to massive quiescent galaxies at $z>3$

An interesting aspect of our quiescent galaxy is that it is currently
experiencing ongoing suppression of star formation. The prominent Balmer break
suggests an evolved stellar population, while the remaining UV continuum as
well as the weak [O II] emission suggests that the galaxy is not completely
quenched yet (Figs. 1 and 2). The galaxy has a young luminosity-weighted age,
and we must be observing the galaxy close to its primary formation epoch.

Figure 5 shows the relationship between the formation redshift
$(z_{\mathrm{form}})$ and observed redshift $(z_{\mathrm{spec}})$ of massive
quiescent galaxies at $z_{\mathrm{spec}}>3$ collected from the literature. The
formation redshift is defined by the epoch at which the galaxy formed 50% of
total stellar mass and is roughly corresponds to the epoch at which the galaxy
experienced its peak star formation activity. This figure shows that massive
quiescent galaxies at $z>3$ have a wide range of formation epochs (also
confirmed from the QGs at $z<3$: summarized in Kalita et al., 2021; Tacchella
et al., 2022). Our galaxy is particularly young and its formation redshift is
close to the observed redshift. In addition, its formation redshift
($z_{\mathrm{form}}\sim 5$) coincides with the inferred formation epoch of
massive elliptical galaxies in the local Universe (Thomas et al., 2010). We
thus speculate that the galaxy is a forming (or just formed) progenitor of
nearby massive ellipticals and a detailed study of the galaxy may provide us
with a clue to the quenching physics. The other massive quiescent galaxies in
the figure are generally older and more time has elapsed between the formation
and observed epochs. For instance, Carnall et al. (2023a) confirm a massive
quiescent galaxy at $z_{\mathrm{spec}}=4.658$. Compared to this galaxy,
COSMOS-1047519 is younger and has a higher SFR and larger dust attenuation.
However, the stellar mass and the peak SFR in its SFH are similar. Therefore,
our galaxy is similar to the Carnall et al. (2023a) galaxy but we are closer
to the quenching epoch.

Figure 5: The relation between formation redshift ($z_{\mathrm{form}}$) at
which the galaxy formed 50% of total stellar mass and observed redshift
($z_{\mathrm{spec}}$). We plot COSMOS-1047519 (the red star) and spectroscopic
samples of massive quiescent galaxies at $z>3$ from previous research
(Schreiber et al., 2018; Valentino et al., 2020; Nanayakkara et al., 2022;
Carnall et al., 2023a). Carnall et al. (2023a) uses a mass-weighted mean
formation time to define $z_{\mathrm{form}}$.

The young age of our galaxy is likely due to a selection effect; we
intentionally targeted the brightest candidate in the $K_{s}$-band (which
covers the Balmer break), and thus we tend to select galaxies with a prominent
Balmer break, leading us to young post-starbursts. It is interesting that old
quiescent galaxies show little dust attenuation ($A_{V}\sim 0$: e.g., Carnall
et al., 2023a; Nanayakkara et al., 2022), while young ones suffer from a
larger amount of attenuation ($A_{V}\sim 0.7$: This work, Valentino et al.,
2020). This indicates that post-starburst galaxies have residual dust.

Based on the non-parametric star formation history (Figure 4), the SFR of
COSMOS-1047519 at the time when 50% mass is formed is $SFR\sim
500\,M_{\odot}\,\mathrm{yr^{-1}}$. This is about 4 times higher than the SFR
of star-forming main sequence galaxies at $z=5$ (Schreiber et al., 2015). If
the galaxy experienced an intense starburst only once, starbursting galaxies
are possible progenitors as suggested by previous research (e.g., Forrest et
al., 2020; Valentino et al., 2020; Carnall et al., 2023a). Massive quiescent
galaxies at $z\sim 2$ show similar properties to submillimeter galaxies (SMGs)
at higher redshifts in terms of masses, effective radii, and number densities
(Toft et al., 2014; Gómez-Guijarro et al., 2018). SMGs tend to have a larger
star formation rate than the star-forming main sequence. By comparing the
physical properties, the peak SFR in SFH of our galaxy is consistent with that
of SMGs which have similar stellar mass at $z\sim 5$ (e.g., da Cunha et al.,
2015; Miettinen et al., 2017). Furthermore, the formation timescale of our
quiescent galaxy, which is the timescale of continuing its peak SFR in non-
parametric SFH, is estimated to be about $80\,\mathrm{Myr}$, and this is close
to gas depletion timescales of SMGs with similar specific star formation rates
at $1<z<5$ (Gómez-Guijarro et al., 2022). Also, Zavala et al. (2022)
summarizes the redshift evolution of gas depletion timescale of both starburst
galaxies and normal star-forming galaxies and show that the timescale is
shorter at the high redshift Universe. Our galaxy’s formation timescale is
consistent with the starburst galaxies’ gas depletion timescale at $z\sim 5$.
Thus, our work lends support to the scenario in which SMGs evolve into
quiescent galaxies.

###  3.4 Comparisons with simulations and role of AGNs

The Illustris TNG300 simulation (Pillepich et al., 2017; Nelson et al., 2019)
is a large cosmological hydrodynamical simulation and reproduces the cosmic
evolution from the early Universe to the local Universe. Thus, the simulation
is a very useful tool to help us understand how massive galaxies form in the
early Universe. We search for similar objects to COSMOS-1047519 in a snapshot
at $z=4.43$. However, there are no massive ($M_{*}>10^{10.5}\,M_{\odot}$)
quiescent galaxies with $sSFR<10^{-9.5}\,\mathrm{yr^{-1}}$. Hartley et al.
(2023) confirm the first quiescent galaxy in the TNG300 is at $z\sim 4.2$
although the definition of the quiescent galaxy is slightly different from
ours ($sSFR<10^{-10}\,\mathrm{yr^{-1}}$). They conclude that kinetic feedback
from AGN has a significant effect on the quenching process of quiescent
galaxies reconstructed at $z\sim 4.2$. We note that COSMOS-1047519 is not
detected in the deep X-ray observation ($L_{\mathrm{2-10\,keV}}<5.1\times
10^{43}\,\mathrm{erg\,s^{-1}}$ in Chandra COSMOS Legacy: Civano et al., 2016),
but this upper limit of X-ray luminosity does not rule out the possibility of
low-luminosity AGN in this galaxy.

Figure 1 shows that the model spectrum cannot fully reproduce the [O II] flux.
Table 1 and Figure 3 also show that [O II]-based SFR is higher than that from
SED fitting. The observed excess suggests that AGN may reside in the galaxy
because [O II] is sensitive to ionization by (low-luminosity) AGN as well as
star formation (e.g., Yan et al., 2006). Maseda et al. (2021) find that more
than half of the massive quiescent galaxies at $z<1$ exhibit [O II] lines and
conclude that this feature traces AGN activities. At $z>2$, there are massive
quiescent galaxies with AGN (e.g., Kriek et al., 2009; Marsan et al., 2015;
Schreiber et al., 2018; Kubo et al., 2022). Our galaxy may be a similar case,
although it is located at a higher redshift. Future deep X-ray or JWST NIR
observations of AGN activity (confirming [O III], [N II], and Balmer lines)
are necessary to identify or rule out the low-luminosity AGN.

##  4 Group environment around the quiescent galaxy

###  4.1 Over-density in the surrounding structure

Figure 6: Distribution of massive ($M_{*}>10^{10}\,M_{\odot}$) galaxies at
$4.4<z_{\mathrm{phot}}<4.7$ in the entire COSMOS field. The red color shows
the density excess of the massive galaxy candidates smoothed over
$30^{\prime\prime}$ which corresponds to the scale of the galaxy group
candidate using kernel density estimation. The blue circle shows the massive
proto-cluster at $z_{\mathrm{spec}}\sim 4.57$
($R_{\mathrm{proj}}=2\,\mathrm{Mpc}$: Lemaux et al., 2018). The right panel
shows a pseudo-color image of the area around the quiescent galaxy (Red:
VISTA/$K_{s}$-band, Green: VISTA/$H$-band, Blue: HSC/$i$-band, McCracken et
al., 2012; Aihara et al., 2022). The five galaxies indicated with the white
solid circles are the member candidates of this group centered on the
quiescent galaxy. Our massive quiescent galaxy at $z=4.53$ (the red point in
the RGB image) exists in the densest region ($12\sigma$ in the COSMOS field).
The red and white dotted circles show the estimated virial radii of the
quiescent galaxy and member candidates, respectively.

To gain deeper insights into quenching physics, we investigate the environment
of our galaxy. We select massive ($M_{*}>10^{10}\,M_{\odot}$) galaxies
regardless of SFRs at $4.4<z_{\mathrm{phot}}<4.7$ from the photo-$z$ catalog
in the COSMOS field (Section 2.1: Ito et al., 2022). The inset of Figure 6
shows a blow-up around the quiescent galaxy. There is a companion galaxy
$(z_{\mathrm{phot}}=4.535^{+0.168}_{-0.105})$ right next to it with a
separation of $2^{\prime\prime}$. Furthermore, there are 3 massive star-
forming galaxies $(z_{\mathrm{phot}}=4.57\mathrm{-}4.69)$ within
$23^{\prime\prime}$ or 151 kpc in physical scale. We recall that the quiescent
galaxy has a photo-$z$ of 4.65. We summarize the SEDs and physical properties
inferred from MIZUKI (Tanaka, 2015) in Figure 7 and Table 2. Each SED shows
that all member candidates have bluer SEDs compared to the quiescent galaxy,
and they are normal star-forming galaxies (locations on a SFR vs. stellar mass
diagram are shown in Figure 3 as black diamonds). The probability distribution
of photo-$z$ shows that all galaxies have the highest probability at
$z_{\mathrm{phot}}\sim 4.5$. Most of them have consistent photometric
redshifts within $1\sigma$ of the quiescent galaxy. The quiescent galaxy has
the largest stellar mass, and this environment may be the highest redshift
galaxy group with a spectroscopically confirmed quiescent galaxy at the
center.

Figure 7: SEDs of the group member candidates. The black points show the
photometry from the COSMOS2020 catalog (Weaver et al., 2022a), and the red
lines and blue squares indicate the model SEDs from MIZUKI (Tanaka, 2015). The
bottom panels show the probability distribution of photometric redshift. All
galaxies have a large probability at $z_{\mathrm{phot}}\sim 4.5$.

To evaluate the significance of this over-density of massive galaxies, we make
a density plot in Figure 6. This plot is obtained by the Gaussian kernel
density estimation method. The galaxy distribution in the entire COSMOS field
is smoothed over $30^{\prime\prime}$ (200 physical kpc at $z=4.5$, which
roughly corresponds to the scale of this over-density region). Our sample here
is complete down to $10^{10}\,M_{\odot}$ for SFGs but not for QGs (Weaver et
al., 2022b), and we may be missing low-mass QGs if any. SFGs significantly
outnumber QGs at these redshifts and missing low-mass QGs will not strongly
affect the density field. We find that our galaxy is located in a highly
significant ($12\sigma$) over-density region, and this structure turns out to
be the densest region of massive galaxies at $4.4<z_{\mathrm{phot}}<4.7$ in
the COSMOS field. On the other hand, if the galaxy distribution is smoothed
over $2.5^{\prime}$ (1 physical Mpc at $z=4.5$), the region is a less
significant ($2.2\sigma$) over-density. These kernel density does not follow
the Gaussian distribution, and the absolute significance is not very
important. We also estimate the excess of galaxy density using the 5th Nearest
Neighbor method, which yields a density distribution more similar to Gaussian
and obtains $180\sigma$. The group still remains the densest region in the
entire COSMOS field. Thus, the group is very compact. For comparison, we
indicate in Figure 6 a massive proto-cluster at $z\sim 4.57$ with the blue
circle (Lemaux et al., 2018). As can be seen, the proto-cluster is much more
extended than our group and on the scale of $\sim\mathrm{Mpc}$. The structure
and size of our group is really different from typical proto-clusters at this
high redshift (Overzier, 2016 for a review).

Table 2: Inferred physical properties of the member galaxies of the group

ID | $z_{\mathrm{phot}}$ | $z_{\mathrm{spec}}$ | $\theta_{\mathrm{sep}}$ | $\theta_{\mathrm{sep}}$ | $\log{M_{*}/M_{\odot}}$ | $SFR_{\mathrm{SED}}$ | $\log{M_{h}/M_{\odot}}$ | $r_{200}$
---|---|---|---|---|---|---|---|---
|  |  | [′′] | [$\mathrm{kpc}$] |  | [$M_{\odot}\,\mathrm{yr^{-1}}$] |  | [kpc]
1048346 | $4.535^{+0.168}_{-0.105}$ | – | 1.94 | 12.8 | $10.60\pm 0.11$ | $196.9^{+64.1}_{-65.6}$ | $12.19^{+0.78}_{-0.66}$ | $64.4^{+52.4}_{-25.5}$
1046859 | $4.630^{+0.118}_{-0.114}$ | – | 11.36 | 75.0 | $10.64^{+0.09}_{-0.14}$ | $58.0^{+33.7}_{-24.3}$ | $12.22^{+0.77}_{-0.68}$ | $65.7^{+52.2}_{-26.7}$
1048201 | $4.570^{+0.077}_{-0.075}$ | – | 11.61 | 76.4 | $10.05^{+0.19}_{-0.21}$ | $34.3^{+17.9}_{-9.8}$ | $11.88^{+0.79}_{-0.68}$ | $50.7^{+42.1}_{-20.5}$
1041229 | $4.693^{+0.103}_{-0.104}$ | – | 22.91 | 150.8 | $10.41^{+0.16}_{-0.19}$ | $68.5^{+44.2}_{-36.8}$ | $12.09^{+0.80}_{-0.69}$ | $59.3^{+49.6}_{-24.3}$
1047519aaThe physical properties of the QG are obtained from prospector using delayed tau-model. | $4.654^{+0.134}_{-0.104}$ | $4.5313\pm 0.0005$ | – | – | $10.72\pm 0.02$ | $8.97^{+3.35}_{-2.70}$ | $12.26^{+0.73}_{-0.62}$ | $67.8^{+50.7}_{-25.7}$

Note. —

  1. 1.

Object ID of member galaxies from the COSMOS2020 Classic catalog (Weaver et
al., 2022a).

  2. 2.

Photometric redshift estimated from MIZUKI (Tanaka, 2015).

  3. 3.

Spectroscopic redshift of COSMOS-1047519.

  4. 4.

Angular separation between COSMOS-1047519 and SFGs.

  5. 5.

Projected physical distance between COSMOS-1047519 and SFGs.

  6. 6.

Inferred stellar mass.

  7. 7.

Inferred star formation rate.

  8. 8.

The halo mass estimated from the stellar-to-halo mass relation (SHMR: Shuntov
et al., 2022).

  9. 9.

Virial radius estimated from the halo mass of each galaxy.

###  4.2 Halo mass and virial radius

While we have not spectroscopically confirmed the redshifts of the SFGs yet,
we make an attempt to infer the halo mass of each member and see if they can
be physically associated. We use the stellar-to-halo mass relation (SHMR)
observed in the COSMOS field at $4.5<z<5.5$ (Shuntov et al., 2022) to estimate
the halo mass assuming that each member is a central galaxy. Estimated values
are summarized in Table 2 (8). The most massive member (quiescent galaxy) has
$M_{h}\sim 10^{12.3}\,M_{\odot}$, which is slightly smaller than the galaxy
group at $z\gtrsim 3$ from previous research ($M_{h}\gtrsim
10^{13}\,M_{\odot}$: e.g., Miller et al., 2018; Hill et al., 2020; Daddi et
al., 2021). Next, we translate the halo mass into the virial radius. Here, we
use the radius $r_{200}$ (Carlberg et al., 1997) as the virial radius. Table 2
(9) summarizes the virial radii of the member candidates. The dotted circles
in the inset of Figure 6 show the virial radii of the member candidates
significantly overlap. Two SFGs are just outside of the virial radius of the
quiescent galaxy in Figure 6, but they are actually consistent with being
inside the virial radius within the uncertainties (see Table 2). The right
bottom galaxy is outside of it, but there is intrinsic scatter in the SMHR.
Thus, the galaxy may possibly be located inside the QG’s virial radius. These
3 - 4 galaxies likely form a group with the quiescent galaxy at the center.
Spectroscopic confirmations of these member candidates are required for
further characterization of the group environment.

###  4.3 Possible formation scenarios of the QG

As discussed earlier, COSMOS-1047519 is quenched very recently (or is being
quenched currently). The group is thus an ideal object to examine the role of
environments, especially for quenching. From the discussion in Sections 3.3
and 3.4, the quiescent galaxy experienced the starburst ($\sim
500\,M_{\odot}\,\mathrm{yr^{-1}}$) for a short timescale ($\sim
80\,\mathrm{Myr}$) and then rapidly quenched. The SFR and timescale of this
starburst are similar to the SMG’s SFR and gas depletion timescale at $z\sim
5$. Also, the $K$-band spectrum of the quiescent galaxy shows the excess of [O
II] emission compared to the model spectrum from prospector, and this galaxy
may harbor a low-luminosity AGN. Combining these discussions, the star
formation and AGN activities induced by the galaxy-galaxy interactions and
mergers affect the quenching of this quiescent galaxy. For example,
observational studies argue that minor mergers and galaxy interactions
increase star formation efficiency and AGN activity (e.g., Brodwin et al.,
2013; Gómez-Guijarro et al., 2018; Coogan et al., 2018). Also, previous
studies confirm that gas mass fractions of QGs are significantly lower than
those of SFGs (e.g., Whitaker et al., 2021; Suzuki et al., 2022). Therefore,
it is possible that the quick gas depletion due to starburst is responsible
for quenching. Shimakawa et al. (2018) suggests that group/cluster
environments have evolved stellar populations, and AGN feedback suppresses the
star formation of member galaxies at high redshift ($2<z<3$). Chiang et al.
(2017) argues that significant group- or cluster-sized cores (with the scale
of $r_{200}$) would be the first region to show the galaxy quenching. Our
group candidate has the comparable scale of these cores, and the quenching
observed in this group environment at $z>4$ is probably consistent with the
core-scale quenching. Our work suggests this core-scale quenching has already
occurred at $z>4$ by gas consumption due to the starburst and/or AGN feedback.

##  5 Conclusion

We present the spectroscopic confirmation of a massive quiescent galaxy at
$z=4.53$ based on the Keck/MOSFIRE observation. We confirm a very large
stellar mass and a very low star formation rate from the extensive SED fitting
using both the photometry and spectrum. The estimated SFR is more than 1 dex
below the star-forming main sequence at $z=4.5$. The star formation history of
the galaxy inferred from the SED fitting suggests that the galaxy experienced
a starburst at $z\sim 5$ followed by rapid quenching with a timescale of $\sim
100\,\mathrm{Myr}$.

To constrain physical drivers of the starburst and subsequent quenching, we
compare the properties of this object with those of quiescent galaxies from
the literature. The galaxy is one of the youngest quiescent galaxies from the
formation redshift; this is an interesting object to understand the physical
processes responsible for the suppression of star formation. The fact that the
star formation timescale of the galaxy is comparable to the gas depletion
timescale of SMGs at similar redshift indicates that the quenching is simply
due to gas consumption. Also, the observational excess of [O II] indicates the
existence of low-luminosity AGN. In addition, the galaxy is found to be
located in the group environment including a companion galaxy within
$2^{\prime\prime}$ (13 physical kpc). These findings suggest that gas
depletion due to the starburst and/or AGN feedback triggered by galaxy-galaxy
interactions or mergers may be responsible for quenching.

In Figure 5, we can clearly say that we are approaching the formation epoch of
the massive quiescent galaxies. This is an exciting redshift regime to
directly unveil the quenching physics. Recent James Webb Space Telescope
(JWST) observations confirm quiescent galaxies at these redshifts (Carnall et
al., 2023a) as well as a large number of the quiescent galaxy candidates
(Valentino et al., 2023; Carnall et al., 2023b; Long et al., 2023). Upcoming
imaging and spectroscopic observations will place a more stringent constraint
on the physical mechanism of quenching and detailed star formation history in
the near future.

This study was supported by JSPS KAKENHI Grant Number JP21K03622 (MO). PFW
acknowledges funding through the National Science and Technology Council grant
111-2112-M-002-048-MY2 and National Taiwan University grant NTU 112L7318 and
NTU 112L7439. The data presented herein were obtained at the W. M. Keck
Observatory, which is operated as a scientific partnership among the
California Institute of Technology, the University of California and the
National Aeronautics and Space Administration. The Observatory was made
possible by the generous financial support of the W. M. Keck Foundation. The
authors wish to recognize and acknowledge the very significant cultural role
and reverence that the summit of Maunakea has always had within the indigenous
Hawaiian community. We are most fortunate to have the opportunity to conduct
observations from this mountain. Based on observations collected at the
European Southern Observatory under ESO programme ID 179.A-2005 and on data
products produced by CALET and the Cambridge Astronomy Survey Unit on behalf
of the UltraVISTA consortium.

## References

  * Aihara et al. (2022) Aihara, H., AlSayyad, Y., Ando, M., et al. 2022, PASJ, 74, 247, doi: 10.1093/pasj/psab122
  * Antwi-Danso et al. (2023) Antwi-Danso, J., Papovich, C., Esdaile, J., et al. 2023, arXiv e-prints, arXiv:2307.09590, doi: 10.48550/arXiv.2307.09590
  * Astropy Collaboration et al. (2013) Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068
  * Astropy Collaboration et al. (2018) Astropy Collaboration, Price-Whelan, A. M., Sipőcz, B. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f
  * Belli et al. (2016) Belli, S., Newman, A. B., & Ellis, R. S. 2016, ApJ, 834, 18, doi: 10.3847/1538-4357/834/1/18
  * Belli et al. (2019) —. 2019, ApJ, 874, 17, doi: 10.3847/1538-4357/ab07af
  * Bellstedt et al. (2020) Bellstedt, S., Robotham, A. S. G., Driver, S. P., et al. 2020, MNRAS, 498, 5581, doi: 10.1093/mnras/staa2620
  * Béthermin et al. (2020) Béthermin, M., Fudamoto, Y., Ginolfi, M., et al. 2020, A&A, 643, A2, doi: 10.1051/0004-6361/202037649
  * Bohlin et al. (2014) Bohlin, R. C., Gordon, K. D., & Tremblay, P.-E. 2014, PASP, 126, 711, doi: 10.1086/677655
  * Brodwin et al. (2013) Brodwin, M., Stanford, S. A., Gonzalez, A. H., et al. 2013, ApJ, 779, 138, doi: 10.1088/0004-637X/779/2/138
  * Calzetti et al. (2000) Calzetti, D., Armus, L., Bohlin, R. C., et al. 2000, ApJ, 533, 682, doi: 10.1086/308692
  * Carlberg et al. (1997) Carlberg, R. G., Yee, H. K. C., & Ellingson, E. 1997, ApJ, 478, 462, doi: 10.1086/303805
  * Carnall et al. (2023a) Carnall, A. C., McLure, R. J., Dunlop, J. S., et al. 2023a, Nature, 619, 716, doi: 10.1038/s41586-023-06158-6
  * Carnall et al. (2023b) Carnall, A. C., McLeod, D. J., McLure, R. J., et al. 2023b, MNRAS, 520, 3974, doi: 10.1093/mnras/stad369
  * Cecchi et al. (2019) Cecchi, R., Bolzonella, M., Cimatti, A., & Girelli, G. 2019, ApJ, 880, L14, doi: 10.3847/2041-8213/ab2c80
  * Chabrier (2003) Chabrier, G. 2003, PASP, 115, 763, doi: 10.1086/376392
  * Chiang et al. (2017) Chiang, Y.-K., Overzier, R. A., Gebhardt, K., & Henriques, B. 2017, ApJ, 844, L23, doi: 10.3847/2041-8213/aa7e7b
  * Civano et al. (2016) Civano, F., Marchesi, S., Comastri, A., et al. 2016, ApJ, 819, 62, doi: 10.3847/0004-637X/819/1/62
  * Conroy & Gunn (2010) Conroy, C., & Gunn, J. E. 2010, ApJ, 712, 833, doi: 10.1088/0004-637X/712/2/833
  * Conroy et al. (2009) Conroy, C., Gunn, J. E., & White, M. 2009, ApJ, 699, 486, doi: 10.1088/0004-637X/699/1/486
  * Coogan et al. (2018) Coogan, R. T., Daddi, E., Sargent, M. T., et al. 2018, MNRAS, 479, 703, doi: 10.1093/mnras/sty1446
  * da Cunha et al. (2015) da Cunha, E., Walter, F., Smail, I. R., et al. 2015, ApJ, 806, 110, doi: 10.1088/0004-637X/806/1/110
  * Daddi et al. (2021) Daddi, E., Valentino, F., Rich, R. M., et al. 2021, A&A, 649, A78, doi: 10.1051/0004-6361/202038700
  * Dressler (1980) Dressler, A. 1980, ApJ, 236, 351, doi: 10.1086/157753
  * Faisst et al. (2020) Faisst, A. L., Schaerer, D., Lemaux, B. C., et al. 2020, ApJS, 247, 61, doi: 10.3847/1538-4365/ab7ccd
  * Foreman-Mackey et al. (2013) Foreman-Mackey, D., Hogg, D. W., Lang, D., & Goodman, J. 2013, PASP, 125, 306, doi: 10.1086/670067
  * Forrest et al. (2020) Forrest, B., Annunziatella, M., Wilson, G., et al. 2020, ApJ, 890, L1, doi: 10.3847/2041-8213/ab5b9f
  * Gallazzi et al. (2005) Gallazzi, A., Charlot, S., Brinchmann, J., White, S. D. M., & Tremonti, C. A. 2005, MNRAS, 362, 41, doi: 10.1111/j.1365-2966.2005.09321.x
  * Glazebrook et al. (2017) Glazebrook, K., Schreiber, C., Labbé, I., et al. 2017, Nature, 544, 71, doi: 10.1038/nature21680
  * Gómez et al. (2003) Gómez, P. L., Nichol, R. C., Miller, C. J., et al. 2003, ApJ, 584, 210, doi: 10.1086/345593
  * Gómez-Guijarro et al. (2018) Gómez-Guijarro, C., Toft, S., Karim, A., et al. 2018, ApJ, 856, 121, doi: 10.3847/1538-4357/aab206
  * Gómez-Guijarro et al. (2022) Gómez-Guijarro, C., Elbaz, D., Xiao, M., et al. 2022, A&A, 659, A196, doi: 10.1051/0004-6361/202142352
  * Harris et al. (2020) Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357, doi: 10.1038/s41586-020-2649-2
  * Hartley et al. (2023) Hartley, A. I., Nelson, E. J., Suess, K. A., et al. 2023, MNRAS, 522, 3138, doi: 10.1093/mnras/stad1162
  * Hill et al. (2020) Hill, R., Chapman, S., Scott, D., et al. 2020, MNRAS, 495, 3124, doi: 10.1093/mnras/staa1275
  * Horne (1986) Horne, K. 1986, PASP, 98, 609, doi: 10.1086/131801
  * Hunter (2007) Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90, doi: 10.1109/MCSE.2007.55
  * Ito et al. (2022) Ito, K., Tanaka, M., Miyaji, T., et al. 2022, ApJ, 929, 53, doi: 10.3847/1538-4357/ac5aaf
  * Ito et al. (2023) Ito, K., Tanaka, M., Valentino, F., et al. 2023, ApJ, 945, L9, doi: 10.3847/2041-8213/acb49b
  * Jin et al. (2018) Jin, S., Daddi, E., Liu, D., et al. 2018, ApJ, 864, 56, doi: 10.3847/1538-4357/aad4af
  * Johnson et al. (2021) Johnson, B. D., Leja, J., Conroy, C., & Speagle, J. S. 2021, ApJS, 254, 22, doi: 10.3847/1538-4365/abef67
  * Kalita et al. (2021) Kalita, B. S., Daddi, E., D’Eugenio, C., et al. 2021, ApJ, 917, L17, doi: 10.3847/2041-8213/ac16dc
  * Kawinwanichakij et al. (2017) Kawinwanichakij, L., Papovich, C., Quadri, R. F., et al. 2017, ApJ, 847, 134, doi: 10.3847/1538-4357/aa8b75
  * Kewley et al. (2004) Kewley, L. J., Geller, M. J., & Jansen, R. A. 2004, AJ, 127, 2002, doi: 10.1086/382723
  * Kriek et al. (2009) Kriek, M., van Dokkum, P. G., Labbé, I., et al. 2009, ApJ, 700, 221, doi: 10.1088/0004-637X/700/1/221
  * Kubo et al. (2021) Kubo, M., Umehata, H., Matsuda, Y., et al. 2021, ApJ, 919, 6, doi: 10.3847/1538-4357/ac0cf8
  * Kubo et al. (2022) —. 2022, ApJ, 935, 89, doi: 10.3847/1538-4357/ac7f2d
  * Le Fèvre et al. (2020) Le Fèvre, O., Béthermin, M., Faisst, A., et al. 2020, A&A, 643, A1, doi: 10.1051/0004-6361/201936965
  * Leja et al. (2019) Leja, J., Carnall, A. C., Johnson, B. D., Conroy, C., & Speagle, J. S. 2019, ApJ, 876, 3, doi: 10.3847/1538-4357/ab133c
  * Leja et al. (2017) Leja, J., Johnson, B. D., Conroy, C., van Dokkum, P. G., & Byler, N. 2017, ApJ, 837, 170, doi: 10.3847/1538-4357/aa5ffe
  * Lemaux et al. (2018) Lemaux, B. C., Le Fèvre, O., Cucciati, O., et al. 2018, A&A, 615, A77, doi: 10.1051/0004-6361/201730870
  * Long et al. (2023) Long, A. S., Antwi-Danso, J., Lambrides, E. L., et al. 2023, arXiv e-prints, arXiv:2305.04662, doi: 10.48550/arXiv.2305.04662
  * Marsan et al. (2015) Marsan, Z. C., Marchesini, D., Brammer, G. B., et al. 2015, ApJ, 801, 133, doi: 10.1088/0004-637X/801/2/133
  * Maseda et al. (2021) Maseda, M. V., van der Wel, A., Franx, M., et al. 2021, ApJ, 923, 18, doi: 10.3847/1538-4357/ac2bfe
  * McConachie et al. (2022) McConachie, I., Wilson, G., Forrest, B., et al. 2022, ApJ, 926, 37, doi: 10.3847/1538-4357/ac2b9f
  * McCracken et al. (2012) McCracken, H. J., Milvang-Jensen, B., Dunlop, J., et al. 2012, A&A, 544, A156, doi: 10.1051/0004-6361/201219507
  * McLean et al. (2010) McLean, I. S., Steidel, C. C., Epps, H. W., et al. 2010, SPIE Proceedings, 7735, 568, doi: 10.1117/12.856715
  * McLean et al. (2012) —. 2012, SPIE Proceedings, 8446, 149, doi: 10.1117/12.924794
  * Merlin et al. (2019) Merlin, E., Fortuni, F., Torelli, M., et al. 2019, MNRAS, 490, 3309, doi: 10.1093/mnras/stz2615
  * Miettinen et al. (2017) Miettinen, O., Delvecchio, I., Smolčić, V., et al. 2017, A&A, 606, A17, doi: 10.1051/0004-6361/201730762
  * Miller et al. (2018) Miller, T. B., Chapman, S. C., Aravena, M., et al. 2018, Nature, 556, 469, doi: 10.1038/s41586-018-0025-2
  * Nanayakkara et al. (2022) Nanayakkara, T., Glazebrook, K., Jacobs, C., et al. 2022, arXiv e-prints, arXiv:2212.11638, doi: 10.48550/arXiv.2212.11638
  * Nelan et al. (2005) Nelan, J. E., Smith, R. J., Hudson, M. J., et al. 2005, ApJ, 632, 137, doi: 10.1086/431962
  * Nelson et al. (2019) Nelson, D., Springel, V., Pillepich, A., et al. 2019, Computational Astrophysics and Cosmology, 6, 2, doi: 10.1186/s40668-019-0028-x
  * Oke & Gunn (1983) Oke, J. B., & Gunn, J. E. 1983, ApJ, 266, 713, doi: 10.1086/160817
  * Overzier (2016) Overzier, R. A. 2016, A&A Rev., 24, 14, doi: 10.1007/s00159-016-0100-3
  * Peng et al. (2010) Peng, Y.-j., Lilly, S. J., Kovač, K., et al. 2010, ApJ, 721, 193, doi: 10.1088/0004-637X/721/1/193
  * Pillepich et al. (2017) Pillepich, A., Nelson, D., Hernquist, L., et al. 2017, MNRAS, 475, 648, doi: 10.1093/mnras/stx3112
  * Renzini (2006) Renzini, A. 2006, ARA&A, 44, 141, doi: 10.1146/annurev.astro.44.051905.092450
  * Schreiber et al. (2015) Schreiber, C., Pannella, M., Elbaz, D., et al. 2015, A&A, 575, A74, doi: 10.1051/0004-6361/201425017
  * Schreiber et al. (2018) Schreiber, C., Glazebrook, K., Nanayakkara, T., et al. 2018, A&A, 618, A85, doi: 10.1051/0004-6361/201833070
  * Shimakawa et al. (2018) Shimakawa, R., Koyama, Y., Röttgering, H. J. A., et al. 2018, MNRAS, 481, 5630, doi: 10.1093/mnras/sty2618
  * Shuntov et al. (2022) Shuntov, M., McCracken, H. J., Gavazzi, R., et al. 2022, A&A, 664, A61, doi: 10.1051/0004-6361/202243136
  * Smolčić et al. (2017) Smolčić, V., Delvecchio, I., Zamorani, G., et al. 2017, A&A, 602, A2, doi: 10.1051/0004-6361/201630223
  * Stockmann et al. (2019) Stockmann, M., Toft, S., Gallazzi, A., et al. 2019, ApJ, 888, 4, doi: 10.3847/1538-4357/ab5af4
  * Suzuki et al. (2022) Suzuki, T. L., Glazebrook, K., Schreiber, C., et al. 2022, ApJ, 936, 61, doi: 10.3847/1538-4357/ac7ce3
  * Tacchella et al. (2022) Tacchella, S., Conroy, C., Faber, S. M., et al. 2022, ApJ, 926, 134, doi: 10.3847/1538-4357/ac449b
  * Tanaka (2015) Tanaka, M. 2015, ApJ, 801, 20, doi: 10.1088/0004-637X/801/1/20
  * Tanaka et al. (2019) Tanaka, M., Valentino, F., Toft, S., et al. 2019, ApJ, 885, L34, doi: 10.3847/2041-8213/ab4ff3
  * Thomas et al. (2005) Thomas, D., Maraston, C., Bender, R., & de Oliveira, C. M. 2005, ApJ, 621, 673, doi: 10.1086/426932
  * Thomas et al. (2010) Thomas, D., Maraston, C., Schawinski, K., Sarzi, M., & Silk, J. 2010, MNRAS, 404, 1775, doi: 10.1111/j.1365-2966.2010.16427.x
  * Toft et al. (2012) Toft, S., Gallazzi, A., Zirm, A., et al. 2012, ApJ, 754, 3, doi: 10.1088/0004-637X/754/1/3
  * Toft et al. (2014) Toft, S., Smolčić, V., Magnelli, B., et al. 2014, ApJ, 782, 68, doi: 10.1088/0004-637X/782/2/68
  * Toshikawa et al. (2014) Toshikawa, J., Kashikawa, N., Overzier, R., et al. 2014, ApJ, 792, 15, doi: 10.1088/0004-637X/792/1/15
  * Valentino et al. (2020) Valentino, F., Tanaka, M., Davidzon, I., et al. 2020, ApJ, 889, 93, doi: 10.3847/1538-4357/ab64dc
  * Valentino et al. (2023) Valentino, F., Brammer, G., Gould, K. M. L., et al. 2023, ApJ, 947, 20, doi: 10.3847/1538-4357/acbefa
  * Weaver et al. (2022a) Weaver, J. R., Kauffmann, O. B., Ilbert, O., et al. 2022a, ApJS, 258, 11, doi: 10.3847/1538-4365/ac3078
  * Weaver et al. (2022b) Weaver, J. R., Davidzon, I., Toft, S., et al. 2022b, arXiv e-prints, arXiv:2212.02512, doi: 10.48550/arXiv.2212.02512
  * Whitaker et al. (2012) Whitaker, K. E., Kriek, M., van Dokkum, P. G., et al. 2012, ApJ, 745, 179, doi: 10.1088/0004-637X/745/2/179
  * Whitaker et al. (2021) Whitaker, K. E., Williams, C. C., Mowla, L., et al. 2021, Nature, 597, 485, doi: 10.1038/s41586-021-03806-7
  * Williams et al. (2009) Williams, R. J., Quadri, R. F., Franx, M., van Dokkum, P., & Labbé, I. 2009, ApJ, 691, 1879, doi: 10.1088/0004-637X/691/2/1879
  * Yan et al. (2006) Yan, R., Newman, J. A., Faber, S. M., et al. 2006, ApJ, 648, 281, doi: 10.1086/505629
  * Young & Scoville (1991) Young, J. S., & Scoville, N. Z. 1991, ARA&A, 29, 581, doi: 10.1146/annurev.aa.29.090191.003053
  * Zavala et al. (2022) Zavala, J. A., Casey, C. M., Spilker, J., et al. 2022, ApJ, 933, 242, doi: 10.3847/1538-4357/ac7560