# Spatial extent of molecular gas, dust, and stars in massive galaxies at
$z=2$ determined with ALMA and JWST

Ken-ichi Tadaki Faculty of Engineering, Hokkai-Gakuen University, Toyohira-ku,
Sapporo 062-8605, Japan  Tadayuki Kodama  Astronomical Institute, Tohoku
University, 6-3, Aramaki, Aoba, Sendai, Miyagi, 980-8578, Japan  Yusei Koyama
National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo
181-8588, Japan  Department of Astronomical Science, SOKENDAI (The Graduate
University for Advanced Studies), Mitaka, Tokyo 181-8588, 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  Ikki Mitsuhashi  National Astronomical
Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan  Department
of Astronomy, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo 113-0033,
Japan  Ryota Ikeda  National Astronomical Observatory of Japan, 2-21-1 Osawa,
Mitaka, Tokyo 181-8588, Japan  Department of Astronomical Science, SOKENDAI
(The Graduate University for Advanced Studies), Mitaka, Tokyo 181-8588, Japan

###### Abstract

We present the results of 0$\farcs$6-resolution observations of CO $J=3-2$
line emission in 10 massive star-forming galaxies at $z=2$ with the Atacama
Large Millimeter/submillimeter Array (ALMA). We compare the spatial extent of
molecular gas with those of dust and stars, traced by the 870 $\mu$m and 4.4
$\mu$m continuum emissions, respectively. The average effective radius of the
CO emission is 1.7 kpc, which is about 50 percent larger than that of the 870
$\mu$m emission and is comparable with that of the 4.4 $\mu$m emission.
Utilizing the best-fit parametric models, we derive the radial gradients of
the specific star-formation rate (sSFR), gas depletion timescale, and gas-mass
fraction within the observed galaxies. We find a more intense star-formation
activity with a higher sSFR and a shorter depletion timescale in the inner
region than in the outer region. The central starburst may be the primary
process for massive galaxies to build up a core. Furthermore, the gas-mass
fraction is high, independent of the galactocentric radius in the observed
galaxies, suggesting that the galaxies have not begun to quench star
formation. Given the shorter gas depletion timescale in the center compared to
the outer region, quenching is expected to occur in the center first and then
propagate outward. We may be witnessing the observed galaxies in the formation
phase of a core prior to the forthcoming phase of star formation propagating
outward.

galaxies: starburst — galaxies: high-redshift — galaxies: ISM

††software: CASA (CASA Team et al., 2022), UVMULTIFIT (Martí-Vidal et al.,
2014), GALFIT (Peng et al., 2010), Source Extractor (Bertin & Arnouts, 1996)

##  1 Introduction

Massive galaxies populate two distinct regions on the stellar mass vs. star-
formation rate (SFR) plane: the so-called main-sequence of star-forming
galaxies and quiescent regime below the main-sequence (e.g. Renzini & Peng,
2015). At $z=1-3$, quiescent galaxies have a compact core in the center (e.g.
Toft et al., 2007) and their radial profile of the stellar emission is well
characterized by S$\acute{\mathrm{e}}$rsic models with a
S$\acute{\mathrm{e}}$rsic index of $n=4$ (e.g. Daddi et al., 2005). In
contrast, star-forming galaxies (SFGs) at similar redshifts have an
exponential disk with $n=1$ (e.g. Wuyts et al., 2011a). The bimodality on the
stellar mass–SFR plane and the correlation between star-formation activity and
morphology suggest that quenching of the SFR and transformation of galaxy
morphology occur at almost the same epoch and on a short timescale.

The scenario of the star formation spreading outward from the galaxy center
(so-called “inside-out growth”) is widely accepted to explain the
morphological evolution of massive galaxies (van Dokkum et al., 2010), i.e.,
galaxies form a compact core and later build the outer envelope through star
formation and minor mergers (Bezanson et al., 2009). ALMA observations have
revealed that massive SFGs commonly have a dusty star-forming core with an
effective radius of $R_{\mathrm{e}}$=1–2 kpc (e.g. Barro et al., 2016; Elbaz
et al., 2018). However, the spatial distributions of HST/1.6 $\mu$m emission
suggest that the massive SFGs already have an extended stellar disk with
$R_{\mathrm{e}}$=2–6 kpc (Tadaki et al., 2020, hereafter T20). These results
do not necessarily support that massive SFGs are in the inside-out growth
phase.

A difficulty to verify the inside-out scenario is that the 1.6 $\mu$m
emission, 0.5 $\mu$m in the rest frame at $z=2$, can be attenuated by dust,
particularly in the central region of the galaxy, where compact 870 $\mu$m
emission is detected. This dust-extinction effect leads to a situation where
the spatial distribution of 1.6 $\mu$m emission is more extended than that of
the stellar mass, which is predicted by numerical simulations with radiative
transfer calculations (Popping et al., 2022) and has been observationally
confirmed with spectral energy distribution (SED) fitting approaches (Suess et
al., 2019). High-resolution 4.4 $\mu$m images obtained by JWST/NIRCam (Rieke
et al., 2023) provide a more accurate view of galaxy morphology with less
effect of dust extinction (Suess et al., 2022; van der Wel et al., 2023).

Another problem is that the information about the spatial distribution of
molecular gas is lacking, which makes it difficult for us to understand how
massive SFGs form stars and quench star formation. As spatially-resolved
observations of distant galaxies with CO emission lines tracing molecular gas
are still limited in normal SFGs in the main-sequence due to faint emission
(Chen et al., 2017; Kaasinen et al., 2020; Ikeda et al., 2022; Liu et al.,
2023), no systematic surveys of the CO emission lines of galaxies coordinated
with JWST 4.4 $\mu$m observations have ever been conducted. In this letter, we
present the results of ALMA observations of CO emission lines from 10 massive
SFGs with a stellar mass of $\log(M_{\star}/M_{\odot})>11$ at $z=2$ in the
PRIMER-UDS field (JWST Cycle 1 GO program; ID: 1837; PI: J. Dunlop) where JWST
4.4 $\mu$m images are obtained. For understanding how massive SFGs form a
core, we compare the spatial extent of three components: gas, dust, and stars.

##  2 Observations

T20 reported ALMA 0$\farcs$2-resolution observations of 870 $\mu$m continuum
emission in 62 massive SFGs at $1.9<z<2.6$ to characterize the spatial extent
of dust emission. In T20, the stellar masses were estimated with SED fitting
of multi-wavelength photometry data from the ultraviolet to near-infrared of
sources in the 3D-HST catalog (Skelton et al., 2014). The total infrared
luminosities were estimated from the single-band photometry at Herschel/PACS
160 $\mu$m, 100 $\mu$m, or Spitzer/MIPS 24 $\mu$m (Wuyts et al., 2011b), and
were converted to dust-obscured SFRs (Kennicutt, 1998). Unobscured SFRs were
estimated from the rest-frame 2800 Å luminosity, but they do not contribute
little to total SFRs (T20). Figure 1 shows a scatter plot of the stellar mass
vs. SFR for galaxies at $1.9<z<2.6$. The T20 sample lies on the main sequence
of star formation at $z\sim 2$, suggesting that they are representative of
massive SFGs at $z=2$ (Whitaker et al., 2014). This is also supported by the
fact that their 870 $\mu$m flux densities are 2–5 mJy, which is by a factor of
2–3 smaller than those in submillimeter bright galaxies (Stach et al., 2019).

Figure 1:  Stellar mass vs. SFR for our ALMA sample of 10 massive SFGs at z=2
(magenta pentagons), the T20 sample with ALMA 870 $\mu$m data (blue circles),
and all galaxies at $1.9<z<2.6$ (gray dots) taken from the 3D-HST catalog
(Skelton et al. 2014; Momcheva et al. 2016). The shaded region indicates the
range of $\pm$0.4 dex from the star-formation main sequence at $z\sim 2$
(Whitaker et al., 2014).

For two (U4-16504 and U4-16795) of the 62 massive SFGs, the CO $J=3-2$ line
emission has been observed with ALMA at a 0$\farcs$6 resolution (Tadaki et
al., 2017, hereafter T17). From the T20 sample, we select additional six
massive SFGs in redshift ranges of $z=2.17-2.21$ and $z=2.51-2.55$. Their CO
$J=3-2$ emission lines can be covered with a single frequency setup of ALMA
Band-3 receivers since the redshift is accurately determined through H$\alpha$
spectroscopy ($\Delta z<0.01$; Wisnioski et al. 2019) or H$\alpha$ narrow-band
imaging ($\Delta z<0.02$; Tadaki et al. 2013). ALMA observations targeting the
six massive SFGs were conducted in 2021 December and 2022 July. The on-source
time was 85 minutes per pointing. The data were calibrated in the standard
manner using CASA (CASA Team et al., 2022). Then, we cleaned the emission down
to the 1.5$\sigma$ level to create 50 km s-1 channel maps with a robust
parameter of +2.0, leading to a spatial resolution of 0$\farcs$6 and a noise
level of 0.13–0.14 mJy beam-1. The data quality is similar to that in T17.
When the line emission is integrated over a velocity range of 200–750 km s-1,
the CO emission is detected at more than 8$\sigma$ for all the targets (Figure
2). In addition, two massive SFGs (U4-17519 and U4-28156) of the T20 sample
are serendipitously detected in CO in the same ALMA observations. Adding two
from T17, we have obtained a sample of 10 massive SFGs in total (Table 1). Our
sample is the largest sample of massive SFGs at $z\sim 2$ with spatially-
resolved data of both 870 $\mu$m continuum and CO $J=3-2$ line emission.

Figure 2:  The JWST 4.4 $\mu$m images (4″$\times$4″) for our sample of 10 massive SFGs (left and center columns in each panel). Magenta contours display the 870 $\mu$m flux densities in the ALMA 0$\farcs$2-resolution images, plotted for every 4$\sigma$. Cyan contours do the velocity-integrated flux of CO $J=3-2$ emission in the same image, plotted for every 4$\sigma$. The right columns in each panel shows the residual 4.4 $\mu$m images after the best-fit model is subtracted. Green lines show the regions masked in measuring the effective radii of the 4.4 $\mu$m emission. White crosses show the central position of the best-fit model in the JWST 4.4 $\mu$m image. The S$\acute{\mathrm{e}}$rsic index of the 4.4 $\mu$m emission is noted at the bottom-right corner.  Table 1:  Source list of 10 massive SFGs  ID | $z_{\mathrm{CO}}$ | $Sdv_{\mathrm{CO}}$ | $R_{\mathrm{e,CO}}$ | $R_{\mathrm{e,4.4}}$
---|---|---|---|---
|  | (Jy km s-1) | (kpc) | (kpc)
U4-16442 | 2.217 | 0.70$\pm$0.08 | 1.33$\pm$0.30 | 0.86
U4-16504 | 2.527 | 0.82$\pm$0.11 | 2.30$\pm$0.42 | 2.24
U4-16795 | 2.524 | 0.59$\pm$0.09 | 1.37$\pm$0.32 | 1.43
U4-17519 | 2.222 | 1.61$\pm$0.10 | 2.00$\pm$0.20 | 2.25
U4-28156 | 2.209 | 0.89$\pm$0.15 | 1.48$\pm$0.49 | 1.89
U4-28473 | 2.522 | 0.79$\pm$0.08 | 1.56$\pm$0.30 | 1.43
U4-28702 | 2.176 | 0.51$\pm$0.05 | 2.01$\pm$0.32 | 1.77
U4-34138 | 2.519 | 0.34$\pm$0.06 | 1.52$\pm$0.51 | 4.19
U4-34617 | 2.533 | 0.30$\pm$0.06 | 1.42$\pm$0.55 | 2.82
U4-36247 | 2.179 | 0.57$\pm$0.06 | 1.97$\pm$0.34 | 2.54

##  3 Size measurements

###  3.1 ALMA data of 870 $\mu$m and CO emissions

CO and 870 $\mu$m continuum emissions were observed with an interferometer;
then, we model the visibility data, not the images (Figure 2). This approach
has advantages of not being affected by uncertainties in Fourier transforms
and deconvolution of a dirty beam. For the 870 $\mu$m continuum emission, T20
have measured the flux density, effective radius, major-to-minor axis ratio,
and position angle of each galaxy, assuming an elliptical exponential disk
model, and characterized its spatial extent. For U4-34138 and U4-34617, the
best-fit models account for only 50%–70% of the total flux densities directly
measured from the short-baseline data, suggesting that a single component
model is not sufficient for characterizing the spatial distribution of the 870
$\mu$m continuum emission. We do not use these two galaxies in section 3.3 and
section 4 as their effective radii can be underestimated.

In the same way as T17, we measure the effective radius of CO emission for 10
massive SFGs with model fitting. In the fitting, we fix the axis ratio and the
position angle of the CO emission to those of 870 $\mu$m emission because the
spatial resolution of the CO observations is not as high as that of the 870
$\mu$m observations. We fit elliptical exponential models to the velocity-
integrated CO data, using the UVMULTIFIT (Martí-Vidal et al., 2014).
Consequently, the “circularized” effective radius of CO emission is found to
range from 1.3 kpc to 2.3 kpc (Table 1). Here, the circularized effective
radius, $R_{\mathrm{e}}$, is obtained by multiplying the effective radius
along the major axis by the square root of the axis ratio and is used in the
following sections.

###  3.2 JWST data of 4.4 $\mu$m emission

Our sample of 10 massive SFGs are all located in the PRIMER-UDS field. We use
mosaic images in the F444W filter (4.4 $\mu$m) with a pixel scale of
0$\farcs$04 from the Dawn JWST Archive, in which data were processed with the
Grizli software (Brammer, 2023; Valentino et al., 2023). We measure the
effective radii of the 4.4 $\mu$m continuum emission for massive SFGs in the
following procedure.

First, we select 18 stars with AB magnitudes of 20–21 in the Spitzer/IRAC 4.5
$\mu$m band (Ashby et al., 2013) from the 3D-HST catalog (Skelton et al.,
2014) and stack their normalized cut-out images in a sub-pixel scale of
0$\farcs$02\. We use the stacked image for deconvolution of the point-spread
function (PSF) in the following size measurements. A full width at half
maximum of a star in the stacked image is 0$\farcs$16\. Next, we generate
segmentation maps of massive SFGs by using SExtractor (Bertin & Arnouts, 1996)
to mask neighboring sources. Then, using the GALFIT code (Peng et al., 2010),
we fit JWST 4.4 $\mu$m cut-out images (4″$\times$4″) with
S$\acute{\mathrm{e}}$rsic models, fixing the sky value at zero and allowing
seven parameters to vary: the centroid position, flux density, effective
radius, S$\acute{\mathrm{e}}$rsic index, axis ratio, and position angle. The
derived centroid position of the 4.4 $\mu$m emission coincides well with the
peak of 870 $\mu$m emission (Figure 2). The circularized effective radius is
found to range from 0.9 kpc to 4.2 kpc (Table 1). The median value of the
S$\acute{\mathrm{e}}$rsic index is $n=1.9$, which is intermediate between SFGs
and quiescent galaxies (Wuyts et al., 2011a).

The residual images after subtracting the best-fit model from the original
images show sub-structures, such as spiral arms and off-center clumps (Figure
2), which cannot be characterized by simple elliptical models. Despite the
presence of residual emissions, the fitting errors are small, $\sim$1% or less
in each parameter. This may be attributed to the fact that our sample sources
are very bright at 4.4$\mu$m with AB magnitudes of 20–21.5 and that the
signal-to-noise ratio is high. The actual uncertainty is dominated by
deviations from a simple parametric model, rather than the statistical errors
of the fitting.

To verify the validity of S$\acute{\mathrm{e}}$rsic models, we measure the
total flux densities in the JWST 4.4 $\mu$m images by using
SExtractor/MAG_ISOCOR and compare them with the flux densities of the best-fit
models. We find that the models account for 106–116 % of the total flux
densities, suggesting that the spatial distribution of the primary component
is mostly characterized by the S$\acute{\mathrm{e}}$rsic models. An exception
is U4-34138; the best-fit model accounts for 130% of its total flux density,
and both ALMA 870 $\mu$m and JWST 4.4 $\mu$m indicate that a single component
is not sufficient for explaining their spatial distributions.

Figure 3:  Size comparisons between the CO, 870 $\mu$m, and 4.4 $\mu$m
emissions for eight massive SFGs. The solid lines show the 1:1 correspondence
between the effective radii compared.

###  3.3 Size comparisons

For eight massive SFGs excluding U4-34138 and U4-34617, we have measured the
effective radii of the CO, 870 $\mu$m, and 4.4 $\mu$m emissions. The average
and standard deviation of the effective radii of the CO, 870 $\mu$m, and 4.4
$\mu$m emissions are 1.75$\pm$0.34 kpc, 1.11$\pm$0.36 kpc, and 1.80$\pm$0.51
kpc, respectively. Figure 3 shows size comparisons between the three tracers.
The effective radius of the 870 $\mu$m emission is about 40% smaller than that
of the 4.4 $\mu$m emission. This trend is also reported in submillimeter
bright galaxies (Chen et al., 2022). The size difference between 870 $\mu$m
and 4.4 $\mu$m is much smaller than the difference between 870 $\mu$m and 1.6
$\mu$m (T20), which is consistent with the fact that 1.6 $\mu$m should be much
more severely affected by dust extinction.

We compare the effective radii of the CO emission with those of the 870 $\mu$m
and 4.4 $\mu$m emissions. The CO emission is more extended than the 870 $\mu$m
emission, which is consistent with previous studies of galaxies at $z=1-3$
(Chen et al., 2017; Calistro Rivera et al., 2018; Ikeda et al., 2022). Whereas
the low-$J$ CO line emission traces the mass of interstellar medium, the 870
$\mu$m emission is sensitive to dust heating by massive stars associated with
ongoing star-forming activity. We discuss the size difference between
molecular gas and dust in section 4. In contrast, the spatial extent of the CO
emission is comparable with that of the 4.4 $\mu$m emission. Although the
current resolution and sensitivity of the CO data do not allow us to capture
the sub-structures as seen in the JWST 4.4 $\mu$m images, the spatial
distributions of the CO and 4.4 $\mu$m emissions may be the same, at least in
a kilo-parsec scale.

##  4 Radial profiles in massive galaxies

CO, 870 $\mu$m, and 4.4 $\mu$m emissions trace molecular gas mass, dust-
obscured SFR, and stellar mass, respectively. We have characterized the
spatial extent of each component and derived the best-fit models in section 3.
Here we interpret these parametric models to investigate the radial dependence
of physical properties in massive SFGs. For the CO data, we estimate the
radial profile of molecular gas masses from the CO $J=3-2$ luminosities,
following the recipe of Tacconi et al. (2020) for SFGs in the main sequence
where two conversion factors are used: $R_{31}$=1.8 for CO $J=3-2$ to CO
$J=1-0$ and $\alpha_{\mathrm{CO}}=4.36$ for CO to H2. For the 870 $\mu$m and
4.4 $\mu$m data, we do not directly convert their observed luminosities to the
SFR and stellar mass, respectively. Galaxy-integrated values of dust-obscured
SFRs and stellar masses of the massive SFGs have been estimated from multi-
wavelength data (T20). By scaling the best-fit models of the 870 $\mu$m and
4.4 $\mu$m emissions to the galaxy-integrated values, we obtain the radial
profiles of the SFR and stellar mass, respectively.

Figure 4:  Best-fit model radial profiles of sSFR, gas depletion timescale,
and gas mass fraction. Solid red lines and shaded region show the average and
standard deviation in eight massive SFGs, respectively. Black dashed lines
show the individual models.

Then, we calculate the radial profiles of the specific SFR (sSFR), defined as
the SFR per unit stellar mass for eight massive SFGs (Figure 4). In the
“inside-out growth” scenario (see Section 1), a core forms first in the
massive galaxy and then star formation propagates outward. In this phase, the
sSFR is larger in the outer region than in the inner region because ongoing
star-formation activity contributes to forming an extended disk. Our results,
however, show that the sSFR increases towards the center, which is the
opposite trend reported in previous studies of massive galaxies (Nelson et
al., 2016; Tacchella et al., 2018; Spilker et al., 2019). If the current star
formation is maintained, the radial profile of stellar mass will be more
centrally concentrated. This is supported by the fact that the
S$\acute{\mathrm{e}}$rsic index of massive SFGs is higher than $n=1$ observed
in less massive SFGs. The massive SFGs may be building up a central core and
transforming their morphology from disk-dominated to bulge-dominated,
eventually leading to a $n=4$ profile as seen in massive quiescent galaxies at
similar redshifts (Wuyts et al., 2011a; Lang et al., 2014).

Moreover, we find that the central region has a shorter gas-depletion
timescale $\tau_{\mathrm{depl}}$, defined as the gas mass divided by the SFR,
than the outer region. The gas-depletion timescales in starburst galaxies are
0.5 dex shorter than those in normal SFGs, even when the same CO-to-H2
conversion factor is used (Kennicutt & De Los Reyes, 2021). In normal SFGs, a
radial dependence of $\tau_{\mathrm{depl}}$ is not seen in the regime where
molecular gas dominates interstellar medium (Leroy et al., 2008). These
results suggest the existence of a bimodality in star-formation activity, the
normal mode and starburst mode, also as pointed out by studies of high-
redshift galaxies (Daddi et al., 2010; Genzel et al., 2010). The physical
condition of gas in the central region of massive SFGs is likely similar to
that in starburst galaxies, in which galaxy-galaxy mergers could trigger
intense star formation. Our sample of massive SFGs show no indication of major
mergers, but some of them have potential, small companions within $\sim 10$
kpc in their JWST 4.4 $\mu$m images (Figure 2). The tidal interaction by small
satellites can develop non-axisymmetric structures in the galaxy, such as
spiral arms, which drive gas flows to the center (Mihos & Hernquist, 1994).
The spiral-arm-driven starburst scenario is supported by the fact that non-
axisymmetric substructures are identified in the JWST 4.4 $\mu$m images after
the primary component is subtracted (Figure 2).

The radial profile of gas-mass fraction $f_{\mathrm{gas}}$, defined by the gas
mass divided by the stellar mass, tells where galaxies begin to quench. The
gas mass fraction is constant over the galaxy at a large gas fraction of about
1.0, indicating that galaxies are gas-rich over the entire region. Even if a
small CO-to-H2 conversion factor of $\alpha_{\mathrm{CO}}=1$ in the starburst
mode is applied, the gas mass fraction is still larger than that in nearby
SFGs (Saintonge et al., 2017). The presence of such large gas reservoirs
implies that quenching has not begun in the massive SFGs. If cold gas is not
accreted onto galaxies from their surroundings, the existing gas begins to be
consumed from the center by star formation within several hundred million
years. Our sample of massive SFGs are likely to be in the phase immediately
before “inside-out” quenching (Tacchella et al., 2015).

Finally, we note a few caveats in our analysis. Our approach implicitly
assumes that luminosity-to-mass ratios are constant within a galaxy. We use
4.4 $\mu$m emissions, which corresponds to the rest-frame 1.5 $\mu$m, as the
tracer of the spatial distribution of the stellar mass. The rest-frame 1.5
$\mu$m emission is less affected by dust extinction. Nevertheless, Zhang et
al. (2023) show, using radiative transfer models, that even 4.4 $\mu$m sizes
are about 75 percent overestimated than the half mass radii in massive SFGs.
If this effect is significant in our sample, the true spatial extent of stars
is more compact than that of the SFR, indicating a suppressed sSFR in the
center. A deviation from parametric models is another problem to accurately
characterize the spatial distribution of emissions. Unlike the JWST 4.4 $\mu$m
images, sub-structures are not visible in the ALMA 870 $\mu$m images. This may
simply be due to the low signal-to-noise ratio ($\sim$10–30) in the ALMA
observations. The peak flux density in the residual images of JWST 4.4 $\mu$m
emission is less than 15% of the peak in the original image (Figure 2). To
capture the sub-structures of dust emission, it is necessary to have deeper
870 $\mu$m images than used in this work. Although these uncertainties are
desired to be addressed in the future, we are beginning to see with excellent
data from the JWST and ALMA how massive galaxies form a core.

This paper makes use of the following ALMA data: ADS/JAO.ALMA#2021.1.01291.S.
ALMA is a partnership of ESO (representing its member states), NSF (USA) and
NINS (Japan), together with NRC (Canada), MOST and ASIAA (Taiwan), and KASI
(Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA
Observatory is operated by ESO, AUI/NRAO and NAOJ. This work is based in part
on observations made with the NASA/ESA/CSA James Webb Space Telescope. These
observations are associated with program #1837. We acknowledge the PRIMER team
for developing their observing program with a zero-exclusive-access period.
The data products presented herein were retrieved from the Dawn JWST Archive
(DJA). DJA is an initiative of the Cosmic Dawn Center, which is funded by the
Danish National Research Foundation under grant No. 140. This work was
supported by JSPS KAKENHI Grant Numbers 20K14526. Data analysis was in part
carried out on the Multi-wavelength Data Analysis System operated by the
Astronomy Data Center (ADC), National Astronomical Observatory of Japan.

## References

  * Ashby et al. (2013) Ashby, M. L. N., Willner, S. P., Fazio, G. G., et al. 2013, ApJ, 769, 80, doi: 10.1088/0004-637X/769/1/80
  * Barro et al. (2016) Barro, G., Kriek, M., Pérez-González, P. G., et al. 2016, ApJ, 827, L32, doi: 10.3847/2041-8205/827/2/L32
  * Bertin & Arnouts (1996) Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393, doi: 10.1051/aas:1996164
  * Bezanson et al. (2009) Bezanson, R., van Dokkum, P. G., Tal, T., et al. 2009, ApJ, 697, 1290, doi: 10.1088/0004-637X/697/2/1290
  * Brammer (2023) Brammer, G. 2023, grizli, 1.9.3, Zenodo, Zenodo, doi: 10.5281/zenodo.8256200
  * Calistro Rivera et al. (2018) Calistro Rivera, G., Hodge, J. A., Smail, I., et al. 2018, ApJ, 863, 56, doi: 10.3847/1538-4357/aacffa
  * CASA Team et al. (2022) CASA Team, Bean, B., Bhatnagar, S., et al. 2022, PASP, 134, 114501, doi: 10.1088/1538-3873/ac9642
  * Chen et al. (2017) Chen, C.-C., Hodge, J. A., Smail, I., et al. 2017, ApJ, 846, 108, doi: 10.3847/1538-4357/aa863a
  * Chen et al. (2022) Chen, C.-C., Gao, Z.-K., Hsu, Q.-N., et al. 2022, ApJ, 939, L7, doi: 10.3847/2041-8213/ac98c6
  * Daddi et al. (2005) Daddi, E., Renzini, A., Pirzkal, N., et al. 2005, ApJ, 626, 680, doi: 10.1086/430104
  * Daddi et al. (2010) Daddi, E., Elbaz, D., Walter, F., et al. 2010, ApJ, 714, L118, doi: 10.1088/2041-8205/714/1/L118
  * Elbaz et al. (2018) Elbaz, D., Leiton, R., Nagar, N., et al. 2018, A&A, 616, A110, doi: 10.1051/0004-6361/201732370
  * Genzel et al. (2010) Genzel, R., Tacconi, L. J., Gracia-Carpio, J., et al. 2010, MNRAS, 407, 2091, doi: 10.1111/j.1365-2966.2010.16969.x
  * Ikeda et al. (2022) Ikeda, R., Tadaki, K.-i., Iono, D., et al. 2022, ApJ, 933, 11, doi: 10.3847/1538-4357/ac6cdc
  * Kaasinen et al. (2020) Kaasinen, M., Walter, F., Novak, M., et al. 2020, ApJ, 899, 37, doi: 10.3847/1538-4357/aba438
  * Kennicutt (1998) Kennicutt, Robert C., J. 1998, ARA&A, 36, 189, doi: 10.1146/annurev.astro.36.1.189
  * Kennicutt & De Los Reyes (2021) Kennicutt, Robert C., J., & De Los Reyes, M. A. C. 2021, ApJ, 908, 61, doi: 10.3847/1538-4357/abd3a2
  * Lang et al. (2014) Lang, P., Wuyts, S., Somerville, R. S., et al. 2014, ApJ, 788, 11, doi: 10.1088/0004-637X/788/1/11
  * Leroy et al. (2008) Leroy, A. K., Walter, F., Brinks, E., et al. 2008, AJ, 136, 2782, doi: 10.1088/0004-6256/136/6/2782
  * Liu et al. (2023) Liu, D., Förster Schreiber, N. M., Genzel, R., et al. 2023, ApJ, 942, 98, doi: 10.3847/1538-4357/aca46b
  * Martí-Vidal et al. (2014) Martí-Vidal, I., Vlemmings, W. H. T., Muller, S., & Casey, S. 2014, A&A, 563, A136, doi: 10.1051/0004-6361/201322633
  * Mihos & Hernquist (1994) Mihos, J. C., & Hernquist, L. 1994, ApJ, 425, L13, doi: 10.1086/187299
  * Momcheva et al. (2016) Momcheva, I. G., Brammer, G. B., van Dokkum, P. G., et al. 2016, ApJS, 225, 27, doi: 10.3847/0067-0049/225/2/27
  * Nelson et al. (2016) Nelson, E. J., van Dokkum, P. G., Förster Schreiber, N. M., et al. 2016, ApJ, 828, 27, doi: 10.3847/0004-637X/828/1/27
  * Peng et al. (2010) Peng, C. Y., Ho, L. C., Impey, C. D., & Rix, H.-W. 2010, AJ, 139, 2097, doi: 10.1088/0004-6256/139/6/2097
  * Popping et al. (2022) Popping, G., Pillepich, A., Calistro Rivera, G., et al. 2022, MNRAS, 510, 3321, doi: 10.1093/mnras/stab3312
  * Renzini & Peng (2015) Renzini, A., & Peng, Y.-j. 2015, ApJ, 801, L29, doi: 10.1088/2041-8205/801/2/L29
  * Rieke et al. (2023) Rieke, M. J., Kelly, D. M., Misselt, K., et al. 2023, PASP, 135, 028001, doi: 10.1088/1538-3873/acac53
  * Saintonge et al. (2017) Saintonge, A., Catinella, B., Tacconi, L. J., et al. 2017, ApJS, 233, 22, doi: 10.3847/1538-4365/aa97e0
  * Skelton et al. (2014) Skelton, R. E., Whitaker, K. E., Momcheva, I. G., et al. 2014, ApJS, 214, 24, doi: 10.1088/0067-0049/214/2/24
  * Spilker et al. (2019) Spilker, J. S., Bezanson, R., Weiner, B. J., Whitaker, K. E., & Williams, C. C. 2019, ApJ, 883, 81, doi: 10.3847/1538-4357/ab3804
  * Stach et al. (2019) Stach, S. M., Dudzevičiūtė, U., Smail, I., et al. 2019, MNRAS, 487, 4648, doi: 10.1093/mnras/stz1536
  * Suess et al. (2019) Suess, K. A., Kriek, M., Price, S. H., & Barro, G. 2019, ApJ, 877, 103, doi: 10.3847/1538-4357/ab1bda
  * Suess et al. (2022) Suess, K. A., Bezanson, R., Nelson, E. J., et al. 2022, ApJ, 937, L33, doi: 10.3847/2041-8213/ac8e06
  * Tacchella et al. (2015) Tacchella, S., Carollo, C. M., Renzini, A., et al. 2015, Science, 348, 314, doi: 10.1126/science.1261094
  * Tacchella et al. (2018) Tacchella, S., Carollo, C. M., Förster Schreiber, N. M., et al. 2018, ApJ, 859, 56, doi: 10.3847/1538-4357/aabf8b
  * Tacconi et al. (2020) Tacconi, L. J., Genzel, R., & Sternberg, A. 2020, ARA&A, 58, 157, doi: 10.1146/annurev-astro-082812-141034
  * Tadaki et al. (2013) Tadaki, K.-i., Kodama, T., Tanaka, I., et al. 2013, ApJ, 778, 114, doi: 10.1088/0004-637X/778/2/114
  * Tadaki et al. (2017) Tadaki, K.-i., Kodama, T., Nelson, E. J., et al. 2017, ApJ, 841, L25, doi: 10.3847/2041-8213/aa7338
  * Tadaki et al. (2020) Tadaki, K.-i., Belli, S., Burkert, A., et al. 2020, ApJ, 901, 74, doi: 10.3847/1538-4357/abaf4a
  * Toft et al. (2007) Toft, S., van Dokkum, P., Franx, M., et al. 2007, ApJ, 671, 285, doi: 10.1086/521810
  * Valentino et al. (2023) Valentino, F., Brammer, G., Gould, K. M. L., et al. 2023, ApJ, 947, 20, doi: 10.3847/1538-4357/acbefa
  * van der Wel et al. (2023) van der Wel, A., Martorano, M., Haussler, B., et al. 2023, arXiv e-prints, arXiv:2307.03264, doi: 10.48550/arXiv.2307.03264
  * van Dokkum et al. (2010) van Dokkum, P. G., Whitaker, K. E., Brammer, G., et al. 2010, ApJ, 709, 1018, doi: 10.1088/0004-637X/709/2/1018
  * Whitaker et al. (2014) Whitaker, K. E., Franx, M., Leja, J., et al. 2014, ApJ, 795, 104, doi: 10.1088/0004-637X/795/2/104
  * Wisnioski et al. (2019) Wisnioski, E., Förster Schreiber, N. M., Fossati, M., et al. 2019, ApJ, 886, 124, doi: 10.3847/1538-4357/ab4db8
  * Wuyts et al. (2011a) Wuyts, S., Förster Schreiber, N. M., van der Wel, A., et al. 2011a, ApJ, 742, 96, doi: 10.1088/0004-637X/742/2/96
  * Wuyts et al. (2011b) Wuyts, S., Förster Schreiber, N. M., Lutz, D., et al. 2011b, ApJ, 738, 106, doi: 10.1088/0004-637X/738/1/106
  * Zhang et al. (2023) Zhang, J., Wuyts, S., Cutler, S. E., et al. 2023, MNRAS, 524, 4128, doi: 10.1093/mnras/stad2066