# PHANGS-JWST First Results: Dust embedded star clusters in NGC 7496
selected via 3.3$\mu$m PAH emission

M. Jimena Rodríguez Steward Observatory, University of Arizona, 933 N Cherry
Ave,Tucson, AZ 85721, USA  Instituto de Astrofísica de La Plata, CONICET–UNLP,
Paseo del Bosque S/N, B1900FWA La Plata, Argentina  Janice C. Lee Gemini
Observatory/NSF’s NOIRLab, 950 N. Cherry Avenue, Tucson, AZ, USA  Steward
Observatory, University of Arizona, 933 N Cherry Ave,Tucson, AZ 85721, USA  B.
C. Whitmore Space Telescope Science Institute, 3700 San Martin Drive,
Baltimore, MD 21218, USA  David A. Thilker Department of Physics and
Astronomy, The Johns Hopkins University, Baltimore, MD 21218 USA  Daniel
Maschmann Steward Observatory, University of Arizona, 933 N Cherry Ave,Tucson,
AZ 85721, USA  Sorbonne Université, LERMA, Observatoire de Paris, PSL
university, CNRS, F-75014, Paris, France  Rupali Chandar Ritter Astrophysical
Research Center, University of Toledo, Toledo, OH 43606, USA  Sinan Deger The
Oskar Klein Centre for Cosmoparticle Physics, Department of Physics, Stockholm
University, AlbaNova, Stockholm, SE-106 91, Sweden  Médéric Boquien Centro de
Astronomía (CITEVA), Universidad de Antofagasta, Avenida Angamos 601,
Antofagasta, Chile  Daniel A. Dale Department of Physics and Astronomy,
University of Wyoming, Laramie, WY 82071, USA  Kirsten L. Larson AURA for the
European Space Agency (ESA), Space Telescope Science Institute, 3700 San
Martin Drive, Baltimore, MD 21218, USA  Thomas G. Williams Sub-department of
Astrophysics, Department of Physics, University of Oxford, Keble Road, Oxford
OX1 3RH, UK  Max-Planck-Institut für Astronomie, Königstuhl 17, D-69117
Heidelberg, Germany  Hwihyun Kim Gemini Observatory/NSF’s NOIRLab, 950 N.
Cherry Avenue, Tucson, AZ, USA  Eva Schinnerer Max-Planck-Institut für
Astronomie, Königstuhl 17, D-69117 Heidelberg, Germany  Erik Rosolowsky
Department of Physics, University of Alberta, Edmonton, Alberta, T6G 2E1,
Canada  Adam K. Leroy Department of Astronomy, The Ohio State University, 140
West 18th Avenue, Columbus, Ohio 43210, USA  Center for Cosmology and
Astroparticle Physics, 191 West Woodruff Avenue, Columbus, OH 43210, USA  Eric
Emsellem European Southern Observatory, Karl-Schwarzschild-Straße 2, 85748
Garching, Germany  Univ Lyon, Univ Lyon1, ENS de Lyon, CNRS, Centre de
Recherche Astrophysique de Lyon UMR5574, F-69230 Saint-Genis-Laval France
Karin M. Sandstrom Center for Astrophysics & Space Sciences, University of
California, San Diego, 9500 Gilman Drive, San Diego, CA 92093, USA  J. M.
Diederik Kruijssen Cosmic Origins Of Life (COOL) Research DAO, coolresearch.io
Kathryn Grasha Research School of Astronomy and Astrophysics, Australian
National University, Canberra, ACT 2611, Australia  ARC Centre of Excellence
for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), Australia  Elizabeth J.
Watkins Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität
Heidelberg, Mönchhofstraße 12-14, D-69120 Heidelberg, Germany  Ashley. T.
Barnes Argelander-Institut für Astronomie, Universität Bonn, Auf dem Hügel 71,
53121, Bonn, Germany  Mattia C. Sormani Universität Heidelberg, Zentrum für
Astronomie, Institut für Theoretische Astrophysik, Albert-Ueberle-Straße 2,
D-69120 Heidelberg, Germany  Jaeyeon Kim Universität Heidelberg, Zentrum für
Astronomie, Institut für Theoretische Astrophysik, Albert-Ueberle-Straße 2,
D-69120 Heidelberg, Germany  Gagandeep S. Anand Space Telescope Science
Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA  Mélanie Chevance
Universität Heidelberg, Zentrum für Astronomie, Institut für Theoretische
Astrophysik, Albert-Ueberle-Straße 2, D-69120 Heidelberg, Germany  Cosmic
Origins Of Life (COOL) Research DAO, coolresearch.io  F. Bigiel Argelander-
Institut für Astronomie, Universität Bonn, Auf dem Hügel 71, 53121 Bonn,
Germany  Ralf S. Klessen Universität Heidelberg, Zentrum für Astronomie,
Institut für Theoretische Astrophysik, Albert-Ueberle-Straße 2, D-69120
Heidelberg, Germany  Universität Heidelberg, Interdisziplinäres Zentrum für
Wissenschaftliches Rechnen, Im Neuenheimer Feld 205, D-69120 Heidelberg,
Germany  Hamid Hassani Department of Physics, University of Alberta, Edmonton,
Alberta, T6G 2E1, Canada  Daizhong Liu Max-Planck-Institut für
Extraterrestrische Physik (MPE), Giessenbachstr. 1, D-85748 Garching, Germany
Christopher M. Faesi University of Connecticut, Department of Physics, 196A
Auditorium Road, Unit 3046, Storrs, CT, 06269  Yixian Cao Max-Planck-Institut
für Extraterrestrische Physik (MPE), Giessenbachstr. 1, D-85748 Garching,
Germany  Francesco Belfiore INAF — Arcetri Astrophysical Observatory, Largo E.
Fermi 5, I-50125, Florence, Italy  Ismael Pessa Max-Planck-Institut für
Astronomie, Königstuhl 17, D-69117 Heidelberg, Germany  Leibniz-Institut für
Astrophysik Potsdam (AIP), An der Sternwarte 16, 14482 Potsdam, Germany
Kathryn Kreckel Astronomisches Rechen-Institut, Zentrum für Astronomie der
Universität Heidelberg, Mönchhofstraße 12-14, D-69120 Heidelberg, Germany
Brent Groves International Centre for Radio Astronomy Research, University of
Western Australia, 7 Fairway, Crawley, 6009 WA, Australia  Jérôme Pety IRAM,
300 rue de la Piscine, 38400 Saint Martin d’Hères, France  LERMA, Observatoire
de Paris, PSL Research University, CNRS, Sorbonne Universités, 75014 Paris
Rémy Indebetouw National Radio Astronomy Observatory, 520 Edgemont Rd.,
Charlottesville, VA 22903  University of Virginia, 530 McCormick Rd.,
Charlottesville, VA 22904  Oleg V. Egorov Astronomisches Rechen-Institut,
Zentrum für Astronomie der Universität Heidelberg, Mönchhofstraße 12-14,
D-69120 Heidelberg, Germany  Guillermo A. Blanc The Observatories of the
Carnegie Institution for Science, 813 Santa Barbara St., Pasadena, CA, USA
Departamento de Astronomía, Universidad de Chile, Camino del Observatorio
1515, Las Condes, Santiago, Chile  Toshiki Saito National Astronomical
Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo, 181-8588, Japan  Annie
Hughes IRAP, Université de Toulouse, CNRS, CNES, UPS, (Toulouse), France

(Received XXX; Accepted XXX)

###### Abstract

The earliest stages of star formation occur enshrouded in dust and are not
observable in the optical. Here we leverage the extraordinary new high-
resolution infrared imaging from JWST to begin the study of dust-embedded star
clusters in nearby galaxies throughout the local volume. We present a
technique for identifying dust-embedded clusters in NGC 7496 (18.7 Mpc), the
first galaxy to be observed by the PHANGS-JWST Cycle 1 Treasury Survey. We
select sources that have strong 3.3$\mu$m PAH emission based on a $\rm
F300M-F335M$ color excess, and identify 67 candidate embedded clusters. Only
eight of these are found in the PHANGS-HST optically-selected cluster catalog
and all are young (six have SED-fit ages of $\sim 1$ Myr). We find that this
sample of embedded cluster candidates may significantly increase the census of
young clusters in NGC 7496 from the PHANGS-HST catalog – the number of
clusters younger than $\sim$2 Myr could be increased by a factor of two.
Candidates are preferentially located in dust lanes, and are coincident with
peaks in PHANGS-ALMA CO (2-1) maps. We take a first look at concentration
indices, luminosity functions, SEDs spanning from 2700Å to 21$\mu$m, and
stellar masses (estimated to be between $\sim 10^{4}-10^{5}M_{\odot}$). The
methods tested here provide a basis for future work to derive accurate
constraints on the physical properties of embedded clusters, characterize the
completeness of cluster samples, and expand analysis to all 19 galaxies in the
PHANGS-JWST sample, which will enable basic unsolved problems in star
formation and cluster evolution to be addressed.

star formation — star clusters — spiral galaxies — surveys

††journal: ApJL††facilities: JWST, HST, ALMA, MUSE††software: Astropy (Astropy
Collaboration et al., 2013, 2018, 2022). This research made use of Photutils,
an Astropy package for detection and photometry of astronomical sources
(Bradley et al., 2022) AstroPy (astropy.org)

##  1 Introduction

Star clusters are formed in the densest parts of giant molecular clouds (Lada
& Lada, 2003; Elmegreen, 2008; Kruijssen, 2012). During their formation and
early evolution they remain surrounded by dust and molecular gas causing them
to be heavily obscured at optical wavelengths, and often only detectable at
infrared and longer wavelengths. Until now, such young objects were mostly
identified using observations of the radio continuum (Johnson et al., 2003) or
dust continuum in combination with molecular-gas lines (Leroy et al., 2018).
Infrared studies of the star clusters inside such nurseries has so far mainly
occurred in the Milky Way, Magellanic Clouds, and Local Group (e.g. Großschedl
et al., 2019).

Since most stars form in clustered environments (Lada & Lada, 2003), embedded
clusters represent a very early, critical stage in the star formation process.
Therefore, the study of these systems is essential for understanding the
mechanisms that drive star formation overall, and the properties and evolution
of star cluster populations in galaxies.

Previous studies suggest that star clusters remain in this embedded phase
within their natal cloud for only a few Myr ($\sim$ 2-5 Myr, e.g. Whitmore et
al., 2014b; Corbelli et al., 2017; Messa et al., 2021; Grasha et al., 2018,
2019; Kim et al., 2021, Kim et al 2022, Whitmore et al. 2022, this volume).
However it has not been possible to obtain complete samples of embedded
clusters beyond the Local Group to constrain these durations more directly, as
the angular resolution of previous infrared facilities could not resolve the
parsec scales required to identify clusters at larger distances.

The powerful new infrared capabilities of JWST enable embedded young star
clusters throughout nearby galaxies to be identified and studied
statistically. Complete samples of embedded clusters from PHANGS-JWST,
combined with the PHANGS-HST, ALMA, and MUSE datasets, will allow basic open
issues in star and cluster formation to be addressed, such as fraction of star
formation that occurs in clusters (cluster formation efficiency), timescales
for the clearing of the natal dust and gas, the conditions that lead to
cluster formation, and the dependence of these parameters on galactic
environment.

In this pilot study, we identify candidate embedded clusters in NGC 7496 using
PHANGS-JWST NIRCam and PHANGS-HST UV-optical imaging. We find that selection
based on an excess in the $\rm F300M-F335M$ color, indicating PAH $3.3\,\mu$m
emission, effectively identifies the youngest dusty star clusters. We take a
first look at their properties, and compare with the census of optically-
selected clusters in the PHANGS-HST catalog. The rest of this paper is
organized as follows. In Section 2, we summarize the observations of NGC 7496
taken as part of the PHANGS-JWST Treasury program. In Section 3 we identify a
small set of prototype embedded clusters with strong PAH $3.3\,\mu$m emission,
and use their measured properties to define selection criteria to identify a
larger smaple of candidate young, embedded clusters. In Section 4 we estimate
the masses of the newly identified clusters and take a first look at the their
luminosity functions at 2 and 3 $\mu$m. We compare this new embedded cluster
sample with the optically-selected PHANGS-HST catalog in Section 5, and also
examine other properties of the sources, including concentration indices, and
UV-IR SEDs, which also incorporates photometry from PHANGS-JWST MIRI imaging.
We summarize our main conclusions and outline future work in Section 6.

##  2 Data

The PHANGS-JWST Cycle 1 Treasury program observed its first target, the dusty
barred spiral galaxy NGC 7496 located at 18.7 Mpc (Shaya et al., 2017;
Kourkchi et al., 2020; Anand et al., 2021), on 6 July 2022. The data were
released (simultaneously to the team and public) on 14 July 2022. All 19
galaxies in the PHANGS-JWST sample will eventually be imaged with NIRCam and
MIRI from 2.0$\micron$ to 21$\micron$, using 8 filters (NIRCam: F200W, F300M,
F335M and F360M; MIRI: F770W, F1000W, F1130W and F2100W). Full details of the
observing strategy and data reduction are given in the PHANGS-JWST survey
description paper in this Volume (Lee et al. 2022).

In this analysis, we examine the JWST data together with UV-optical imaging in
5 filters from the PHANGS-HST survey (Lee et al., 2022, F275W, F336W, F438W,
F555W and F814W). We compare our dust embedded clusters with the sample from
the PHANGS-HST cluster catalog (Lee et al., 2022; Thilker et al., 2021; Turner
et al., 2021; Deger et al., 2022), which provides age and stellar-mass
estimates from spectral-energy distribution (SED) fitting in NGC 7496. Here,
we consider the 263 clusters in the HST catalog which have passed human visual
inspection and are classified as class 1 (symmetric compact cluster), and
class 2 (asymmetric compact cluster; Whitmore et al., 2021; Deger et al.,
2022). This PHANGS-HST sample spans a wide range of properties, with ages
between 1 Myr and 13.7 Gyr, and masses between 500$M_{\odot}$ and 4.6 $\times
10^{6}M_{\odot}$ with a median of 1.5 $\times 10^{4}M_{\odot}$. Of these, 131
are 10 Myr and younger, with masses between 600$M_{\odot}$ and 4.3 $\times
10^{5}M_{\odot}$ with a median of 8000 M⊙.

##  3 Methodology

###  3.1 Identification of embedded cluster prototypes

To begin our studies of dust embedded, young star clusters with JWST, we
visually inspect the images to identify a small sample of sources that are
obvious candidates for dusty clusters and can serve as prototypes to guide our
analysis. We look for bright compact sources in the NIRCam $\rm F335M$ filter
that also appear in at least one other PHANGS-JWST NIRCam image ($\rm F200W$,
$\rm F300M$, or $\rm F360M$), but are either faint or not visible by eye in
the PHANGS-HST UV-optical images (A${}_{V}\gtrsim$ 10).We choose compact
objects that are slightly more extended than point sources (i.e., FWHM
$\gtrsim$ 1.8 pixels $\sim$ 10 pc), following a process similar to that for
optical star clusters in PHANGS-HST imaging (Lee et al., 2022; Thilker et al.,
2021; Whitmore et al., 2021; Deger et al., 2022). We choose to start our
inspection with the NIRCam $F335M$ image because it is the highest resolution
image obtained by PHANGS-JWST that captures PAH emission and hot dust111We do
not use continuum subtracted F335M images for visual inspection to avoid
issues with residuals on the small spatial scales of interest here.. We
identify an initial set of 12 prototypical clusters. The bottom panels of Fig.
1 show examples of these prototypes marked in yellow. Aperture photometry is
performed to examine the properties of these objects and to develop selection
criteria to select embedded cluster candidates, as discussed further in the
next section.

Figure 1:  The upper panel shows the PHANGS-HST WFC3 $\rm F555M$ image of NGC
7496. The sample of 67 PHANGS-JWST 3.3 $\mu$m selected star cluster candidates
are plotted with different colors according to their categories: embedded
(red), partially embedded (green) and visible (blue). The locations of
optically-selected clusters from the PHANGS-HST catalog are also shown, and
distinguished by SED-fit age (black squares for $>10$ Myr and black circles
for $<10$ Myr). Only clusters brighter than $\rm F300M<25$ are included. The
bottom panels show images in the HST-WFC3, JWST-NIRCam, and JWST-MIRI filters,
for the $10"\times 10"$ region indicated by the white box in the upper panel.
The central wavelength of each filter is indicated in the panel label. The
colored circles are the same as in the upper panel. Clusters marked by an
additional yellow circle are part of our prototype sample (see text for
details). The comparison of this region in the optical HST images and IR from
JWST, clearly shows that the candidates fall along a dust lane, largely
obscured in the HST bands.

###  3.2 Source detection and photometry

To obtain positions and photometry for our set of 12 prototype embedded
clusters, as well as to search for embedded clusters in a more systematic way,
we use routines in the Photutils (Bradley et al., 2022) Astropy package for
photometry. First, we use the peak-finding algorithm find_peaks to detect
sources in the F335M image. The level of the background varies significantly
across the image. So, in order to estimate local background levels, we use the
function SExtractorBackground to build a 2D model of the background. Then, we
search for local maxima in square regions that are 11 px on a side.

To derive accurate source positions, we use the function centroid_quadratic,
which determines the centroid by fitting 2D quadratic polynomials. We extract
photometry from a circular aperture with radius of 0$\farcs$093 (3 NIRCam
short-wavelength pixels) which encloses more than 50% of the energy for a
point source (0$\farcs$073) in the F335W filter. We subtract the background
computed from an annulus between 0$\farcs$217 and 0$\farcs$31 away from the
source center. The units of the NIRCam imaing are MJy/steradian, so we
multiply by the pixel area in steradians, given by the parameter PIXAR_SR in
the header of the image, to obtain flux densities in MJy. We then convert the
measured flux densities into the AB magnitudes using the usual expression:
$\\\ \displaystyle
m_{\text{AB}}=-2.5\log_{10}\left({\frac{f_{\nu}}{3\,631\times
10^{-6}{\text{MJy}}}}\right).$
For this initial analysis, we forgo aperture corrections to the photometry to
calculate total source fluxes. The measurement of accurate total fluxes for
individual clusters across the PHANGS-JWST filter set will be subject of
dedicated future work to address the challenges presented by the 10-fold
decrease in resolution from 2-21$\mu$m. Nevertheless, our sample selection
strategy which is primarily based on the F300M-F335M color (described in Sect.
3) should not be greatly affected since the resolution in these adjacent bands
is quite similar, with a difference in the PSF FWHM of only 0$\farcs$011.

###  3.3 Selection criteria for embedded cluster candidates

In Figure 2 we show color-magnitude diagrams (CMDs) based on $\rm F335M$ and
$\rm F300M$ photometry; the former captures flux from PAH 3.3$\mu$m feature,
while the latter primarily probes stellar and dust continuum (Lee et al. 2022;
Sandstrom et al 2022, Chastenet et al 2022, this Volume). Panel a in Figure 2
shows the 12 visually identified prototype embedded clusters (yellow stars)
together with the sample of $\rm F335M$ sources detected using Photutils
find_peaks (black dots). This latter sample is comprised of a mixture of
sources including stellar clusters of different ages, MS, RGB and AGB stars
and also background galaxies.

These CMDs are analogous to those commonly used to select emission-line
sources in extra-galactic narrow-band imaging surveys (e.g., Ly et al., 2011;
Lee et al., 2012), and similar strategies can be adopted to identify and
characterize sources with PAH emission. Sources that show a significant $\rm
F300M-F335M$ color excess (i.e., a continuum-subtracted F335M flux) are
identified as PAH emitters. The locus of points around $\rm F300M-F335M=0$
represents continuum sources with little-to-no PAH emission. These objects are
typically associated with star clusters older than 10 Myr as shown in panel c
of Fig. 2. Not surprisingly, this distribution becomes broader at fainter
F335M magnitudes, due to increasing noise in the $\rm F300M-F335M$ measurement
(compare with Fig. 3 in Lee et al., 2012). Sources with PAH emission show
significant $\rm F300M-F335M$ color excess and are found to the right of the
locus, and we find that all 12 prototypes are in this region.

Based on this clear separation in the CMD, we select a larger sample of bright
PAH emitters for examination, i.e., $\rm F300M-F335M>0.3$, $\rm F335M<24$ and
$\rm F300M<25$. This selection provides a sample of 67 objects, shown with
cyan symbols in panel a of Fig. 2. In this figure, the lines indicate the
limits $\rm F300M-F335M>0.3$ and $F335M<24$. We note there are additional
sources (beyond the 67 cyan candidates) that fall inside this box; however
these sources are fainter than $F300M=25$ mag and not included in our sample.

We visually inspect each of these 67 cluster candidates, and divide them into
3 categories:

  * •

embedded: optical emission very faint or undetected, similar to the 12
prototype objects ($N=28$)

  * •

intermediate/ambiguous: optical emission detected, but it is not clear whether
the optical source is the counterpart to the F335M source due to positional
differences, and lower resolution at 3$\mu$m ($N=16$)

  * •

visible/exposed: clear optical counterpart ($N=23$)

Examples of objects in each category are shown in Figure 1. We will compare
our new, dust embedded cluster sample with the optically selected PHANGS-HST
catalog in the Discussion.

Figure 2: Color-magnitude diagram $\rm F335M$ vs. $\rm F300M-F335M$ for NGC
7496. Magnitudes are in the AB system. In all panels the black dots are $\rm
F335M$ sources detected with Photutils find_peaks. Density contours for the
densest parts of this diagram are shown in panels a and b. In panel a) yellow
stars show the 12 prototype embedded clusters selected in our initial visual
inspection. Based on the location in the CMD of these candidates, we select 67
embedded candidates (cyan circles). The dashed lines show the selection
criteria: $\rm F300M-F335M>$0.3 and F335M$<$24\. The magenta box indicates a
region where scatter due to the uncertainties in the color is large, and is
chosen for the purposes of illustrating the spatial distribution in Fig. 5.
Panel b) shows the same extended sample of 67 candidates but differentiated by
category: embedded objects (red), intermediate or partially embedded (green),
and visible or exposed (blue). Panels c and d show for comparison the location
in the CMD sources from the PHANGS-HST optical cluster catalog. Panel c) show
clusters older than 100 Myr (magenta). As expected, these clusters fall around
$\rm F300M-F335M=0$, indicating that these old sources do not have PAH
emission. This panel also shows clusters with SED-fit age estimates between
10-100 Myr (green crosses) and 5-10 Myr (yellow diamonds), which also appear
around $\rm F300M-F335M=0$. In contrast, about half of the clusters younger
than 2 Myr shown in panel d) (small cyan crosses) are PAH emitters. Panel d)
also shows clusters between 2 and 5 Myr (orange squares), which mostly have
little measured PAH emission. Figure 3: Luminosity functions measured for
different cluster samples are shown in the $\rm F200W$ (left) and $\rm F300M$
(right) filters. The red squares show distributions for the 67 dust embedded
cluster candidates from this work. The orange points show the luminosity
functions for PHANGS-HST selected clusters at all ages (N=263), and the blue
dots are PHANGS-HST clusters younger than 10 Myr (N=131). Green triangles
indicate the LF of PHANGS-HST clusters plus the 67 embedded cluster candidates
(N=330). The green line shows the best fit index to this last sample, while
the orange line show the fit for only the PHANGS-HST cluster distribution
(orange circles). Our dust embedded cluster sample (red squares) is not
sufficiently deep to have many data points in the luminosity function before
the distribution begins to flatten, likely due to incompleteness, but
comparing the derived slopes with and without the embedded candidates we
observe that they are quite similar. The bright portion of each distribution
appears to follow a trend that is consistent with that observed for the
optically-selected HST clusters. The upper axis indicates mass estimates from
the method described in Section 4.2.

##  4 Results

Luminosity and mass functions for the youngest cluster populations in galaxies
give direct constraints on the initial cluster mass function, analogous to the
stellar initial stellar mass function. One of the major weaknesses in current
studies of star formation is that the fraction of the most recently formed
dust obscured clusters has been unknown and unaccounted for. These initial
results provide a preview of the work with JWST which will measure these
fundamental distributions.

###  4.1 Luminosity Function

For clusters with similar ages and reddening, the luminosity function of
clusters can serve as a proxy for their mass function. The luminosity function
(LF) can be approximated, at least to first order, by a power law shape of the
form $dN/dL\propto L^{\alpha}$ (Whitmore et al., 1999; Fall, 2006; Whitmore et
al., 2014a). Values of the power-law index $\alpha\sim-2$ are typical for
young star clusters (e.g. Larsen, 2009; Whitmore et al., 2014a).

In Fig 3 we present the LFs of our embedded cluster candidates in the $\rm
F200W$ and $\rm F300M$ bands, which sample flux from the stellar continuum,
with some contribution from the dust continuum (red squares). These
distributions increase starting from the brightest magnitudes (to the right),
eventually flatten, and then drop off again (F200W filter). The flattening
towards fainter magnitudes is almost certainly due to incompleteness.

For comparison we also show the LF of optically-selected clusters from the
PHANGS-HST survey (Lee et al., 2022; Thilker et al., 2021; Turner et al.,
2021; Deger et al., 2022), with no restriction on age (shown in orange) and
clusters with best fit ages younger than 10 Myr (shown in blue). We also plot
the LF of the combined cluster sample, i.e. PHANGS-HST clusters plus the 67
embedded candidates (shown with green triangles). The LF for the full HST+JWST
cluster sample (green) has a best fit power-law index of $-2.01$ in $\rm
F200W$ and $-1.77$ for $\rm F300M$ (shown as the green lines in each panel).
The fit over only the PHANGS-HST clusters (orange) gives very similar index
values, $-1.91$ in $\rm F200W$ and $-1.73$ for $\rm F300M$ (orange lines). On
the other hand, while there are only few data points before our embedded
cluster distribution (red points) flattens at magnitudes fainter than
M${}_{F200W}\geq$-8, the bright points suggest a behavior similar to the
optically-selected clusters. The LF in the F300M filter however, appears to be
steeper than the PHANGS-HST clusters. This difference could be due to the
imposed selection criteria that involve cuts using the F300M filter (Sect.
3.3).

Based on our preliminary results, we suspect that the LF for embedded star
clusters present a similar shape to that for optical clusters. However our
sample is not large enough to derive accurate power-law indices. In future
work we will extend this work to the full sample of 19 PHANGS-JWST galaxies,
which will be based on total fluxes computed with appropriate aperture
corrections. A larger sample will better constrain the shape of the LF as well
as the embedded cluster mass function, which again, is effectively the initial
cluster mass function. Comparison with what we have already learned for
visible clusters, will provide important insights into the survival of
clusters in transition to becoming exposed/visible.

###  4.2 Estimate of Cluster Masses

To obtain initial stellar mass estimates for our 67 embedded cluster
candidates, we fit a linear relation to obtain the mass-to-light ratio (e.g.
Fall, 2006; Larsen, 2009) using clusters younger than 2 Myr in the PHANGS-HST
catalog. In doing so, we obtain coefficients $\gamma$ and $C$, where:
$\mbox{log}(M/M_{\odot})=\gamma~{}\mbox{mag}+C$. We use apparent magnitudes in
F200W and F300M bands, obtaining values of $\gamma=$-2.35, $C=$34.22, and
$\gamma=$-2.43, $C=$35.46 respectively.

Using the relation for $\rm F200W$, we obtain a range of masses between
6.4$\times 10^{2}$ and $1.1\times 10^{5}M_{\odot}$, with approximately $80\%$
in the range $10^{4}$– $10^{5}~{}M_{\odot}$. In the case of masses obtained
from $\rm F300M$, the values for our candidates start at $\sim 2\times
10^{4}M_{\odot}$ due to our imposed condition in the selection criteria ($\rm
F300M<25$, see Sect. 3.3). We find that $\sim 88\%$ of the sample is between
this minimum value and $10^{5}~{}M_{\odot}$, with a few candidates reaching up
$\sim 5~{}\times 10^{5}M_{\odot}$. The masses estimated from F200W and F300M
are generally consistent to within a factor of a few, but clearly, from the
vastly different values on the low end of the range, there are candidates
(n$\sim$10) with estimates which differ by up to a factor of $\sim$30\. All of
these candidates are embedded sources, which likely suffer from high
extinction, even at 2$\mu$m. In future work, we will provide more reliable
mass estimates from spectral energy distribution (SED) fitting, as discussed
further in the next section.

##  5 Discussion

We compare our sample of 67 dust embedded cluster candidates with the PHANGS-
HST human inspected class $1+2$ cluster catalog (N=263), and find that our
analysis of the PHANGS-JWST imaging has identified 59 new, embedded clusters
candidates in NGC 7496. These objects are of particular importance because
they are likely to be among the youngest clusters in this galaxy, and are
needed to construct a complete census. In this context, it is notable that the
size of our new sample is comparable to the number of young HST clusters (59
younger than 2 Myr; 94 younger than 5 Myr), and may double the census of the
population younger than $\sim$2 Myr.

Of the 8 clusters in common between the two samples, we classify seven as
visible/exposed, and 1 as partially embedded/intermediate. All are found to be
younger than 11 Myr (six having ages less than 1 Myr), with masses of $\sim
1-7\times 10^{4}M_{\odot}$. (As mentioned earlier the full PHANGS-HST cluster
sample, meanwhile, contains clusters as old as 13 Gyr.)

We can gain additional insight by examining the infrared properties of
clusters of all ages from the optically-selected PHANGS-HST sample. Panels c)
and d) in Fig. 2 show the location of clusters in different age intervals in
the F300M-F335M color vs. F335M magnitude diagram. In panel c) we can see that
clusters older than 100 Myr (magenta triangles) have $\rm F300M-F335M=0$,
indicating these older sources do not have PAH emission. This panel also shows
that nearly all clusters with ages between 10-100 Myr (green crosses) and 5-10
Myr (yellow diamonds) have $\rm F300M-F335M=0$. On the other hand, panel d)
shows that all HST clusters with a $\rm F300M-F335M$ color excess (i.e. strong
PAH emission) have ages $\leq$2 Myr (cyan crosses). These very young,
optically-selected clusters have a similar range of $\rm F300M-F335M$ values
as our 67 embedded candidates, although most of them have a significantly
fainter F335M magnitude. Panel d) of Fig. 2 also shows clusters with estimated
ages between 2 and 5 Myr (orange squares). While a small fraction of these 2-5
Myr cluster have slighly higher $\rm F300M-F335M$ values than clusters older
than 5 Myr, a surprising number of them show little-to-no PAH emission.
Assuming that the age-dating from PHANGS-HST is correct for these clusters,
this result indicates that measurable PAH emission may drop very rapidly (in 2
Myr) in clusters of moderate mass.

We also examine the Concentration Index (CI) of infrared and optically
selected clusters. The CI provides a measure of the compactness of the source,
and is useful to distinguish between clusters and stars (e.g. Chandar et al.,
2010; Whitmore et al., 2014b; Deger et al., 2022). In particular, Whitmore et
al. (2022, this volume) found that CI estimated from the JWST F200W filter
significantly improves the separation of stars and clusters. CI values were
estimated following the procedure in Whitmore et al. (2022, this volume), as
the magnitude difference measured between 1 and 4 pixel apertures
(0$\farcs$031 and 0$\farcs$124) in the F200W filter. In Fig 4 we present the
results. The vertical dashed line indicates CI$=1.4$, a limit to separate
clusters from stars (Whitmore et al. 2022, this volume). The 67 dust embedded
clusters from this work are nearly all to the right of the line, meaning they
are extended relative to a point source, although there are a few fainter
objects which fall to the left of the line. The dispersion in the size
measurements clearly increases towards fainter magnitudes.

Figure 4: F200W magnitude vs. Concentration Index (measured as the difference
in magnitude between circular apertures with 1 and 4 pixel radius). The
vertical dashed line indicates CI$=1.4$ which can be used to distinguish
clusters from stars (Whitmore et al. 2022, this volume). The colored circles
represent our 67 cluster candidates as indicated, stars/point sources are
represented by a star symbol. PHANGS-HST clusters younger than 2 Myr are small
cyan symbols and those older than 100 Myr are small magenta triangles. The
grey dots are all the sources detected in the F335M image.

Next we examine the overall spatial distribution of the sample, as well as the
location of our dust embedded cluster candidates relative to other structures
and components of the ISM. In Fig. 1 we see a strong concentration of embedded
clusters (shown in red) along a dust lane in the northern spiral arm, which
forms a ridge just next to young (age $<$ 10 Myr) optically-selected clusters.
Jumping to the left panel of Fig. 5, we see that strongest PAH emitters (shown
as the green dots, without an accompanying magenta circle) are mostly located
where we see the most prominent dust features in the optical HST images, along
the spiral arms. Sources with $\rm F300M-F335M>$ 0.3, but with faint $\rm
F335M$ magnitudes (see magenta box in Fig. 2 a) are enclosed with a magenta
circle. Recall that we decided to apply cuts in magnitude to study only the
brightest sources ($\rm F335M<24$ and $\rm F300M<25$) to simplify this initial
analysis. However, by imposing these limits, weaker PAH emitters are excluded
from inspection of the image, these appear to coincide with the more subtle
dust lanes and potentially may also be dust embedded clusters. In future work
we will test selection criteria which employ a color excess curve to identify
fainter embedded clusters.

The middle and right panels of Fig. 5 show a CO(2-1) ALMA image taken as part
of the PHANGS–ALMA survey (Leroy et al., 2021), and the H$\alpha$ VLT-MUSE
image of NGC 7496 from the PHANGS-MUSE survey (Emsellem et al., 2022). Our 67
PAH-emitting sources are closely associated with molecular gas and current
star formation. Only 9% of our candidates appear unassociated with significant
peaks of CO emission, Hα, or both. These 9% all have no obvious optical
counterpart in the HST images, and half have CI values similar to stars,
indicating they are very compact and possibly not embedded clusters.

Finally, we examine the SEDs of the embedded clusters from optical wavelengths
with HST to the IR with NIRCam and MIRI, which provide further insights into
their properties. We show preliminary SEDs of the 12 embedded cluster
prototypes in Fig. 6. These show a clear deficit in optical flux relative to
the infrared. In fact, we were able to identify possibly associated faint
optical emission for only three of these objects. For the 9 embedded clusters,
without UV-optical detections, we show upper limits in the HST bands. For this
first look, the photometric measurements in all bands have been performed with
the same 0$\farcs$155 aperture, which leads to a relative underestimate of the
measured fluxes in the MIRI-bands, as no aperture corrections have been
applied as discussed before. To produce proper SEDs for these clusters in
future work, we will need to correctly distinguish between crowded point
sources and their corresponding diffuse PAH emission, with more careful source
extraction which takes the different PSFs into account. These are some of the
challenge that need to be addressed in order to perform proper SED fitting for
embedded clusters and more accurately constrain their physical properties
(e.g., stellar masses, dust masses, ages, reddenings). In addition to the
distinctive PAH-feature at $3.3\,\mu$m, we see a dip at $10\,\mu$m indicating
silicate absorption, which is caused by protostellar envelopes (Crapsi et al.,
2008) and has been observed in young stellar objects (e.g. Großschedl et al.,
2019). This spectral feature supports our conclusion that these candidates are
very young embedded clusters.

Figure 5: Left: Combined HST F555W (blue) and JWST F335M (red) image. The
green dots are sources detected in F335M that satisfy our color cut $\rm
F300M-F335M>0.3$ (Sect. 3.3), but before performing any cut in magnitude.
Sources shown in green without a magenta circle are the strongest PAH
emitters, and are mostly found in the main dust lanes within the spiral arms.
Sources with an additional magenta circle are those that have $\rm
F300M-F335M$ between 0.3 and 0.7, and $\rm F335M>24.5$, i.e., they are both
fainter and have larger color uncertainties (magenta box in Fig. 2). This
figure shows that when we select only the brightest sources with the largest
color excesses, sources which tend to coincide with minor dust lanes in the
galaxy, i.e., potentially fainter embedded clusters, are excluded. Middle:
CO(2-1) ALMA map, with resolution of $\sim 1"$ with the 67 embedded cluster
candidates (red circles). Right: Muse Hα map with resolution of $\sim
0\farcs$7 and the 67 candidates. Note that the sample is well-correlated with
$H_{\alpha}$ and CO(2-1) peaks.  Figure 6:  Preliminary UV-IR Spectral Energy
Distribution of the 12 embedded prototype clusters (Sect. 3.1). Prototypes
classified as partially embedded or ‘intermediate’ are shown with dashed
lines, and embedded clusters as solid lines. For objects which are not
detected in the HST-bands, we show upper limits with grey arrows. These
preliminary SEDs are constructed with fluxes measured with the same aperture
in all bands, which leads to an underestimate of the flux in the MIRI-bands,
and without aperture correction. Nevertheless, two features in the SEDs of
embedded clusters are clearly seen: PAH emission at $3.3\,\mu$m and silicate
absorption at $10\,\mu$m.

##  6 Summary and Conclusions

In this work, we have used new NIRCam imaging of the nearby spiral galaxy NGC
7496, the first galaxy to be observed for the PHANGS-JWST Treasury survey, to
identify very young clusters embedded in natal dust and gas. Our selection
method relies on detection of PAH 3.3 $\mu$m emission, which is closely
associated with the ISM of very recently formed clusters.

We begin by identifying 12 prototype, dust-obscured clusters based on visual
inspection of both PHANGS-JWST NIRCam and PHANGS-HST optical images. We find
that all 12 show strong PAH emission at 3.3 $\mu$m, and fall in a region of
the F335M vs. $\rm F330M-F335M$ color-magnitude diagram that clearly separates
from the vast majority of detections. To first order the PAH emission at
$3.3\,\mu$m appears to correlate with other dust emission (Sandstrom et al.,
Dale et al., Chastenet et al., 2022 this volume) and so should represent a
sensitive, high resolution tracer of dust-reprocessed UV light from young
stars. Based on this, we develop criteria to select a larger sample of
candidates. This selection is primarily based on the F330M-F335M color excess,
and yields a sample of 67 candidate embedded clusters in NGC 7496. By
comparing the F300M-F335M colors of this sample to optically-selected clusters
in the PHANGS-HST catalog, which have ages determined through SED fitting of
5-band UV-optical photometry, we estimate that the embedded clusters are
likely to be younger than $\sim$2 Myr.

We find that our new sample may significantly increase the census of young
clusters from the PHANGS-HST catalog – the number of clusters younger than 2
Myr could be increased by a factor of two. A more careful analysis of the
selection functions and completeness of both the HST and JWST cluster samples
will be required to provide an accurate assessment of the fraction of young
clusters which are embedded and are missing from optical catalogs. The eight
clusters in common between the two catalogs have very young SED ages (six are
$\sim 1$ Myr). These results underscore the importance of our new PHANGS-JWST
imaging for studying the earliest stages of star and cluster formation.

Preliminary optical/infrared SEDs for the visually selected prototype
candidates show PAH emission and possible silicate absorption. Concentration
index measurements confirm that the majority of our 67 sources are more
extended than stars/point sources. These characteristics provide additional
evidence that most of our selected candidates are star clusters. We also take
a first look at the 2 and 3 $\mu$m luminosity functions for our sample, and
estimate stellar masses, finding values of $10^{4}$– $10^{5}~{}M_{\odot}$.

The strongest and brightest PAH emitters are mainly located in prominent dust
lanes within the main spiral arms of the galaxy, next to young optically-
detected clusters from PHANGS-HST. The spatial distribution of our candidates
show that they are also correlated with Hα and CO(2-1) emission.

In future work we will expand this analysis to all 19 galaxies in the PHANGS-
JWST sample, and examine the completeness of samples based on the F300M-F335M
color excess for selecting young embedded star clusters. Significant effort
will be required to develop techniques to obtain robust total fluxes across
the 13 PHANGS-HST and JWST filters from 2750Å to 2$\mu$m due to the factor of
10 decrease in resolution. Such techniques are needed to produce SEDs
appropriate for constraining the physical properties of these clusters through
the fitting of stellar population and dust models. Ultimately, a complete
census of star clusters from PHANGS-HST and JWST will enable basic unsolved
problems in star formation and cluster evolution to be addressed through new
constraints on the initial cluster mass function, star cluster formation
efficiencies, as well as on feedback timescales associated with the clearing
of the natal gas and dust.

## acknowledgments

This work is based on observations made with the NASA/ESA/CSA JWST and
NASA/ESA Hubble Space Telescopes. The data were obtained from the Mikulski
Archive for Space Telescopes at the Space Telescope Science Institute, which
is operated by the Association of Universities for Research in Astronomy,
Inc., under NASA contract NAS 5-03127 for JWST and NASA contract NAS 5-26555
for HST. The JWST observations are associated with program 2107, and those
from HST with program 15454. The specific JWST observations analyzed can be
accessed via http://dx.doi.org/10.17909/9bdf-jn24 (catalog 10.17909/9bdf-
jn24). We have also used higher level data products developed and released by
PHANGS-HST http://dx.doi.org/10.17909/t9-r08f-dq31 (catalog
10.17909/t9-r08f-dq31) (image products) http://dx.doi.org/10.17909/jray-9798
(catalog 10.17909/jray-9798) (catalog products). We are grateful to Scott
Fleming at STScI and his team for their excellent support in helping us
provide these products to the community through
https://archive.stsci.edu/hlsp/phangs-hst and
https://archive.stsci.edu/hlsp/phangs-cat. Based on observations collected at
the European Southern Observatory under ESO programmes 1100.B-0651 (PHANGS-
MUSE; PI: Schinnerer). This paper makes use of the following ALMA data:
ADS/JAO.ALMA#2017.1.00886.L, 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. JMDK gratefully acknowledges funding from the European Research Council
(ERC) under the European Union’s Horizon 2020 research and innovation
programme via the ERC Starting Grant MUSTANG (grant agreement number 714907).
COOL Research DAO is a Decentralized Autonomous Organization supporting
research in astrophysics aimed at uncovering our cosmic origins. EJW
acknowledges the funding provided by the Deutsche Forschungsgemeinschaft (DFG,
German Research Foundation) – Project-ID 138713538 – SFB 881 (“The Milky Way
System”, subproject P1). MB acknowledges support from FONDECYT regular grant
1211000 and by the ANID BASAL project FB210003. TGW acknowledges funding from
the European Research Council (ERC) under the European Union’s Horizon 2020
research and innovation programme (grant agreement No. 694343). JK gratefully
acknowledges funding from the Deutsche Forschungsgemeinschaft (DFG, German
Research Foundation) through the DFG Sachbeihilfe (grant number KR4801/2-1).
MC gratefully acknowledges funding from the DFG through an Emmy Noether
Research Group (grant number CH2137/1-1). FB would like to acknowledge funding
from the European Research Council (ERC) under the European Union’s Horizon
2020 research and innovation programme (grant agreement No.726384/Empire). RSK
acknowledges financial support from the European Research Council via the ERC
Synergy Grant “ECOGAL” (project ID 855130), from the Deutsche
Forschungsgemeinschaft (DFG) via the Collaborative Research Center “The Milky
Way System” (SFB 881 – funding ID 138713538 – subprojects A1, B1, B2 and B8)
and from the Heidelberg Cluster of Excellence (EXC 2181 - 390900948)
“STRUCTURES”, funded by the German Excellence Strategy. RSK also thanks the
German Ministry for Economic Affairs and Climate Action for funding in the
project “MAINN” (funding ID 50OO2206). ER acknowledges the support of the
Natural Sciences and Engineering Research Council of Canada (NSERC), funding
reference number RGPIN-2022-03499. KG is supported by the Australian Research
Council through the Discovery Early Career Researcher Award (DECRA) Fellowship
DE220100766 funded by the Australian Government. KG is supported by the
Australian Research Council Centre of Excellence for All Sky Astrophysics in 3
Dimensions (ASTRO 3D), through project number CE170100013. SD is supported by
funding from the European Research Council (ERC) under the European Union’s
Horizon 2020 research and innovation programme (grant agreement no. 101018897
CosmicExplorer). KK gratefully acknowledges funding from the Deutsche
Forschungsgemeinschaft (DFG, German Research Foundation) in the form of an
Emmy Noether Research Group (grant number KR4598/2-1, PI Kreckel). HH
acknowledges the support of the Natural Sciences and Engineering Research
Council of Canada (NSERC), funding reference number RGPIN-2022-03499.

JPe acknowledges support by the DAOISM grant ANR-21-CE31-0010 and by the
Programme National “Physique et Chimie du Milieu Interstellaire” (PCMI) of
CNRS/INSU with INC/INP, co-funded by CEA and CNES. G.A.B. acknowledges the
support from ANID Basal project FB210003.

## References

  * Anand et al. (2021) Anand, G. S., Lee, J. C., Van Dyk, S. D., et al. 2021, MNRAS, 501, 3621, doi: 10.1093/mnras/staa3668
  * 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
  * Astropy Collaboration et al. (2022) Astropy Collaboration, Price-Whelan, A. M., Lim, P. L., et al. 2022, apj, 935, 167, doi: 10.3847/1538-4357/ac7c74
  * Bradley et al. (2022) Bradley, L., Sipőcz, B., Robitaille, T., et al. 2022, astropy/photutils: 1.5.0, 1.5.0, Zenodo, doi: 10.5281/zenodo.6825092
  * Chandar et al. (2010) Chandar, R., Whitmore, B. C., Kim, H., et al. 2010, ApJ, 719, 966, doi: 10.1088/0004-637X/719/1/966
  * Corbelli et al. (2017) Corbelli, E., Braine, J., Bandiera, R., et al. 2017, A&A, 601, A146, doi: 10.1051/0004-6361/201630034
  * Crapsi et al. (2008) Crapsi, A., van Dishoeck, E. F., Hogerheijde, M. R., Pontoppidan, K. M., & Dullemond, C. P. 2008, A&A, 486, 245, doi: 10.1051/0004-6361:20078589
  * Deger et al. (2022) Deger, S., Lee, J. C., Whitmore, B. C., et al. 2022, MNRAS, 510, 32, doi: 10.1093/mnras/stab3213
  * Elmegreen (2008) Elmegreen, B. G. 2008, ApJ, 672, 1006, doi: 10.1086/523791
  * Emsellem et al. (2022) Emsellem, E., Schinnerer, E., Santoro, F., et al. 2022, A&A, 659, A191, doi: 10.1051/0004-6361/202141727
  * Fall (2006) Fall, S. M. 2006, ApJ, 652, 1129, doi: 10.1086/508404
  * Grasha et al. (2018) Grasha, K., Calzetti, D., Bittle, L., et al. 2018, MNRAS, 481, 1016, doi: 10.1093/mnras/sty2154
  * Grasha et al. (2019) Grasha, K., Calzetti, D., Adamo, A., et al. 2019, MNRAS, 483, 4707, doi: 10.1093/mnras/sty3424
  * Großschedl et al. (2019) Großschedl, J. E., Alves, J., Teixeira, P. S., et al. 2019, A&A, 622, A149, doi: 10.1051/0004-6361/201832577
  * Johnson et al. (2003) Johnson, K. E., Indebetouw, R., & Pisano, D. J. 2003, AJ, 126, 101, doi: 10.1086/375459
  * Kim et al. (2021) Kim, J., Chevance, M., Kruijssen, J. M. D., et al. 2021, MNRAS, 504, 487, doi: 10.1093/mnras/stab878
  * Kourkchi et al. (2020) Kourkchi, E., Courtois, H. M., Graziani, R., et al. 2020, AJ, 159, 67, doi: 10.3847/1538-3881/ab620e
  * Kruijssen (2012) Kruijssen, J. M. D. 2012, MNRAS, 426, 3008, doi: 10.1111/j.1365-2966.2012.21923.x
  * Lada & Lada (2003) Lada, C. J., & Lada, E. A. 2003, ARA&A, 41, 57, doi: 10.1146/annurev.astro.41.011802.094844
  * Larsen (2009) Larsen, S. S. 2009, A&A, 494, 539, doi: 10.1051/0004-6361:200811212
  * Lee et al. (2012) Lee, J. C., Ly, C., Spitler, L., et al. 2012, PASP, 124, 782, doi: 10.1086/666528
  * Lee et al. (2022) Lee, J. C., Whitmore, B. C., Thilker, D. A., et al. 2022, ApJS, 258, 10, doi: 10.3847/1538-4365/ac1fe5
  * Leroy et al. (2018) Leroy, A. K., Bolatto, A. D., Ostriker, E. C., et al. 2018, ApJ, 869, 126, doi: 10.3847/1538-4357/aaecd1
  * Leroy et al. (2021) Leroy, A. K., Schinnerer, E., Hughes, A., et al. 2021, ApJS, 257, 43, doi: 10.3847/1538-4365/ac17f3
  * Ly et al. (2011) Ly, C., Lee, J. C., Dale, D. A., et al. 2011, ApJ, 726, 109, doi: 10.1088/0004-637X/726/2/109
  * Messa et al. (2021) Messa, M., Calzetti, D., Adamo, A., et al. 2021, ApJ, 909, 121, doi: 10.3847/1538-4357/abe0b5
  * Shaya et al. (2017) Shaya, E. J., Tully, R. B., Hoffman, Y., & Pomarède, D. 2017, ApJ, 850, 207, doi: 10.3847/1538-4357/aa9525
  * Thilker et al. (2021) Thilker, D. A., Whitmore, B. C., Lee, J. C., et al. 2021, arXiv e-prints, arXiv:2106.13366.  https://arxiv.org/abs/2106.13366
  * Turner et al. (2021) Turner, J. A., Dale, D. A., Lee, J. C., et al. 2021, arXiv e-prints, arXiv:2101.02134.  https://arxiv.org/abs/2101.02134
  * Whitmore et al. (2014a) Whitmore, B. C., Chandar, R., Bowers, A. S., et al. 2014a, AJ, 147, 78, doi: 10.1088/0004-6256/147/4/78
  * Whitmore et al. (1999) Whitmore, B. C., Zhang, Q., Leitherer, C., et al. 1999, AJ, 118, 1551, doi: 10.1086/301041
  * Whitmore et al. (2014b) Whitmore, B. C., Brogan, C., Chandar, R., et al. 2014b, ApJ, 795, 156, doi: 10.1088/0004-637X/795/2/156
  * Whitmore et al. (2021) Whitmore, B. C., Lee, J. C., Chandar, R., et al. 2021, MNRAS, 506, 5294, doi: 10.1093/mnras/stab2087