# What Are Those Tiny Things?
A First Study of Compact Star Clusters in the SMACS0723 Field with JWST

Andreas L. Faisst Caltech/IPAC, MS314-6, 1200 E. California Blvd. Pasadena, CA
91125, USA  Ranga Ram Chary Caltech/IPAC, MS314-6, 1200 E. California Blvd.
Pasadena, CA 91125, USA  Gabriel Brammer Cosmic Dawn Center (DAWN),
Copenhagen, Denmark  Niels Bohr Institute, University of Copenhagen, Jagtvej
128, 2200 Copenhagen, Denmark  Sune Toft Cosmic Dawn Center (DAWN),
Copenhagen, Denmark  Niels Bohr Institute, University of Copenhagen, Jagtvej
128, 2200 Copenhagen, Denmark

###### Abstract

We use the unprecedented resolution and depth of the JWST NIRCam Early Release
Observations at $1-5\,{\rm\mu m}$ to study the stellar mass, age, and
metallicity of compact star clusters in the neighborhood of the host galaxies
in the SMACS J0723.3-7327 galaxy cluster field at $z=0.39$. The measured
colors of these star clusters show a similar distribution as quiescent
galaxies at the same redshift, but are $>3$ magnitudes fainter than the
current depths of wide-field galaxy survey. The star clusters are unresolved
in the NIRCam/F150W data suggesting sizes smaller than $50\,{\rm pc}$. This is
significantly smaller than star forming clumps or dwarf galaxies in local
galaxies. From fitting their photometry with simple stellar population (SSP)
models, we find stellar metallicities consistent with $0.2-0.3\,{\rm
Z_{\odot}}$ and ages of $1.5^{+0.5}_{-0.5}\,{\rm Gyrs}$. We rule out
metallicities $<0.2\,{\rm Z_{\odot}}$ and solar/super-solar at $4\sigma$
significance. Assuming mass-to-light ratios obtained from the best-fit SSPs,
we estimate stellar masses of $2.4^{+3.0}_{-1.5}\times 10^{6}\,{\rm
M_{\odot}}$. These are between average masses of local globular clusters and
dwarf galaxies. Our analysis suggests middle-aged globulars with relatively
recent formation times at $z=0.5-0.7$, which could have been subsequently
stripped away from their host galaxies due to interactions in the cluster
environment, or formed in cold flows onto the cluster core. However, we cannot
rule out these objects being compact cores of stripped dwarf galaxies.

Globular star clusters (656), Galaxy clusters (584), Stellar populations
(1622), Metallicity (1031), Galaxy formation (595)

††facilities: JWST (NIRCam), VLT (MUSE)††software:  astropy (Astropy
Collaboration et al., 2013, 2018), EAZY (Brammer et al., 2008), FSPS (Conroy
et al., 2009; Conroy & Gunn, 2010), GALAXEV (Bruzual & Charlot, 2003), Grizli
(Brammer & Matharu, 2021), Source Extractor (Bertin & Arnouts, 1996)

##  1 Introduction

The Early Release Observations (ERO; Pontoppidan et al., 2022) have already
showcased the capabilities of the new James Webb Space Telescope (JWST; Rigby
et al., 2022) in terms of its sensitivity and resolution at near-infrared
wavelengths.

Figure 1: Overview of data used in this study. The large white squares are the
$2.2\arcmin\times 2.2\arcmin$ FoVs of the two NIRCam modules. The left one is
centered on the cluster BCG (color composite of all $6$ observed NIRCam
filters) and the right one (F200W shown only) is offset by approximately
$3\arcmin$ (or $\sim 1\,{\rm Mpc}$ at cluster redshift). The location of the
selected compact star clusters studied in this work is marked with the green
dashed contour. The JWST/MIRI coverage (red) is indicated for completeness,
although MIRI data is not used in this study. The red inset shows an example
selection of globulars (green circles) close to the BCG.

Here, we use the unprecedented sensitivity of the JWST ERO data to study for
the first time, the faintest and most compact structures around the galaxies
associated with the SMACS J0723.3-7327 galaxy cluster field (hereafter
SMACS0723) at $z=0.39$. Although these objects appear to be consistent with
compact star clusters (or globular clusters), they could just as well be the
cores of stripped dwarf galaxies.

Globulars around galaxies are abundant and have been observed in our Milky Way
as well as many local galaxies (e.g., Harris & Racine, 1979; Larsen et al.,
2001; Brodie et al., 2014; Harris et al., 2014; Massari et al., 2019). The
number of globulars hosted by galaxies range from a few to tens for dwarf
galaxies such as the Magellanic clouds (e.g., Georgiev et al., 2010), to a few
hundreds for intermediate-mass galaxies such as our Milky Way or M31 (e.g.,
Harris, 1991; Massari et al., 2019), to thousands and more for massive
brightest cluster galaxies (BCGs) in galaxy clusters (e.g., Peng et al., 2008;
Harris et al., 2017; Alamo-Martínez et al., 2013), which early on were also
associated with the intercluster medium (ICM; e.g., Jordán et al., 2003;
Bassino et al., 2003).

There are different mechanisms suggested for the formation of globulars. Old
globulars, among the oldest stellar structures in our universe (e.g., Ricotti
et al., 2016), could be formed through rapid processes (such as the collapse
of gas clouds, e.g., Peebles & Dicke, 1968; Forbes et al., 2018) in the early
stages of the universe (such as the Epoch of Reionization at $z\sim 6$). On
the other hand, the peak formation of globulars (i.e., their ages) may
coincide with the peak of cosmic star formation density in galaxies around
$z\sim 2$, suggesting they are formed via continuous star formation in gas-
rich environments (Harris, 1991; Brodie & Strader, 2006; Forbes et al., 2018).
Indeed, some observations have suggested such a scenario by finding young
globulars in dense, gas-rich merging systems (Schweizer & Seitzer, 1998; de
Grijs et al., 2001; Trujillo-Gomez et al., 2021) and current theoretical
models mostly assume such a co-evolutionary scenario (e.g., Pfeffer et al.,
2018; Choksi & Gnedin, 2019; Li & Gnedin, 2019; El-Badry et al., 2019). There
are also observational hints of cluster formation from cooled gas from the ICM
to the galaxy cluster core (e.g., Holtzman et al., 1992). For an in-depth
discussion of the different globular cluster formation mechanisms, we refer
the readers to Kruijssen (2015).

Age determination based on main-sequence turnoff from colors of single stars
and cooling curves from long-lived white dwarfs suggest a dominant population
of very old globulars with a range of metallicity as well as a “young” branch
for which metallicity is anti-correlated to age (Harris & Racine, 1979; Krauss
& Chaboyer, 2003; Marín-Franch et al., 2009; Forbes & Bridges, 2010;
VandenBerg et al., 2013; Leaman et al., 2013; Forbes et al., 2015, 2018;
Kruijssen et al., 2019; Massari et al., 2019). The latter may be associated
with disruption events of dwarf galaxies and accretion (in-situ vs. ex-situ
formation, see also Kruijssen et al. 2019). Among the young globulars, the
metal-poor population is slightly older than the metal-rich population ($12.5$
vs. $11.5\,{\rm Gyrs}$; Forbes et al. 2018), however, these differences are of
low significance due to uncertainties in the age measurements. Similarly, the
absolute ages of the oldest and metal poor globulars have a significant range;
Alternative age measurements by Forbes et al. (2015) (assuming that the
metallicity of globulars follows the galaxy mass$-$metallicity relation)
suggest that even the oldest, metal-poor globulars form at $z<5.9$, i.e. after
the reionization of the early universe.

The interacting galaxies in the SMACS0723 galaxy cluster environment may be
the place to look for evidence for the formation of compact star clusters at
$z~{}=~{}0.39$ $-$ approximately $4.3\,{\rm Gyrs}$ before the observation of
Milky Way or local globulars. The galaxies are clearly interacting as shown by
the evident diffuse intracluster light (e.g., Pascale et al., 2022),
suggestive of stars being stripped from the galaxies. The new JWST/NIRCam
observations at $1-5\,{\rm\mu m}$ show a considerable amount of relatively
blue and faint ($>28\,{\rm AB\,mag}$) point sources around the cluster members
(see also Lee et al., 2022). As shown in Section 3.5, this number of faint
point sources cannot be explained by Milky Way stars, nor globulars in the
Milky Way, which, at sizes of $\sim 10\,{\rm pc}$ would be resolved and
significantly brighter. These objects are good candidates for globular
clusters and their study may inform us about the formation of globulars at
higher redshifts.

The large angular coverage of the two NIRCam fields of view (FoV), being
offset from each other by $\sim 1\,{\rm Mpc}$ at the cluster’s redshift, allow
also a spatial study of globulars around the brightest cluster galaxy (BCG).
If recently formed star clusters are stripped from their host galaxies due to
the interactions in the galaxy cluster, we would expect these to be relatively
young and metal abundant compared to those originating from an early-formation
scenario. Furthermore, the size and masses of these compact star clusters may
differentiate them from stripped cores of dwarf galaxies (e.g., Ideta &
Makino, 2004).

This paper is organized as follows: In Section 2, we detail the data used in
this work, the selection of the compact star clusters, and various
measurements. In Section 3, we present the results from our analysis. We
conclude in Section 4. Throughout this work, we assume a $\Lambda$CDM
cosmology with $H_{0}=70\,{\rm km\,s^{-1}\,Mpc^{-1}}$, $\Omega_{\Lambda}=0.7$,
and $\Omega_{\rm m}=0.3$. All magnitudes are given in the AB system (Oke,
1974) and stellar masses and star formation rates (SFRs) are normalized to a
Chabrier (2003) initial mass function (IMF) unless noted differently.

##  2 Data and Measurements

###  2.1 Data

In this work, we focus on compact stellar clusters in the galaxy cluster
environment SMACS J0723.3-7327 at $z=0.39$ (07h23m13.3s, -73d27m25s).
SMACS0723 was initially discovered as part of the southern extension to the
ROSAT All-Sky Survey (Voges et al., 1999) based Massive Cluster Survey (MACS;
Ebeling et al., 2001) and also detected by Planck (Planck Collaboration et
al., 2011) through the Sunyaev-Zel’dovich effect. It was then subsequently
studied by the Reionization Lensing Cluster Survey using the Hubble space
telescope (RELICS, Coe et al., 2019). A new study using JWST by Mahler et al.
(2022) places the total mass of the cluster at $M_{\rm<400\,kpc}=3\times
10^{14}\,{\rm M_{\odot}}$ (compared to the measurement by Planck of $M_{\rm
500}=8\times 10^{14}\,{\rm M_{\odot}}$). The BCG has a stellar mass of $\sim
2\times 10^{11}\,{\rm M_{\odot}}$ (close to the “knee” of the galaxy stellar
mass function, e.g., Davidzon et al. 2017) and resembles a relatively
featureless elliptical galaxy with little to no ongoing star formation. Here,
we use new JWST observations of the cluster (ERO program ID 2736; Pontoppidan
et al., 2022) taken with the Near Infrared Camera (NIRCam; Rieke et al., 2005)
broad-band filters F090W ($0.90\rm\mu m$), F150W ($1.50\rm\mu m$), F200W
($1.99\rm\mu m$), F277W ($2.76\rm\mu m$), F356W ($3.57\rm\mu m$), and F444W
($4.41\rm\mu m$). These filters correspond to wavelengths in the cluster’s
rest-frame of $0.65\rm\mu m$, $1.08\rm\mu m$, $1.43\rm\mu m$, $1.98\rm\mu m$,
$2.57\rm\mu m$, and $3.17\rm\mu m$, respectively. NIRCam consists of two
modules, each observing a $2.2\arcmin\times 2.2\arcmin$ FoV, one centered on
the cluster’s BCG and the other one centered $\sim 3\arcmin$ ($\sim 1\,{\rm
Mpc}$ at the cluster’s redshift) to the south-west. The data were downloaded
from the Mikulski Archive of Space Telescopes (MAST)111https://mast.stsci.edu/
and subsequently reduced with the JWST data reduction pipeline. The reduced
image data were then combined using the grism redshift and line analysis
software for space-based spectroscopy (Grizli; Brammer & Matharu, 2021)
package to a final pixel scale of $0.02\arcsec/{\rm px}$ for F090W, F150W, and
F200W and $0.04\arcsec/{\rm px}$ for F277W, F356W, and F444W, respectively
(Brammer, 2022). Note that the recent jwst_0942.pmap photometric calibration
reference file was used with modifications as of September 5 2022 as described
in the Grizli Github repository222https://github.com/gbrammer/grizli/pull/107.
The details of the data reduction will be presented in detail in an upcoming
paper (Brammer et al., in prep). The field was also imaged by JWST/MIRI at
mid-infrared wavelengths. However, the MIRI data is too shallow for this study
and is therefore not being used. Figure 1 shows an overview of the data used.

Figure 2: Left: 1-dimensional light profiles of the extracted compact star
clusters (purple; stacked in each filter) and the PSF (gray) in all $6$ NIRCam
filters. This shows the unresolved nature of the extracted sources. Right:
Simulation to assess the maximum upper limit in size of an unresolved source
given the PSF in the NIRCam/F150W filter (black). We simulated sources with
half-light radii of 20, 50, 100, and $200\,{\rm pc}$ (blue, orange, green, and
red lines) at $z=0.39$ and a peak flux of $20\,{\rm nJy}$, consistent with
observations of the F150W stack (see left panel). We convolved those profiles
with the PSF (which is shown as the thick black line) and include realistic
noise from the real observations. We find that we would be able to resolve
sources larger than $50\,{\rm pc}$. Hence, the selected compact star clusters
must have sizes less than $50\,{\rm pc}$. The lower panel shows the residual
(source$-$PSF profile).

###  2.2 Source Selection

In this work, we study the faintest, compact stellar clusters in the SMACS0723
field, such as potential globular clusters around the cluster host galaxies.
These sources are selected manually mainly on the F200W image, however, we
require them also to be detected in at least two other bands in order to
reject potential spurious sources. In addition, the sources are selected to be
unresolved point sources as well as faint (to exclude Milky Way stars, see
Section 3.5). For example, a good upper limit in size of globulars is $\sim
10\,{\rm pc}$ (e.g., Larsen et al., 2001), which, at $z=0.39$, corresponds to
an angular size of $\sim 1.4$ milliarcseconds (note that there are some larger
globulars, for example NGC 2419 in the Milky Way and Lindsay 1 in the Small
Magellanic Cloud). This is significantly smaller than the PSF size (between
$20$ and $120$ milliarcseconds at $1-5\,{\rm\mu m}$), thus motivating the
point-source assumption. Milky Way stars are the most likely contaminants in
this selection, as discussed in Section 3.5. We tried an automated selection
of globulars, however, we found that this approach results in a severely
incomplete selection due to blending with the BCG and other cluster galaxies,
as well as the variation of the intracluster and scattered light across the
field. In total, we identified $178$ compact star clusters in the full FoV of
NIRCam around the cluster host galaxies (see Figure 1), which we characterize
and study in the following. The coordinates and NIRCam fluxes of the extracted
star clusters are listed in Table LABEL:tab:photo. We note that our selection
is not complete, but serves as a starting point to understand the properties
and origin of these faint sources. We refer to the work by Lee et al. (2022)
for a detailed study of the distribution and number density of these star
clusters in the ICM of SMACS0723. If these sources are globular clusters, we
would expect to only see the tip of the iceberg (i.e. the brightest ones) even
at the unprecedented depths of these observations, assuming the commonly used
Gaussian globular cluster luminosity function (e.g., Alamo-Martínez et al.,
2013).

###  2.3 Measurement of the PSF

To measure the photometry of unresolved point sources, a robust determination
of the point spread function (PSF) is crucial. Here, we measure the PSF in all
$6$ NIRCam filters by stacking stars on the full FoV of the available
observations. For the selection of stars, we use an identical approach as in
Faisst et al. (2022). Summarizing, the stars are selected based on the $R_{e}$
vs. magnitude diagram (produced by the flux_radius and flux_auto quantities
derived by SExtractor (Bertin & Arnouts, 1996) run the NIRCam images). We note
that, based on the upturn in size measurements on that diagram, point sources
at $\sim 25\,{\rm mag}$ already start to enter the non-linear regime towards
saturation at the depth of these NIRCam observations. We therefore require
stars between $25\,{\rm mag}$ and $27\,{\rm mag}$, to avoid the aforementioned
saturation effect as well as to exclude potential faint, spurious sources. In
addition, a half-light radius of less than $3\,{\rm pixels}$ is required to
select unresolved sources. For each of the $58$ stars, we create a
$2\arcsec\times 2\arcsec$ cutout and subsequently center the stars before
stacking them to obtain the final PSF. The final PSF for each filter
(normalized and of the same pixel scale as the images, see Section 2.1) are
available for download333https://github.com/afaisst/JWST_SMACS_PSFs.

The relatively low number density of stars does not allow us to quantify
variations of the PSF. However, the recent study by Nardiello et al. (2022)
measured PSF variations across the NIRCam FoV based on stars in the globular
cluster M 92, finding variations in the FWHM of up to $15-20\%$. Such
variations have a negligible effect on the measured photometry in our case,
but we will include this effect later when we constrain the sizes of our
compact star clusters.

###  2.4 Measurement of Photometry

The photometry of the selected globulars is measured using the software
Tractor444http://thetractor.org/ (Lang et al., 2016a, b; Weaver et al., 2021),
which performs a prior-based forced photometry including the PSF of the
observations. We first compared the 1-dimensional projected light profiles
from the stack of all compact star clusters to the one of the PSF (left panel
of Figure 2). This test shows that the star clusters are indeed consistent
with unresolved point sources, hence we use the point-source fitting option of
Tractor. In the following, we fit the photometry of individual sources to
study the variations in the stellar population across our sample. We also
derive the photometry from the stacks of the sources in each of the $6$ NIRCam
filters to study the average properties. In both cases, we create cutouts of
$0.8\arcsec$ size of all the sources. The stacks were created by first
performing a local background subtraction (measured in a sky annulus with
inner radius of $5\,\rm px$ and outer radius of $10\,\rm px$) on the
individual cutouts and then combining them via median stacking. The following
steps are then identical for the fitting of individual sources and the stacks.
Tractor is run on the $0.8\arcsec$ cutouts by applying a point source model,
using the F200W position of the sources as prior (determined from the 0-order
moment of light on the source). During the fitting, the position is free to
vary within $\pm 2\,{\rm pixels}$ of the prior position. This helps to
mitigate potential misalignments between the different image products. In
addition, we let Tractor fit and subtract the (slowly varying on $0.8\arcsec$
scales) local background at the position of the source to remove the
contribution of the halo from nearby cluster galaxies and the intracluster
light. Note that for that reason, simple aperture photometry will result in
overestimated flux measurements. The inverse variance image (used for error
estimation) is created as $1/\sigma^{2}$ with $\sigma$ derived from
$\sigma-$clipping statistics on a large region of the image not contaminated
by the intracluster light and other galaxies. The variance output by Tractor
is used to obtain the uncertainties on the flux measurements.

Figure 3 shows the fits to the stacked cutouts of the compact star clusters in
the six different bands. The point source assumption is also validated by the
residuals, which are consistent with zero. The NIRCam $6$-band photometry
derived for the stack is listed in Table 2.

Figure 3: We use the Tractor software package to fit point source profiles to
the selected compact star clusters in the highly blended cluster environment.
The first column shows the stacked cutouts in each of the NIRCAM band. The
second and third columns show the best-fit model and the residual,
respectively. The rows show the fits for the $6$ NIRCam filters. The measured
total flux values in nJy are indicated. The intensity scale is the same for
each row (the residuals are consistent with zero) and all cutouts are
$0.8\arcsec$ in size.  Figure 4: Properties of the compact star clusters found
in the SMACS0723 field. Left panel: Magnitude distribution in F090W (blue),
F200W (orange), and F444W (red semi-filled). The vertical gray area shows the
range in $3\sigma$ limits in the three filters shown. The blue filled
histogram shows the expected number of Milky Way stars from Wainscoat et al.
(1992) towards the cluster field within the full NIRCam FoV. The dark blue
horizontal lines show the same for the combined number of M/L/T stars from
Kirkpatrick et al. (2021). Middle panel: The distribution of the extracted
compact star clusters (purple circles; median as purple star) in color space.
Typical errors in the colors are shown by the error bars in black (lowest
$10\%$ and median errors). The distribution of (de-reddened) colors of star
forming (gray) and quiescent (red) galaxies at $z=0.39$ from the COSMOS2020
catalog (Weaver et al., 2022) is shown. The star clusters match with the color
distribution of the quiescent galaxy population. The A${}_{\rm v}=2\,{\rm
mag}$ extinction vector is also shown. Right panel: The $2.2\,{\rm\mu m}$
magnitude vs. stellar mass relation of quiescent galaxies (red dots) is
similar to the one of the star clusters, indicating a similar $K-$band M/L
ratio. The stellar masses of the star clusters (median of
$2.4^{+3.0}_{-1.5}\times 10^{6}\,{\rm M_{\odot}}$, see inset) are derived from
the M/L ratio of the best-fit SSP models (Section 3.1.3).

###  2.5 SED Fitting

To study the properties of the compact star clusters, we fit simple stellar
population (SSP) models to the photometry of the median stacks obtained in
Section 2.4. We assume that the star clusters have been formed in a single
burst, thus are well described with an SSP model. Given the low sampling in
wavelength of these data, we think that this is a good approximation as
multiple stellar populations would be difficult to tell apart if they exist.
Before fitting, we need to correct the extracted flux densities for Milky Way
dust extinction, which we obtain from the Schlegel et al. (1998) dust
maps555Specifically, we use the sfdmap Python package
(https://github.com/kbarbary/sfdmap) recalibrated by Schlafly & Finkbeiner
(2011). The dust extinction towards the SMACS0723 is significant at an
$E(B-V)\sim 0.2\,{\rm mag}$ level, which results in an wavelength-dependent
extinction of $\sim 0.25\,{\rm mag}$ at $0.9\,{\rm\mu m}$, $\sim 0.07\,{\rm
mag}$ at $2.0\,{\rm\mu m}$, and less than $0.03\,{\rm mag}$ at $4.4\,{\rm\mu
m}$ assuming the Fitzpatrick (1999) dust extinction curve. We use these values
to correct the measured flux densities of the star clusters. For our fiducial
SSP models, we chose Padova 1994 stellar evolutionary tracks (Bertelli et al.,
1994) together with the Basel Stellar Library (BaSeL, version 3.1; Lejeune et
al., 1997, 1998; Westera & Buser, 2003) complemented by the empirical STELIB
library (Le Borgne et al., 2003)666http://svocats.cab.inta-
csic.es/stelib/index.php at wavelengths blueward of $9500\,{\rm\AA}$ (see
Bruzual & Charlot, 2003). In the following, we assume a Chabrier (2003) IMF.
These fiducial SSP models were created using the software
GALAXEV777http://www.bruzual.org/bc03/ in a grid of different ages and stellar
metallicities. Specifically, the age grid ranges from $0.5\,{\rm Gyrs}$ to
$11\,{\rm Gyrs}$ in steps of $0.5\,{\rm Gyrs}$ and we use $6$ different
stellar metallicities of $0.005$, $0.02$, $0.2$, $0.4$, $1$, and $2.5\,{\rm
Z_{\odot}}$. We compared the results using these fiducial models to other SSP
models as well. Specifically, we compared to the MIST stellar tracks (Dotter,
2016; Choi et al., 2016), based on the MESA isochrones (Paxton et al., 2011,
2013, 2015, 2018)888https://waps.cfa.harvard.edu/MIST/index.html, assuming a
BaSeL stellar library. These additional SSP models are created using the
Flexible Stellar Population Synthesis code (FSPS; Conroy et al., 2009; Conroy
& Gunn, 2010)999https://github.com/cconroy20/fsps. A Python wrapper (Johnson
et al., 2021) exists at this link: https://dfm.io/python-fsps/current/. for a
Chabrier IMF and using the same age and metallicity grid. Generally, we find
that wavelengths blueward of $\sim 1\,{\rm\mu m}$ rest-frame are most affected
by the choice of these different models. We will comment on the differences in
the results in Section 3. The fit to the various models was performed by
$\chi^{2}$ minimization using the SciPy least-squares Python package. We note
that we fixed the redshift of the compact star clusters to the one of the
galaxies in the SMACS0723 cluster ($z=0.39$). In Section 3.1.1 we will show
that this is indeed a good assumption based on the similarity in colors of the
star clusters and galaxies at $z=0.39$. Also, small changes in redshift (e.g.,
due to the kinematics in the cluster environment) do not have an impact on the
fitted properties.

Figure 5: Results from fitting the photometry of all extracted compact star
clusters. Left Panel: $\chi^{2}$ map of the age vs. metallicity grid with
$3\sigma$, $4\sigma$, and $5\sigma$ contours indicated. The cross marks the
best-fit solution ($0.2\,{\rm Z_{\odot}}$ and $1.5\,{\rm Gyrs}$). The age of
the universe at $z=0.39$ ($9.3\,{\rm Gyrs}$) is indicated by the horizontal
white line. For the full globular population we find an age of
$1.5^{+0.5}_{-0.5}\,{\rm Gyrs}$ and a best-fit metallicity of $20-30\%$ solar.
Metallicities of $<20\%$ or more than solar are ruled out at high
significance. Right Panel: Data (black symbols) and best-fit SSP model (black
line) shown with other models of different age and metallicity combinations
(see legend). While different metal abundances produce different SEDs at
$<1.5\,{\rm\mu m}$, older ages are difficult to discern. Better wavelength
sampling with medium-band filters at $2-3\,{\rm\mu m}$ and $4-4.5\,{\rm\mu m}$
wavelengths would constrain older ages better. The colored lines show black
body models at different temperatures normalized to $1\,{\rm\mu m}$.

##  3 Results

###  3.1 Properties of Globular Clusters

####  3.1.1 Photometry and Colors

Figure 4 show the observed photometric properties of the extracted compact
star clusters in SMACS0723. As shown on the left panel, the brightness of the
star clusters ranges from $28$ to $30\,{\rm mag}$ in F090W and $27.5$ to
$29.5\,{\rm mag}$ in F200W (left panel). The NIRCam filters cover the
(redshifted) $2\,{\rm\mu m}$ peak, hence the F090W and F444W brightness is
similar. The middle left panel shows the color distribution of the compact
star clusters (purple circles) compared to star forming (gray) and quiescent
(red) galaxies selected in the COSMOS2020 catalog (Weaver et al., 2022) at a
redshift $z=0.39$ with $\Delta z~{}=~{}0.2$101010We interpolate the Suprime-
Cam/$z$, UltraVISTA/$H$, UltraVISTA/$K_{s}$, and Spitzer/IRAC $3.6\,{\rm\mu
m}$ fluxes from COSMOS2020 to obtain the corresponding fluxes in the
JWST/NIRCam filters F090W, F150W, F200W, and F277W.. Due to their SED shape,
which is due to the redshifting of the 1.6$\mu$m bump through the bandpasses,
the globulars reside mostly at red [F090W]$-$[F150W]$\,\gtrsim 0$ colors and
blue [F200W]$-$[F277W]$\,\lesssim 0$ colors. This parameter space is similar
to quiescent galaxies at the same redshift, suggesting similar stellar
populations. However, the star clusters are significantly fainter, $2-4\,{\rm
mag}$ below the detection limits of the COSMOS surveys (right panel).

####  3.1.2 Population-Averaged Ages and Metallicities

We note that these star clusters are faint even for JWST and most of the
individual star clusters are detected at very low S/N in blue and red bands
where their SED flux drops. We therefore first fit SSP models (see Section
2.5) to the photometry derived from the stacked cutouts to obtain a
population-averaged median age and stellar metallicity measurement. The
following values for metallicity and age are therefore an average of the
studied relatively massive cluster population (see also Section 3.3). Later in
Section 3.2 we will fit individual star clusters to study the population
variations of these properties.

Figure 5 shows the results from SED fitting using our fiducial SSP models
(Padova stellar tracks) to the stacked photometry. The left panel shows a
$\chi^{2}$ map for the adopted age and metallicity grid with $3\sigma$,
$4\sigma$, and $5\sigma$ contours indicated. We find a best-fit age of
$1.5^{+0.5}_{-0.5}\,{\rm Gyr}$ and a best-fit metallicity of $0.2-0.3\,{\rm
Z_{\odot}}$ ($3\sigma$). Interestingly, the $\chi^{2}$ map also indicates the
presence of a younger ($<1\,{\rm Gyr}$) and more metal rich ($0.4-1.0\,{\rm
Z_{\odot}}$) solution. The right panel of Figure 5 shows the data (black
symbols) with the best-fit SED (black line) as well as other models (see
legend in figure) for comparison with the same age or metallicity as the best
fit.

The data excludes with high significance metallicities below $0.2\,{\rm
Z_{\odot}}$ as well as solar/super-solar. This is because changes in
metallicity affect the colors significantly at a fixed age. For example,
compare the $1.5\,{\rm Gyr}$ model at $0.02\,{\rm Z_{\odot}}$ (gray dotted
line) and at $2.5\,{\rm Z_{\odot}}$ (gray dashed line) with the best fit
($0.2\,{\rm Z_{\odot}}$) in the right panel of Figure 5.

On the other hand, ages are not constrained well by our current data,
especially with the JWST filters available. For example, ages up to $5\,{\rm
Gyrs}$ cannot be excluded at better than $4\sigma$ level and maximal ages of
the Universe at $z=0.39$ ($9.3\,{\rm Gyrs}$) are possible at $5\sigma$ level.
This is expected by the lack of blue coverage of the JWST filters, and in
addition the relation between color and age only changes weakly for SSPs with
ages older than $\sim 3\,{\rm Gyr}$. For example, the [F090W]$-$[F200W] color
(corresponding to rest-frame $(r-H)$ color) changes by $0.4-0.6\,{\rm mag}$
(depending on metallicity) for ages $<3\,{\rm Gyr}$ (caused by hot massive
stars), while it only changes by $\sim 0.2\,{\rm mag}$ thereafter. We note
that a better sampling of the observed $0.5-1.5\,{\rm\mu m}$ regime could
constrain the older ages better (see Figure 5).

In addition, we quantify the reliability of these results by comparing to fits
using the MIST isochrones as discussed in Section 2.5. We find that the models
differ significantly at wavelengths blueward of $\sim 1\,{\rm\mu m}$ rest-
frame for low metallicities and low ages. However, we find overall that our
results are robust against the choice of different model parameterizations.
Specifically, using the MIST isochrones, we find consistent ages of
$1.5^{+0.5}_{-0.5}\,{\rm Gyr}$ and a best-fit metallicity of $0.4\,{\rm
Z_{\odot}}$ with a slightly larger $3\sigma$ range of $0.2-0.4\,{\rm
Z_{\odot}}$. Similarly to the other models, metallicities of $<0.2\,{\rm
Z_{\odot}}$ as well as solar metallicities are robustly excluded.

####  3.1.3 Stellar Masses

From the best-fit SSP models obtained for each individual star cluster, we
derive a $V-$band mass-to-light (M/L) ratio from which we can estimate the
total stellar masses of the compact star clusters. For the best-fit SSP model
fit to the stacked photometry, we derive a M/L ratio of $0.45\,{\rm
M_{\odot}\,L_{\odot}^{-1}}$. The M/L ratios of the individual star clusters
range from $0.2-4.8\,{\rm M_{\odot}\,L_{\odot}^{-1}}$. With the $V$-band
luminosity derived from the NIRCam/F090W filter (which is close to the $\sim
5500\,{\rm\AA}$ $V$-band in rest-frame), we derive stellar masses for the
individual star clusters and we find a median of $2.4^{+3.0}_{-1.5}\times
10^{6}\,{\rm M_{\odot}}$ (using the M/L ratio derived from the stacked SED
would result in a stacked median stellar mass of $3.9^{+3.2}_{-1.8}\times
10^{6}\,{\rm M_{\odot}}$).

As shown on the right panel in Figure 4, the star clusters line up well with
quiescent galaxies at $z=0.39$ on the $K-$band magnitude vs. stellar mass
diagram. This suggest that these compact star clusters have a similar M/L
ratio as quiescent galaxies at the same redshift. Assuming the quiescent
galaxy M/L relation, we would obtain an average stellar mass of
$3.3^{+1.6}_{-1.1}\times 10^{6}\,{\rm M_{\odot}}$.

We can compare this obtained M/L ratio to what is measured for globular
clusters in the Milky Way and local galaxies. The M/L ratios depend on the age
(hence mass itself) and metallicity of the stellar population. Given the
estimated age and metallicity of our star clusters, we find a possible range
in M/L of $1-4\,{\rm M_{\odot}\,L_{\odot}^{-1}}$ in rest-frame $V$-band
according to the observations and models in Kruijssen (2008). Note that the
M/L ratio increases with age, hence the upper end of this range would be
applicable to old globulars, while the lower end is more common in young star
clusters. Our measured M/L is consistent with younger ages.

Summarizing, the masses derived for our compact star clusters are on the high-
end of what is expected for globular star clusters in local galaxies (see also
Figure 6). Furthermore, the high-mass end of the derived mass range may
overlap with stellar masses estimated for Milky Way dwarf galaxies. To assess
this, we compare the size constraints on our compact star clusters with the
sizes of local dwarf galaxies.

Figure 6: Upper limits on the sizes of the compact star clusters (purple)
compared to sizes of $z=0.39$ galaxies from HST COSMOS-DASH (Mowla et al.,
2019; Cutler et al., 2022) in WFC3/F160W (light gray dots) and measured from
NIRCam/F150W at lower masses (dark gray dots). The line shows a linear fit to
the $M-R_{\rm e}$ relation. Also indicated are typical sizes of star-forming
regions in local galaxies (light blue hatched with $1\sigma$ percentile;
Larson et al., 2020), the sizes/masses of dwarf galaxies around the Milky Way
(black squares; Strigari et al., 2008), and sizes/masses of local globular
clusters (black box; Larsen et al., 2001; Hilker et al., 2020). The $z=0.39$
compact star clusters overlap with the massive end of the stellar mass
distribution of local globulars as well as with common masses of Milky Way
dwarf assuming they lose $\sim 90\%$ of their mass during close passages to
the BCG (black arrow).

####  3.1.4 Sizes

As established already in Section 2.4 and Figure 2, the selected compact star
clusters are unresolved, hence we are only able to place an upper limit on
their sizes. A conservative upper limit would be the NIRCam PSF size at $\sim
1.5\,{\rm\mu m}$, which is $\sim 180\,{\rm pc}$ at $z=0.39$. To measure a more
accurate upper size limit, we carry out a simple simulation as shown in the
right panel of Figure 2. Specifically, we simulate point sources of different
sizes (from $20$ to $200\,{\rm pc}$), which we convolve with the NIRCam/F150W
PSF (Section 2.3). We add realistic background noise measured from the real
NIRCam/F150W image and assume a point source peak flux of $20\,{\rm nJy}$,
which is consistent with the one measured for the stack in the same filter
(see left panel of Figure 2). This simple simulation shows that we would be
able to resolve sources larger than $50\,{\rm pc}$. We therefore place an
upper limit to the sizes of our compact star clusters of $50\,{\rm pc}$.

Figure 6 compares this size limit to other Galactic and extra-galactic sources
at similar stellar masses as derived for our compact star clusters (Section
3.1.3). The sizes of the galaxies at $z=0.39$ are taken from the HST COSMOS-
DASH morphology catalog (Mowla et al., 2019; Cutler et al., 2022) in HST
WFC3/F160W. At lower masses, we complement that sample with galaxies at the
same redshift directly extracted from the NIRSpec/F150W image111111The masses
and redshift are computed using the SED-fitting code EAZY (Brammer et al.,
2008; Brammer, 2022). Note, that we only extract sources from the NIRCam field
offset from the cluster’s BCG to avoid the effects of lensing on the size
measurements.. The sizes of these lower-mass galaxies are consistent with
extrapolating the $M-R_{e}$ relation at $>10^{9}\,{\rm M_{\odot}}$ (dashed
line) to these lower masses. The galaxies are clearly more extended than the
compact star clusters selected here. We also show average sizes of star-
forming clumps (blue hatched area showing $1\sigma$) in local galaxies taken
from Drazinos et al. (2013) and Larson et al. (2020). At the resolution of the
NIRCam observations, we would be able to marginally resolve such structures if
they were present in the (quiescent) SMACS0723 host galaxies. Similarly, we
would resolve objects similar in mass and size as the Milky Way dwarf
galaxies, here taken from Strigari et al. (2008)121212The masses were derived
from total luminosities given in Strigari et al. (2008) and assuming the mass-
to-light ratios of the galaxies measured by Revaz et al. (2009).. We caution
however, if the dwarf galaxies have been tidally stripped in the dense cluster
environment such that only the bright central core remains, we would likely
not be able to distinguish those from compact star clusters. For example, a
dwarf galaxy could lose more than $90\%$ of its mass during the first few
pericenter passages around its host galaxy (Ideta & Makino, 2004). This would
bring them to a mass consistent with our compact star clusters.

Figure 7: Individual compact clusters color-coded by their best-fit
metallicity (red scale) and age (blue scale). Note that each symbols has two
colors assigned (metallicity as edge-color and age as face-color). Light
symbols correspond to star clusters with low ages and metallicities, while
darker symbols correspond older and more metal rich star clusters. The
background shows a Gaussian kernel density estimation of the data points for
visual guidance of the density of points. The lines show models at different
metallicities (color of lines) as a function of age (running from left to
right, dots on lines represent ages of 0.5, 1, 4, and $9\,{\rm Gyrs}$).

###  3.2 Variations in the Properties of Star Clusters

As shown in the middle panel of Figure 1, the selected compact star clusters
span about $1.5-2\,{\rm mags}$ in color space, which could be indicative of
variations in age and metal properties. In the following, we try to
characterize these color variations in terms of variations in these physical
parameters.

For this, we fit the same SSP models as described in Section 2.5 to each
individual compact star cluster. We note that while the uncertainties of these
measurements for individual compact star clusters are rather large due to
their faintness, we still are able to investigate statistically trends of age
and metallicity in our sample. Figure 7 shows the individual star clusters on
the [F090W]$-$[F150W] vs. [F200W]$-$[F277W] color$-$color diagram color-coded
by the best-fit age (blue scale) and metallicity (red scale). Note that each
symbol has two colors assigned (metallicity as edge-color and age as face-
color). Light symbols correspond to star clusters with lower ages and
metallicities, while darker symbols correspond to star clusters with older
ages and higher metallicities. The background shows a Gaussian kernel density
estimation (including the uncertainties of the data points) to visualize the
most probably density of points. The lines indicate colors derived from the
SSP models for different metallicities and ages (running from left to right,
dots on lines indicated ages of 0.5, 1, 4, and $9\,{\rm Gyrs}$. Older models
result in redder [F090W]$-$[F150W] colors, while more metal rich models result
in a reddening of both colors.

The range in colors of the individual compact star clusters are coupled with
variations in ages and metallicity. This suggests different formation times
and possibly different formation processes (causing different metal contents)
of the star clusters in the SMACS0723 environment. We also note that the
observed color (hence metallicity) distribution may be expected to be affected
by the “blue tilt”, caused by a lack of the most massive, metal poor star
clusters (see Forbes & Bridges, 2010; Usher et al., 2018).

Figure 8:  Color vs. magnitude diagram in $(B-I)$ vs. $I$-band absolute
luminosity (in Vega system). The brown and gray points correspond to the
globulars around BCGs NGC 7720 and ESO444-G046 in the Abell 2634 and 3558
galaxy cluster, respectively, from Harris et al. (2014). The latter galaxy
cluster is $1.7$ times more massive than the former but still $1.7$ times less
massive than SMACS0735. The compact star clusters studied in this work at
$z=0.39$ are shown as purple circles. They occupy the bright end at relatively
blue $B-I$ colors consistent with the more massive of the two local galaxy
cluster shown.

###  3.3 Comparison to Local Globular Clusters

In the following, we compare the BCG and the identified compact star clusters
to systems in the local universe.

The BCG of the SMACS0723 cluster has a stellar mass of $\sim 2\times
10^{11}\,{\rm M_{\odot}}$ and a $V$-band absolute magnitude of $\rm
M_{V}^{Vega}\sim-23.2$131313The $V$-band magnitude was derived from HST
photometry and subsequently converted to the Landolt $V$ in Vega system to be
consistent with the literature., which is at the faint end of the brightness
distribution of the BCGs studied in Harris et al. (2014) ($-24.1\lesssim\rm
M_{V}^{Vega}\lesssim-23.0$). The $V$-band luminosities of our compact star
clusters range between $2.5\times 10^{6}\,{\rm L_{\odot}}$ and $3.1\times
10^{7}\,{\rm L_{\odot}}$, which is about $1-2$ orders of magnitudes brighter
than the common turnover luminosity of the globular cluster luminosity
function at $\sim 10^{5}\,{\rm L_{\odot}}$ (Larsen et al., 2001; Harris et
al., 2014). (Note that the lower limit is due to the sensitivity limit of the
JWST observations.) In this luminosity range, the luminosity functions of
globulars around local BCGs with similar luminosity find about $100$ globular
clusters (Harris et al., 2014), which is $60\%$ less than what we find in the
SMACS0723 cluster field. Several reasons could contribute to this differences.
First, the SMACS0723 galaxy cluster is more massive ($8\times 10^{14}\,{\rm
M_{\odot}}$ as measured by Planck) compared to the Abell clusters ($1-5\times
10^{14}\,{\rm M_{\odot}}$), which affects the number of globulars. For
example, as shown in Harris et al. (2014), the luminosity function of
globulars around the BCG in Abell 3558 ($4.7\times 10^{14}\,{\rm M_{\odot}}$)
peaks at two times higher number densities as compared to the one of the less
massive cluster Abell 1736 ($2.8\times 10^{14}\,{\rm M_{\odot}}$). Second, our
selection includes the full ICM (over several $100\,{\rm kpc}$, see Figure 1),
which may lead to the inclusion of globular clusters around other galaxies in
the vicinity of the BCG. Finally, as pointed out in Section 3.1.4, we might
also include the tidally stripped compact cores of dwarf galaxies in our
sample. Given the above points, the number of compact star clusters is close
to what is expected based on local observations.

Note that $>50\%$ of our compact star clusters have $\log(L/L_{\odot})>6.7$
and thus would be considered as superluminous globulars according to Harris et
al. (2014). Such superluminous objects could be related to ultra compact dwarf
galaxies (or the stripped cores thereof) or bridge the gap between globulars
and dwarf galaxies. These object have been found in several rich local galaxy
clusters (e.g., Misgeld et al., 2011; Mieske et al., 2012). SMACS0723 is a
massive galaxy cluster at these redshifts (approximately a factor of two more
massive than local galaxy clusters studied in Harris et al.), hence the large
occurrence of such superluminous globulars would not surprising.

Finally, we compared the color distribution of our compact star clusters to
the globulars around local BCGs from Harris et al. (2014). Figure 8 shows the
$(B-I)_{\rm Vega}$ vs. M${}_{I}^{\rm Vega}$ color-magnitude diagram for our
extracted compact star clusters at $z=0.39$ (purple circles)141414These
quantities have been measured on the best-fit de-reddened rest-frame SSP
models to the individual star clusters in the Landolt filter system (in Vega
magnitudes) to be consistent with other works. Note that the JWST data does
not cover the rest-frame $B$ and $I-$bands. Their fluxes are extrapolated from
the best-fit models. as well as globulars around the local galaxies NGC 7720
(gray) and ESO444-G046 (brown), which are the BCGs of the clusters Abell 2634
and 3558, respectively. The former BCG is brighter ($-23.8$ vs. $-23.4\,{\rm
Vega\,mag}$) and resides in a more massive cluster ($4.7\times 10^{14}$ vs.
$1.5\times 10^{14}\,{\rm M_{\odot}}$), which, however, is still $1.7$ times
less massive than SMACS0723. The compact star clusters studied in this work at
$z=0.39$ reside at the bright end of the distribution of local globulars.
Their colors are consistent with the colors of globulars in Abell 3558, the
more massive one of the two local galaxy clusters shown in Figure 8. This is
consistent with the idea that the brightness of the globular clusters scales
with the mass of the galaxy clusters.

###  3.4 Comparison to Higher Redshift Globulars

Recent studies by Mowla et al. (2022) and Claeyssens et al. (2022) examined
the properties of individual globular star clusters in SMACS0723 field of
lensed galaxies at higher redshifts. The significant magnification (up to
$100\times$) due to lensing allows the authors of these studies to probe
fainter star clusters in the mass range of $10^{5}-10^{7}\,{\rm M_{\odot}}$.
However, the wavelength range probed by the JWST NIRCam filters is bluer due
to the higher redshift of the sources, which may affect how well different
properties of the clusters can be constrained with the given photometry. The
Claeyssens et al. (2022) study finds relatively young ages of 100s of Myrs up
to $\sim 1\,{\rm Gyr}$ for the studied star clusters around $18$ galaxies in
the redshift range $1.3<z<7.7$. The star clusters are consistent local
globulars in terms of their size and stellar mass. These ages are $\sim
1-2\,{\rm Gyr}$ younger than what is measured for our BCG star clusters at
$3\sigma$, which is in line with the formation of star clusters over cosmic
time. On the other hand, Mowla et al. (2022) study in detail a system dubbed
as the “Sparkler” at $z=1.378$ and find ages of $3-5\,{\rm Gyrs}$ for $6$ out
of the $12$ star clusters. This would indicate that these star clusters have
been formed during the early reionization phase of the intergalactic medium at
$z=8-11$, which would be an interesting but also extreme scenario for cluster
formation as understood by current models and other observations of lensed
galaxies at high redshifts (see discussion in Claeyssens et al. 2022 and
references therein as well as, for example, Vanzella et al. 2017). We note
that Claeyssens et al. find much younger ages ($\sim 100\,{\rm Myrs}$) for the
same star clusters. Understanding this disagreement is beyond the scope of our
paper, however, there could be multiple reasons such as aperture vs. PSF
fitting photometer methods, the inclusion of galactic extinction, differences
in SSP models and SED fitting codes, as well as differences in the JWST
photometric calibration references.

###  3.5 A Final Word on Milky Way Stars

Due to their point-like nature and faintness, cool dwarf stars in our Milky
Way could be mistaken as globular clusters in the $z=0.39$ host galaxies. A
significant contamination of our sample by such stars is, however, ruled out
by two reasons.

First, as shown in Figure 5, black body models (representing cool Milky Way
dwarf stars from $3000-3400\,{\rm K}$) are not consistent with the extracted
photometry of our sources. Specifically, the mid-infrared peak is redshifted
consistent with the redshift of the cluster galaxies ($z=0.39$). A combination
of black body models (i.e. stars of different temperatures) would be necessary
to explain the observed photometry. We note that due to the stacking analysis,
stars of different temperatures can be combined, leading to a similar SED as
the stacked photometry of the star clusters in our sample. As an additional
test, we therefore compared the photometry of randomly picked star clusters to
point sources (i.e. stars) at comparable faint magnitudes selected from the
parallel NIRCam module off the center of SMACS0723. We find that the mid-
infrared peak emission between the two samples is significantly offset (as a
results of the redshift), suggesting negligible contribution of stars to the
stack.

Second, the predicted number of stars in the NIRCam FoV is low compared to the
selected compact star clusters. Specifically, we predicted the number of stars
and brown dwarfs from the Wainscoat et al. (1992) as well as the Kirkpatrick
et al. (2021) models. The former model is in good agreement with the number of
stars in the COSMOS field (Scoville et al., 2007) as shown in Fajardo-Acosta
et al. (2022), however, it does not include consistently M, L, and T spectral
types, which start to contribute significantly at fainter magnitudes. The
expected number of stars from the Wainscoat and Kirkpatrick models are shown
on the left panel of Figure 4 as blue histogram and dark blue horizontal
lines, respectively. We would expect on the order of $\sim 20$ stars and
dwarfs over the full FoV of NIRCam, and approximately $5$ over the area where
the compact star clusters are found (see Figure 1).

The negligible contribution of Milky Way stars to our sample is also suggested
by comparing the number of selected star clusters in the FoVs of the two
NIRCam modules. Specifically, the parallel module off-center of the SMACS0723
cluster should be dominated by Milky Way stars. Repeating the sample selection
on that field results in only $\sim 10$ point sources at similar magnitudes as
the selected star clusters. Conservatively assuming that these are all stars
and that the stellar density is the same in both FoVs, we would expect $<10$
out of the $178$ selected compact star clusters to be Milky Way stars.

Vice versa, we note that globulars and dwarf galaxies in and around our Milky
Way would be easily resolved by JWST and can therefore be ruled out.

##  4 Summary and Conclusions

JWST’s depth and resolution provides the exciting opportunity to study the
faintest and most compact star clusters in our universe. Here, we use the
NIRCam early release observations of the SMACS0723 galaxy cluster at $z=0.39$
to study a population of $178$ compact star clusters residing in the
intracluster region.

We extract the photometry of these point sources with the Tractor software
using robust PSF measurements. We note that there is considerable Galactic
dust extinction towards the SMACS0723 field, which needs to be corrected for.
We find that the compact star clusters occupy a similar location in
[F090W]$-$[F150W] vs. [F200W]$-$[F277W] color space as quiescent galaxies at
the same redshifts (Figure 4). However, the star clusters are more than $2-4$
magnitudes fainter than the detection limits of current wide-field surveys and
have sizes that are smaller than $50\,{\rm pc}$ (Figures 2 and 6).

The photometry of the star clusters is fit with SSP models to obtain
constraints on their masses, age, and stellar metallicity (Figure 5).
Different stellar models are tested and the results are found to be robust
under the different choices. We derive metallicities between $0.2-0.3\,{\rm
Z_{\odot}}$ and robustly exclude $<0.2\,{\rm Z_{\odot}}$ and solar/super-solar
metallicities at $4\sigma$ level. For the ages, we find
$1.5^{+0.5}_{-0.5}\,{\rm Gyrs}$, ruling out ages $>5\,{\rm Gyrs}$ at $4\sigma$
confidence. The photometry is, however, consistent with older ages up to
$9\,{\rm Gyrs}$ at $5\sigma$ level, mainly due to the relatively flat relation
between color and age at ages $>3\,{\rm Gyrs}$. In addition, we find
indications of variations of age and metallicity in this cluster population
(Figure 7).

Assuming the M/L ratios of the best fit SSP models, we derive stellar masses
for the star clusters of $2.4^{+3.0}_{-1.5}\times 10^{6}\,{\rm M_{\odot}}$
(Figure 4). We note that this M/L ratio is similar to the one of quiescent
galaxies at the same redshift and consistent with models and observed ratios
of local globulars. The stellar masses of our compact star clusters lie at the
high-mass end of average masses of local globulars and there could be overlap
with masses of local dwarf galaxies (Figure 6).

All in all, this suggests that these objects are likely young to middle-aged,
compact star clusters (sizes smaller than $50\,{\rm pc}$) with formation times
at $z=0.5-0.7$. Such a young age and modest metallicity support a scenario
where the star clusters have been formed recently and then were stripped away
several $100\,{\rm kpc}$ (projected) from their host galaxies due to the
interactions in the cluster field. On the other hand, these clusters could
have been formed recently in cold flows onto the cluster core (e.g., Holtzman
et al., 1992). Related to this, the recent work by Lee et al. (2022) studies
the spatial distribution of these star clusters and indicates that they follow
closely the intercluster light and trace well the dark matter structure of the
galaxy cluster. This would be more in support of a scenario in which the star
clusters are stripped from their host galaxies in this highly interactive
environment. A narrower sampling of the $1-5\,{\rm\mu m}$ wavelength with
photometry or spectroscopy could help in determining more robust ages to place
more stringent constraints on the formation scenario.

The star clusters probed here are $1-2$ orders of magnitudes brighter than the
turnover of the globular cluster luminosity function measured around BCGs in
local galaxy clusters. The lower end of the luminosity distribution is limited
by JWST’s sensitivity. At these luminosities, the clusters are in the regime
of superluminous globulars as defined in Harris et al. (2014), however, it is
to note that SMACS0723 is relatively massive compared to local galaxy clusters
(although its BCG is at the lower end of the luminosity distribution of local
BCG probed in Harris et al.). Interestingly, the $(B-I)$ color distribution of
compact star clusters in SMACS0723 is similar to the one of globulars in the
$\sim 1.7\times$ less massive Abell 3558 cluster, one of the most massive
clusters studied in that work (Figure 8).

We note that the star cluster here are, at maximal sizes of $50\,{\rm pc}$ and
masses at the high end of local globulars, among the most compact stellar
agglomerations (Figure 6). Compact star clusters or globulars are a likely
explanation of these objects, however, we note that the stripped compact cores
of dwarf galaxies could be an alternative explanation (see for example Ideta &
Makino (2004) for a discussion of the origin of $\omega$ Centauri). For
example, number estimates based on the Illustris simulation (Genel et al.,
2014; Vogelsberger et al., 2014a, b) suggest several hundreds of dwarf
galaxies at masses of $10^{7}\,{\rm M_{\odot}}$ in clusters with $M_{\rm
200}>5\times 10^{13}\,{\rm M_{\odot}}$, including SMACS0723 at a mass of
$8.4\times 10^{14}\,{\rm M_{\odot}}$ (Mistani et al., 2016; Coe et al., 2019).
Simulations suggest that a dwarf galaxy could lose $\sim 90\%$ of its mass
during the first few pericenter passages around its host galaxy (e.g., Ideta &
Makino, 2004), making their masses consistent with the ones measured for the
clusters (Figure 6). If a fraction of the expected number of dwarf galaxies
gets stripped in the cluster environment, compact cores of these dwarfs could
become comparable in number with the compact star clusters seen here.

Acknowledgments: We thank Sergio Fajardo-Acosta, Alastair Edge, and Jessica
Krick for fruitful discussions on the topic of stars and globular clusters. We
also thank the anonymous referee for the helpful input, which significantly
improved the quality of this manuscript. This research is partially funded by
the Joint Survey Processing effort at IPAC/Caltech through NASA grant
NNN12AA01C. This research made use of the NASA/IPAC Extragalactic Database
(NED), which is operated by the Jet Propulsion Laboratory, California
Institute of Technology, under contract with the National Aeronautics and
Space Administration. The Cosmic Dawn Center (DAWN) is funded by the Danish
National Research Foundation under grant No. 140. This work has been based on
observations made with the NASA/ESA/CSA James Webb Space Telescope. 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. These observations are associated with JWST programs 2736. The
authors acknowledge the ERO teams led by Klaus M. Pontoppidan for developing
their observing programs with a zero-exclusive-access period.  Table 1:
Coordinates, NIRCam fluxes, and stellar masses for all extracted compact star
clusters. All fluxes are corrected for Galactic extinction. The errors in
masses are derived from the photometry only and do not include uncertainties
in the M/L ratio. ID R.A. Decl. F090W F150W F200W F277W F356W F444W log(M/M⊙)
(J2000) (J2000) (nJy) (nJy) (nJy) (nJy) (nJy) (nJy) SC_000 110.83478 -73.45518
$9.4\pm 1.2$ $22.7\pm 0.3$ $20.3\pm 0.3$ $21.6\pm 1.2$ $12.0\pm 1.1$ $11.2\pm
1.5$ $6.73\pm 0.05$ SC_001 110.83487 -73.45463 $20.5\pm 1.2$ $29.2\pm 0.5$
$33.8\pm 0.7$ $30.7\pm 0.6$ $15.4\pm 1.1$ $13.4\pm 1.5$ $7.02\pm 0.02$ SC_002
110.83238 -73.45431 $34.9\pm 1.2$ $57.5\pm 0.8$ $70.3\pm 0.7$ $67.7\pm 0.5$
$39.6\pm 0.5$ $33.7\pm 0.5$ $7.25\pm 0.02$ SC_003 110.83262 -73.45475 $29.8\pm
1.2$ $29.8\pm 0.7$ $33.3\pm 0.7$ $31.5\pm 1.1$ $17.3\pm 0.7$ $12.8\pm 1.5$
$6.52\pm 0.02$ SC_004 110.83263 -73.45367 $12.8\pm 1.2$ $20.8\pm 0.7$ $14.7\pm
0.5$ $10.6\pm 1.2$ $11.1\pm 0.7$ $4.5\pm 1.5$ $6.68\pm 0.04$ SC_005 110.82962
-73.45353 $16.4\pm 1.2$ $16.7\pm 0.5$ $19.2\pm 0.5$ $12.2\pm 0.8$ $9.4\pm 0.6$
$7.6\pm 1.5$ $6.59\pm 0.03$ SC_006 110.83044 -73.45322 $15.5\pm 1.2$ $20.0\pm
0.5$ $22.5\pm 0.7$ $16.3\pm 1.2$ $11.1\pm 0.7$ $6.4\pm 1.5$ $6.94\pm 0.04$
SC_007 110.82800 -73.45331 $3.2\pm 1.2$ $12.2\pm 0.7$ $14.0\pm 0.7$ $18.9\pm
0.5$ $16.6\pm 1.1$ $15.7\pm 1.5$ $5.75\pm 0.14$ SC_008 110.82647 -73.45389
$23.8\pm 1.2$ $20.6\pm 0.5$ $19.7\pm 0.6$ $25.2\pm 0.8$ $9.5\pm 1.1$ $8.6\pm
1.5$ $6.27\pm 0.02$ SC_009 110.82579 -73.45360 $21.7\pm 1.2$ $26.3\pm 0.5$
$27.0\pm 0.4$ $24.6\pm 0.7$ $15.0\pm 1.1$ $11.7\pm 0.7$ $6.42\pm 0.02$ SC_010
110.82474 -73.45357 $5.3\pm 1.2$ $14.9\pm 0.4$ $18.9\pm 0.4$ $13.0\pm 1.2$
$11.4\pm 1.1$ $7.8\pm 1.5$ $6.62\pm 0.09$ SC_011 110.82139 -73.45397 $17.0\pm
1.2$ $18.6\pm 0.6$ $18.0\pm 0.3$ $14.9\pm 0.5$ $9.6\pm 0.7$ $5.9\pm 1.5$
$6.46\pm 0.03$ SC_012 110.82147 -73.45443 $6.3\pm 1.2$ $16.8\pm 0.8$ $14.9\pm
0.7$ $12.8\pm 1.2$ $11.5\pm 1.1$ $1.8\pm 1.5$ $6.65\pm 0.10$ SC_013 110.82276
-73.45429 $7.5\pm 1.2$ $16.6\pm 0.7$ $20.8\pm 0.4$ $15.2\pm 1.2$ $2.0\pm 1.1$
$5.4\pm 1.5$ $6.55\pm 0.07$ SC_014 110.82239 -73.45520 $14.7\pm 1.2$ $17.8\pm
0.8$ $22.2\pm 0.6$ $20.7\pm 1.2$ $12.0\pm 1.1$ $13.3\pm 1.5$ $6.50\pm 0.04$
SC_015 110.82412 -73.45540 $26.1\pm 1.2$ $42.1\pm 0.2$ $42.7\pm 0.3$ $47.2\pm
1.2$ $27.2\pm 1.0$ $21.7\pm 1.5$ $6.36\pm 0.02$ SC_016 110.82460 -73.45579
$15.2\pm 1.2$ $16.6\pm 0.5$ $18.5\pm 0.5$ $19.5\pm 1.1$ $7.3\pm 1.1$ $7.4\pm
1.1$ $6.13\pm 0.03$ SC_017 110.82441 -73.45585 $8.1\pm 1.2$ $14.6\pm 0.6$
$13.0\pm 0.5$ $16.9\pm 0.5$ $15.3\pm 0.9$ $13.5\pm 1.5$ $5.92\pm 0.06$ SC_018
110.82575 -73.45549 $20.8\pm 1.2$ $28.0\pm 0.6$ $21.5\pm 0.5$ $21.9\pm 1.2$
$16.8\pm 1.1$ $16.7\pm 1.5$ $6.16\pm 0.02$ SC_019 110.82953 -73.45540 $18.3\pm
1.2$ $21.3\pm 0.8$ $28.3\pm 0.2$ $33.8\pm 1.2$ $20.3\pm 1.1$ $24.1\pm 1.5$
$6.52\pm 0.02$ SC_020 110.83033 -73.45513 $26.0\pm 1.2$ $34.4\pm 0.4$ $38.6\pm
0.4$ $42.2\pm 1.2$ $26.4\pm 1.1$ $13.8\pm 1.5$ $6.43\pm 0.02$ SC_021 110.83040
-73.45523 $12.0\pm 1.2$ $21.5\pm 0.7$ $27.5\pm 0.6$ $39.3\pm 1.2$ $29.3\pm
1.1$ $30.0\pm 1.5$ $6.34\pm 0.04$ SC_022 110.83355 -73.45528 $11.5\pm 1.2$
$12.9\pm 0.5$ $13.0\pm 0.6$ $12.9\pm 1.0$ $5.3\pm 1.1$ $6.3\pm 1.5$ $5.95\pm
0.05$ SC_023 110.83300 -73.45532 $6.8\pm 1.2$ $15.5\pm 0.5$ $14.4\pm 0.5$
$13.7\pm 1.0$ $7.1\pm 0.7$ $6.2\pm 1.5$ $6.63\pm 0.08$ SC_024 110.83395
-73.45505 $15.7\pm 0.1$ $15.8\pm 0.6$ $11.1\pm 0.6$ $10.1\pm 1.2$ $3.8\pm 1.1$
$1.2\pm 1.5$ $6.22\pm 0.00$ SC_025 110.83219 -73.45462 $19.3\pm 1.2$ $22.8\pm
0.6$ $24.3\pm 0.7$ $20.5\pm 0.5$ $17.1\pm 1.0$ $12.7\pm 1.5$ $6.37\pm 0.03$
SC_026 110.83015 -73.45389 $19.9\pm 0.0$ $30.4\pm 0.8$ $34.9\pm 0.5$ $36.0\pm
0.9$ $18.9\pm 0.7$ $18.3\pm 1.5$ $6.18\pm 0.00$ SC_027 110.82938 -73.45402
$12.7\pm 1.2$ $17.0\pm 0.8$ $21.8\pm 0.5$ $17.4\pm 1.2$ $12.8\pm 1.1$ $9.3\pm
1.5$ $6.49\pm 0.04$ SC_028 110.83031 -73.45406 $18.4\pm 1.2$ $14.4\pm 0.7$
$14.7\pm 0.6$ $19.7\pm 1.2$ $9.2\pm 1.1$ $10.7\pm 1.5$ $6.11\pm 0.03$ SC_029
110.83097 -73.45398 $4.4\pm 1.2$ $13.7\pm 0.8$ $12.0\pm 0.5$ $9.8\pm 0.4$
$2.3\pm 1.1$ $2.5\pm 1.5$ $6.17\pm 0.12$ SC_030 110.83071 -73.45574 $46.2\pm
1.2$ $55.4\pm 0.4$ $59.1\pm 0.7$ $52.6\pm 1.2$ $29.8\pm 0.5$ $20.5\pm 1.5$
$7.08\pm 0.01$ SC_031 110.83011 -73.45603 $10.3\pm 1.2$ $21.3\pm 0.8$ $18.8\pm
0.6$ $15.2\pm 0.3$ $9.5\pm 1.1$ $4.6\pm 1.5$ $6.76\pm 0.04$ SC_032 110.83222
-73.45585 $10.8\pm 1.2$ $13.2\pm 0.4$ $14.6\pm 0.5$ $13.4\pm 1.2$ $7.1\pm 0.1$
$2.9\pm 1.5$ $6.76\pm 0.04$ SC_033 110.82036 -73.45593 $5.2\pm 1.2$ $12.7\pm
0.8$ $13.1\pm 0.5$ $15.8\pm 0.6$ $7.3\pm 1.0$ $6.0\pm 1.5$ $6.53\pm 0.09$
SC_034 110.82258 -73.45596 $10.0\pm 1.2$ $12.7\pm 0.3$ $12.6\pm 0.4$ $8.3\pm
1.2$ $3.7\pm 1.1$ $3.3\pm 1.5$ $6.68\pm 0.05$ SC_035 110.80869 -73.45551
$15.6\pm 1.2$ $18.8\pm 0.5$ $20.8\pm 0.5$ $19.6\pm 0.6$ $10.4\pm 1.1$ $6.6\pm
1.5$ $6.37\pm 0.04$ SC_036 110.81668 -73.45396 $15.0\pm 1.2$ $10.1\pm 0.6$
$13.3\pm 0.5$ $16.7\pm 1.2$ $7.7\pm 1.1$ $8.0\pm 1.5$ $6.12\pm 0.04$ SC_037
110.81672 -73.45406 $3.9\pm 1.2$ $21.2\pm 0.8$ $19.9\pm 0.4$ $16.8\pm 0.9$
$7.1\pm 0.6$ $3.5\pm 1.5$ $6.45\pm 0.14$ SC_038 110.81860 -73.45359 $6.8\pm
1.2$ $20.8\pm 0.7$ $23.1\pm 0.6$ $24.1\pm 1.2$ $14.1\pm 1.1$ $7.6\pm 1.5$
$6.89\pm 0.07$ SC_039 110.82047 -73.45328 $31.2\pm 1.2$ $32.3\pm 0.4$ $32.5\pm
0.4$ $31.2\pm 0.5$ $20.6\pm 0.5$ $8.4\pm 1.5$ $6.38\pm 0.01$ SC_040 110.82181
-73.45330 $12.8\pm 1.2$ $19.8\pm 0.1$ $15.7\pm 0.2$ $16.9\pm 1.2$ $15.1\pm
1.1$ $15.6\pm 1.5$ $6.12\pm 0.04$ SC_041 110.82086 -73.45378 $2.8\pm 1.2$
$11.5\pm 0.7$ $11.6\pm 0.4$ $8.6\pm 1.2$ $7.5\pm 0.7$ $2.9\pm 1.5$ $6.32\pm
0.18$ SC_042 110.82852 -73.45620 $12.0\pm 0.1$ $17.6\pm 0.4$ $17.1\pm 0.6$
$16.0\pm 0.4$ $8.8\pm 1.1$ $5.9\pm 1.5$ $6.37\pm 0.00$ SC_043 110.82804
-73.45646 $17.9\pm 1.2$ $20.7\pm 0.8$ $15.5\pm 0.3$ $15.2\pm 1.2$ $8.4\pm 1.1$
$6.9\pm 1.5$ $6.26\pm 0.03$ SC_044 110.82936 -73.45614 $18.6\pm 1.2$ $17.1\pm
0.5$ $18.0\pm 0.5$ $20.0\pm 1.2$ $16.6\pm 1.1$ $21.3\pm 1.5$ $6.28\pm 0.03$
SC_045 110.82436 -73.45603 $8.0\pm 1.2$ $14.9\pm 0.7$ $16.0\pm 0.6$ $13.3\pm
0.8$ $6.9\pm 1.1$ $1.9\pm 1.5$ $6.39\pm 0.06$ SC_046 110.82245 -73.45393
$11.0\pm 1.2$ $13.9\pm 0.3$ $11.9\pm 0.5$ $11.0\pm 0.3$ $4.6\pm 0.7$ $4.4\pm
1.5$ $6.59\pm 0.04$ SC_047 110.82245 -73.45386 $9.5\pm 1.2$ $14.6\pm 0.7$
$14.3\pm 0.6$ $14.5\pm 0.6$ $18.8\pm 0.4$ $10.9\pm 1.5$ $5.99\pm 0.06$ SC_048
110.82226 -73.45405 $6.0\pm 1.2$ $7.1\pm 0.6$ $8.2\pm 0.5$ $7.4\pm 1.2$
$8.3\pm 1.1$ $1.9\pm 1.5$ $5.95\pm 0.09$ SC_049 110.81272 -73.45459 $19.8\pm
1.2$ $25.4\pm 0.8$ $25.6\pm 0.6$ $21.9\pm 1.2$ $12.9\pm 1.1$ $9.5\pm 1.5$
$7.05\pm 0.02$ SC_050 110.82056 -73.45527 $10.7\pm 1.2$ $20.9\pm 0.8$ $20.4\pm
0.6$ $24.2\pm 1.2$ $10.7\pm 0.7$ $12.8\pm 1.5$ $6.74\pm 0.04$ SC_051 110.83121
-73.45448 $10.5\pm 1.2$ $18.1\pm 0.8$ $18.0\pm 0.6$ $17.6\pm 1.2$ $10.5\pm
1.1$ $9.6\pm 1.5$ $6.80\pm 0.05$ SC_052 110.83858 -73.45495 $12.0\pm 1.2$
$19.7\pm 0.8$ $18.9\pm 0.4$ $17.0\pm 1.2$ $10.8\pm 1.1$ $6.6\pm 1.5$ $6.36\pm
0.05$ SC_053 110.83849 -73.45514 $19.3\pm 1.2$ $24.8\pm 0.6$ $22.9\pm 0.5$
$22.8\pm 0.7$ $13.3\pm 0.7$ $7.7\pm 1.5$ $6.17\pm 0.02$ SC_054 110.83820
-73.45532 $9.5\pm 1.2$ $8.4\pm 0.6$ $10.7\pm 0.7$ $11.2\pm 1.2$ $5.0\pm 1.1$
$4.8\pm 1.5$ $5.93\pm 0.06$ SC_055 110.83400 -73.45490 $6.1\pm 1.2$ $9.3\pm
0.8$ $15.3\pm 0.6$ $15.0\pm 1.1$ $6.4\pm 1.1$ $7.5\pm 1.5$ $6.75\pm 0.10$
SC_056 110.83486 -73.45413 $7.2\pm 1.2$ $11.4\pm 0.6$ $12.0\pm 0.3$ $9.5\pm
1.2$ $7.8\pm 1.1$ $8.4\pm 1.5$ $6.63\pm 0.07$ SC_057 110.82368 -73.45312
$7.7\pm 1.2$ $11.5\pm 0.5$ $16.3\pm 0.2$ $13.4\pm 0.6$ $8.0\pm 1.1$ $2.2\pm
1.5$ $6.78\pm 0.07$ SC_058 110.82875 -73.45347 $5.8\pm 1.2$ $8.2\pm 0.6$
$10.7\pm 0.5$ $8.6\pm 1.2$ $5.3\pm 1.1$ $4.1\pm 1.5$ $6.20\pm 0.07$ SC_059
110.84541 -73.45423 $9.5\pm 1.2$ $17.9\pm 0.5$ $15.5\pm 0.7$ $11.1\pm 1.2$
$5.6\pm 1.1$ $7.5\pm 0.3$ $6.72\pm 0.06$ SC_060 110.84582 -73.45393 $6.3\pm
1.2$ $12.8\pm 0.6$ $11.3\pm 0.7$ $10.0\pm 1.2$ $7.9\pm 1.0$ $6.0\pm 0.5$
$6.58\pm 0.08$ SC_061 110.84403 -73.45389 $3.9\pm 1.1$ $10.4\pm 0.8$ $11.2\pm
0.2$ $11.9\pm 1.2$ $6.3\pm 1.1$ $4.7\pm 1.5$ $6.68\pm 0.14$ SC_062 110.84351
-73.45305 $9.3\pm 1.2$ $14.2\pm 0.8$ $12.2\pm 0.7$ $11.7\pm 1.2$ $6.9\pm 1.1$
$3.0\pm 1.5$ $6.72\pm 0.06$ SC_063 110.84426 -73.45268 $7.1\pm 0.1$ $19.4\pm
0.5$ $19.6\pm 0.5$ $19.7\pm 1.2$ $9.7\pm 0.8$ $6.6\pm 1.5$ $6.56\pm 0.01$
SC_064 110.84474 -73.45277 $10.8\pm 1.2$ $18.6\pm 0.8$ $19.3\pm 0.6$ $21.3\pm
1.2$ $12.0\pm 1.1$ $8.3\pm 1.5$ $6.83\pm 0.05$ SC_065 110.84351 -73.45347
$2.0\pm 1.2$ $13.4\pm 0.7$ $14.9\pm 0.7$ $11.8\pm 1.2$ $6.6\pm 0.0$ $3.1\pm
1.5$ $5.23\pm 0.22$ SC_066 110.83753 -73.45430 $10.7\pm 1.2$ $16.5\pm 0.5$
$12.7\pm 0.7$ $18.2\pm 1.2$ $12.1\pm 0.5$ $7.0\pm 1.5$ $6.04\pm 0.05$ SC_067
110.82613 -73.45409 $4.1\pm 1.2$ $24.4\pm 0.7$ $21.5\pm 0.6$ $28.9\pm 1.2$
$17.8\pm 1.1$ $28.6\pm 1.5$ $6.69\pm 0.13$ SC_068 110.83132 -73.45512 $4.6\pm
1.2$ $6.0\pm 0.8$ $10.7\pm 0.6$ $5.3\pm 1.1$ $1.9\pm 1.1$ $0.8\pm 1.5$
$6.06\pm 0.11$ SC_069 110.82314 -73.45583 $42.1\pm 1.2$ $53.0\pm 0.0$ $37.3\pm
0.1$ $32.8\pm 1.1$ $35.2\pm 1.1$ $29.7\pm 1.5$ $6.50\pm 0.02$ SC_070 110.82385
-73.45596 $17.6\pm 1.2$ $26.8\pm 0.8$ $29.5\pm 0.7$ $28.9\pm 1.2$ $18.3\pm
1.0$ $13.9\pm 1.5$ $6.57\pm 0.03$ SC_071 110.83472 -73.45482 $6.5\pm 1.2$
$12.4\pm 0.7$ $11.3\pm 0.4$ $9.5\pm 1.2$ $5.9\pm 1.1$ $8.6\pm 1.5$ $6.57\pm
0.08$ SC_072 110.84418 -73.45358 $7.7\pm 1.2$ $7.2\pm 0.2$ $5.2\pm 0.7$
$7.2\pm 1.2$ $4.4\pm 1.1$ $5.7\pm 1.5$ $5.74\pm 0.05$ SC_073 110.84534
-73.45344 $8.4\pm 1.2$ $13.2\pm 0.7$ $15.0\pm 0.7$ $13.5\pm 1.0$ $6.5\pm 1.1$
$5.3\pm 1.5$ $6.59\pm 0.06$ SC_074 110.80991 -73.45428 $7.1\pm 1.2$ $5.8\pm
0.8$ $7.3\pm 0.6$ $6.1\pm 1.2$ $5.8\pm 1.1$ $-0.1\pm 1.5$ $6.47\pm 0.07$
SC_075 110.81175 -73.45398 $4.1\pm 1.2$ $11.9\pm 0.4$ $13.9\pm 0.7$ $10.8\pm
1.2$ $7.9\pm 1.0$ $3.8\pm 1.5$ $6.48\pm 0.15$ SC_076 110.81713 -73.45409
$12.9\pm 1.2$ $22.3\pm 0.0$ $17.0\pm 0.6$ $17.3\pm 1.2$ $12.1\pm 0.7$ $6.3\pm
1.5$ $5.99\pm 0.04$ SC_077 110.82002 -73.45379 $20.2\pm 1.2$ $21.5\pm 0.5$
$20.4\pm 0.7$ $-0.7\pm 1.2$ $-1.2\pm 1.1$ $-2.9\pm 1.5$ $6.92\pm 0.03$ SC_078
110.83525 -73.45489 $4.9\pm 1.2$ $8.4\pm 0.6$ $12.0\pm 0.7$ $12.5\pm 1.2$
$6.9\pm 1.1$ $4.3\pm 1.4$ $6.24\pm 0.11$ SC_079 110.83585 -73.45481 $6.6\pm
1.2$ $11.6\pm 0.8$ $11.6\pm 0.7$ $11.3\pm 1.2$ $6.2\pm 0.8$ $1.7\pm 1.5$
$6.30\pm 0.09$ SC_080 110.84533 -73.45445 $7.7\pm 1.2$ $14.5\pm 0.7$ $14.1\pm
0.5$ $14.0\pm 1.1$ $7.5\pm 1.1$ $3.9\pm 1.5$ $6.75\pm 0.06$ SC_081 110.84509
-73.45449 $4.9\pm 1.2$ $10.0\pm 0.7$ $9.8\pm 0.4$ $7.9\pm 1.2$ $4.6\pm 0.6$
$-2.5\pm 1.5$ $6.28\pm 0.11$ SC_082 110.82796 -73.45581 $4.7\pm 1.2$ $8.8\pm
0.8$ $12.6\pm 0.6$ $8.9\pm 1.2$ $8.7\pm 1.1$ $4.8\pm 1.5$ $6.55\pm 0.12$
SC_083 110.82717 -73.45708 $7.1\pm 1.2$ $18.8\pm 0.6$ $20.3\pm 0.5$ $19.4\pm
0.7$ $11.0\pm 1.0$ $8.0\pm 1.5$ $6.63\pm 0.07$ SC_084 110.78770 -73.45499
$6.6\pm 1.2$ $10.7\pm 0.6$ $9.7\pm 0.6$ $10.5\pm 1.2$ $3.8\pm 1.1$ $6.5\pm
0.5$ $6.15\pm 0.07$ SC_085 110.81329 -73.45452 $23.5\pm 1.2$ $13.6\pm 0.8$
$14.3\pm 0.5$ $2.1\pm 1.2$ $1.8\pm 1.1$ $-0.4\pm 1.5$ $6.98\pm 0.02$ SC_086
110.82160 -73.45648 $7.5\pm 1.2$ $8.3\pm 0.8$ $13.7\pm 0.7$ $10.9\pm 0.8$
$5.8\pm 1.0$ $7.8\pm 1.5$ $6.37\pm 0.07$ SC_087 110.81876 -73.45635 $10.8\pm
0.1$ $11.7\pm 0.8$ $15.3\pm 0.7$ $10.6\pm 1.2$ $5.0\pm 1.0$ $5.3\pm 1.5$
$6.75\pm 0.00$ SC_088 110.81799 -73.45675 $2.8\pm 1.2$ $8.5\pm 0.8$ $7.8\pm
0.5$ $9.5\pm 0.4$ $5.3\pm 1.1$ $2.3\pm 1.5$ $5.73\pm 0.19$ SC_089 110.81732
-73.45681 $11.4\pm 1.2$ $12.8\pm 0.7$ $13.3\pm 0.4$ $11.0\pm 0.7$ $4.5\pm 1.1$
$4.0\pm 1.5$ $6.45\pm 0.04$ SC_090 110.81038 -73.45548 $14.1\pm 1.2$ $17.6\pm
0.7$ $18.7\pm 0.7$ $21.8\pm 1.2$ $12.9\pm 1.1$ $12.1\pm 1.5$ $6.16\pm 0.04$
SC_091 110.78922 -73.45409 $14.0\pm 0.7$ $8.6\pm 0.6$ $9.6\pm 0.4$ $10.2\pm
0.9$ $4.7\pm 1.1$ $3.1\pm 1.5$ $6.02\pm 0.02$ SC_092 110.78970 -73.45433
$7.7\pm 1.2$ $10.8\pm 0.5$ $11.2\pm 0.4$ $8.8\pm 1.2$ $4.7\pm 0.7$ $5.5\pm
1.5$ $6.64\pm 0.07$ SC_093 110.79125 -73.45385 $9.8\pm 1.2$ $10.2\pm 0.5$
$10.7\pm 0.5$ $9.8\pm 1.2$ $3.5\pm 1.1$ $2.4\pm 1.5$ $6.33\pm 0.05$ SC_094
110.78340 -73.45303 $6.7\pm 0.1$ $8.2\pm 0.5$ $9.5\pm 0.4$ $7.4\pm 1.2$
$2.8\pm 1.1$ $2.2\pm 1.5$ $6.57\pm 0.01$ SC_095 110.78423 -73.45257 $1.9\pm
1.2$ $6.7\pm 0.4$ $7.7\pm 0.4$ $6.8\pm 1.2$ $2.8\pm 1.1$ $1.2\pm 1.5$ $6.41\pm
0.24$ SC_096 110.78713 -73.45280 $22.1\pm 1.2$ $22.9\pm 0.6$ $23.7\pm 0.7$
$21.4\pm 1.2$ $12.1\pm 0.8$ $9.5\pm 1.5$ $6.64\pm 0.03$ SC_097 110.78789
-73.45194 $13.2\pm 1.2$ $17.7\pm 0.4$ $18.5\pm 0.5$ $14.6\pm 1.2$ $9.5\pm 1.1$
$5.8\pm 1.5$ $6.86\pm 0.03$ SC_098 110.78635 -73.45047 $7.2\pm 1.2$ $14.7\pm
0.6$ $14.0\pm 0.4$ $18.4\pm 1.2$ $10.8\pm 0.6$ $9.2\pm 1.5$ $5.88\pm 0.08$
SC_099 110.78172 -73.45070 $10.3\pm 1.2$ $9.8\pm 0.8$ $10.8\pm 0.6$ $9.1\pm
0.6$ $4.5\pm 1.1$ $1.8\pm 1.5$ $6.35\pm 0.04$ SC_100 110.79601 -73.44790
$6.0\pm 1.2$ $16.9\pm 0.7$ $19.2\pm 0.5$ $18.7\pm 1.2$ $9.8\pm 0.6$ $6.0\pm
1.5$ $6.83\pm 0.08$ SC_101 110.79508 -73.44825 $14.7\pm 1.2$ $13.2\pm 0.7$
$14.7\pm 0.7$ $13.0\pm 1.2$ $6.2\pm 0.8$ $10.0\pm 1.5$ $6.30\pm 0.04$ SC_102
110.79584 -73.44829 $9.4\pm 1.2$ $16.7\pm 0.7$ $15.7\pm 0.4$ $14.3\pm 1.2$
$8.9\pm 1.1$ $7.0\pm 1.5$ $6.32\pm 0.06$ SC_103 110.80174 -73.44977 $13.2\pm
1.2$ $17.9\pm 0.6$ $17.8\pm 0.5$ $19.1\pm 0.7$ $9.5\pm 1.1$ $8.6\pm 1.5$
$6.07\pm 0.05$ SC_104 110.80198 -73.44992 $9.3\pm 1.2$ $13.8\pm 0.4$ $16.7\pm
0.1$ $14.3\pm 1.1$ $8.0\pm 1.0$ $5.7\pm 1.5$ $6.75\pm 0.06$ SC_105 110.80116
-73.44958 $9.9\pm 1.2$ $16.3\pm 0.7$ $16.0\pm 0.5$ $18.8\pm 0.6$ $13.8\pm 1.1$
$14.2\pm 1.5$ $6.00\pm 0.04$ SC_106 110.80534 -73.44852 $8.6\pm 1.2$ $11.5\pm
0.7$ $16.0\pm 0.5$ $9.4\pm 0.5$ $8.0\pm 0.5$ $6.0\pm 1.5$ $6.29\pm 0.05$
SC_107 110.80524 -73.44870 $8.0\pm 1.2$ $10.6\pm 0.3$ $8.2\pm 0.7$ $11.9\pm
1.2$ $5.5\pm 0.9$ $2.2\pm 1.5$ $5.75\pm 0.06$ SC_108 110.78716 -73.45552
$8.9\pm 1.2$ $14.5\pm 0.5$ $15.0\pm 0.5$ $15.0\pm 1.2$ $9.2\pm 1.1$ $7.6\pm
1.5$ $6.28\pm 0.06$ SC_109 110.78741 -73.45586 $9.9\pm 1.2$ $11.8\pm 0.7$
$15.5\pm 0.6$ $12.2\pm 1.2$ $6.4\pm 0.5$ $4.2\pm 0.4$ $6.72\pm 0.06$ SC_110
110.78030 -73.45425 $7.6\pm 1.2$ $13.3\pm 0.5$ $14.7\pm 0.6$ $12.7\pm 0.4$
$6.1\pm 0.7$ $3.1\pm 1.5$ $6.55\pm 0.07$ SC_111 110.78126 -73.45340 $5.6\pm
1.2$ $11.9\pm 0.4$ $15.3\pm 0.7$ $15.7\pm 0.4$ $9.0\pm 1.1$ $8.3\pm 1.5$
$6.76\pm 0.08$ SC_112 110.78087 -73.45291 $10.7\pm 1.2$ $17.9\pm 0.5$ $20.0\pm
0.5$ $20.6\pm 1.2$ $13.2\pm 0.9$ $8.3\pm 1.5$ $6.75\pm 0.04$ SC_113 110.79191
-73.45265 $9.3\pm 1.2$ $15.2\pm 0.7$ $14.4\pm 0.4$ $13.2\pm 1.2$ $8.5\pm 0.2$
$4.0\pm 1.5$ $6.27\pm 0.06$ SC_114 110.79176 -73.45274 $11.4\pm 1.2$ $13.2\pm
0.8$ $13.5\pm 0.6$ $10.8\pm 1.2$ $5.9\pm 1.1$ $5.0\pm 1.5$ $6.66\pm 0.04$
SC_115 110.79931 -73.45132 $7.9\pm 1.2$ $15.4\pm 0.7$ $13.7\pm 0.4$ $11.7\pm
0.8$ $6.4\pm 1.1$ $7.9\pm 1.5$ $6.65\pm 0.07$ SC_116 110.79995 -73.45124
$12.0\pm 1.2$ $9.8\pm 0.8$ $11.8\pm 0.6$ $10.0\pm 1.2$ $4.6\pm 0.3$ $6.4\pm
1.5$ $6.09\pm 0.04$ SC_117 110.79854 -73.45139 $4.4\pm 1.2$ $12.8\pm 0.5$
$10.2\pm 0.5$ $10.9\pm 1.2$ $5.4\pm 0.6$ $3.4\pm 1.5$ $6.41\pm 0.12$ SC_118
110.79830 -73.45146 $7.1\pm 1.2$ $8.5\pm 0.6$ $9.3\pm 0.4$ $10.9\pm 0.3$
$5.2\pm 0.6$ $0.2\pm 1.5$ $5.87\pm 0.07$ SC_119 110.79798 -73.45131 $7.7\pm
1.2$ $9.6\pm 0.5$ $11.5\pm 0.5$ $9.5\pm 1.2$ $5.3\pm 1.1$ $3.6\pm 1.5$
$6.25\pm 0.07$ SC_120 110.79658 -73.45191 $13.1\pm 1.2$ $15.0\pm 0.7$ $13.5\pm
0.6$ $11.4\pm 1.2$ $7.4\pm 0.7$ $2.6\pm 1.5$ $6.25\pm 0.04$ SC_121 110.78631
-73.45810 $23.0\pm 1.2$ $25.2\pm 0.8$ $24.1\pm 0.7$ $25.6\pm 1.2$ $19.6\pm
1.1$ $11.2\pm 1.5$ $6.26\pm 0.02$ SC_122 110.78559 -73.45643 $10.1\pm 1.2$
$14.8\pm 0.7$ $14.9\pm 0.3$ $13.9\pm 1.2$ $6.0\pm 1.1$ $5.0\pm 1.5$ $6.75\pm
0.05$ SC_123 110.78135 -73.45553 $8.2\pm 1.2$ $21.7\pm 0.7$ $19.7\pm 0.7$
$22.2\pm 1.2$ $14.3\pm 0.9$ $9.3\pm 1.5$ $6.86\pm 0.07$ SC_124 110.67039
-73.48220 $17.8\pm 1.2$ $14.8\pm 0.7$ $19.1\pm 0.7$ $26.5\pm 1.2$ $17.0\pm
1.1$ $14.8\pm 1.5$ $6.85\pm 0.03$ SC_125 110.68257 -73.47759 $15.3\pm 1.2$
$12.4\pm 0.6$ $16.0\pm 0.6$ $19.9\pm 1.2$ $8.7\pm 1.1$ $8.9\pm 1.5$ $6.79\pm
0.03$ SC_126 110.73865 -73.47510 $5.6\pm 1.2$ $14.7\pm 0.6$ $14.0\pm 0.1$
$14.0\pm 1.2$ $29.0\pm 1.1$ $20.4\pm 1.5$ $6.35\pm 0.09$ SC_127 110.70747
-73.49255 $21.9\pm 1.2$ $32.1\pm 0.8$ $25.4\pm 0.5$ $34.1\pm 1.2$ $32.7\pm
1.1$ $33.2\pm 1.5$ $6.95\pm 0.02$ SC_128 110.68775 -73.48465 $15.1\pm 1.2$
$18.6\pm 0.8$ $13.4\pm 0.7$ $18.7\pm 0.5$ $21.6\pm 0.8$ $19.9\pm 1.5$ $6.79\pm
0.03$ SC_129 110.69481 -73.48426 $9.5\pm 1.2$ $13.6\pm 0.7$ $20.6\pm 0.7$
$37.8\pm 1.2$ $34.1\pm 1.0$ $35.6\pm 1.5$ $6.58\pm 0.06$ SC_130 110.70230
-73.48263 $8.9\pm 1.2$ $12.4\pm 0.8$ $12.8\pm 0.7$ $13.5\pm 0.8$ $14.8\pm 1.1$
$17.8\pm 1.5$ $6.56\pm 0.06$ SC_131 110.69502 -73.48136 $15.5\pm 1.2$ $18.3\pm
0.7$ $19.4\pm 0.7$ $29.6\pm 1.2$ $28.7\pm 1.1$ $24.5\pm 1.5$ $6.80\pm 0.03$
SC_132 110.67261 -73.47396 $15.6\pm 1.2$ $21.2\pm 0.8$ $19.9\pm 0.7$ $29.5\pm
1.2$ $21.2\pm 1.1$ $15.9\pm 1.5$ $6.81\pm 0.03$ SC_133 110.85435 -73.45440
$8.1\pm 1.2$ $10.3\pm 0.6$ $10.5\pm 0.7$ $7.0\pm 1.2$ $5.1\pm 1.1$ $3.9\pm
1.5$ $6.66\pm 0.06$ SC_134 110.85244 -73.45419 $3.8\pm 1.2$ $13.3\pm 0.6$
$13.6\pm 0.7$ $13.0\pm 1.2$ $8.3\pm 0.6$ $3.6\pm 1.5$ $6.61\pm 0.15$ SC_135
110.85889 -73.45459 $4.2\pm 1.2$ $12.8\pm 0.8$ $9.7\pm 0.6$ $6.7\pm 1.2$
$3.9\pm 0.8$ $0.6\pm 1.5$ $6.37\pm 0.10$ SC_136 110.85791 -73.45462 $6.6\pm
1.2$ $10.5\pm 0.7$ $10.9\pm 0.6$ $8.3\pm 0.7$ $5.7\pm 1.1$ $-1.6\pm 1.5$
$6.43\pm 0.08$ SC_137 110.85896 -73.45420 $6.3\pm 1.2$ $11.6\pm 0.6$ $12.0\pm
0.6$ $10.6\pm 0.9$ $4.7\pm 1.1$ $5.1\pm 1.5$ $6.46\pm 0.10$ SC_138 110.86045
-73.45428 $10.7\pm 1.2$ $12.3\pm 0.8$ $13.8\pm 0.7$ $12.1\pm 1.2$ $7.3\pm 1.1$
$6.5\pm 1.5$ $6.12\pm 0.06$ SC_139 110.86098 -73.45427 $6.2\pm 1.2$ $5.4\pm
0.6$ $6.0\pm 0.7$ $6.1\pm 1.2$ $4.0\pm 1.1$ $-0.0\pm 1.5$ $6.43\pm 0.07$
SC_140 110.85891 -73.45394 $10.7\pm 1.2$ $9.3\pm 0.7$ $10.6\pm 0.6$ $7.4\pm
0.6$ $4.3\pm 1.1$ $1.0\pm 1.5$ $6.15\pm 0.05$ SC_141 110.82008 -73.46628
$21.7\pm 1.2$ $27.3\pm 0.3$ $18.4\pm 0.7$ $15.3\pm 0.3$ $9.1\pm 0.8$ $5.6\pm
1.5$ $6.17\pm 0.03$ SC_142 110.82292 -73.46619 $0.9\pm 1.2$ $8.3\pm 0.8$
$9.5\pm 0.7$ $6.9\pm 1.2$ $5.4\pm 1.1$ $0.4\pm 1.5$ $6.29\pm 0.35$ SC_143
110.79685 -73.45404 $2.9\pm 1.2$ $7.2\pm 0.7$ $8.4\pm 0.4$ $7.2\pm 1.2$
$3.7\pm 0.3$ $3.5\pm 1.5$ $6.08\pm 0.22$ SC_144 110.66959 -73.47230 $4.1\pm
1.2$ $15.2\pm 0.5$ $14.1\pm 0.5$ $20.5\pm 0.5$ $61.5\pm 1.0$ $76.3\pm 1.5$
$6.21\pm 0.13$ SC_145 110.81957 -73.45875 $11.0\pm 1.2$ $13.2\pm 0.8$ $13.6\pm
0.4$ $9.7\pm 1.2$ $6.1\pm 0.6$ $5.3\pm 1.5$ $6.64\pm 0.05$ SC_146 110.82110
-73.45871 $5.1\pm 1.2$ $12.6\pm 0.5$ $12.4\pm 0.6$ $9.3\pm 1.2$ $4.7\pm 1.1$
$4.1\pm 1.5$ $6.37\pm 0.10$ SC_147 110.82095 -73.45843 $3.9\pm 1.2$ $8.1\pm
0.7$ $7.4\pm 0.7$ $6.5\pm 1.2$ $3.2\pm 1.1$ $2.5\pm 1.5$ $6.33\pm 0.14$ SC_148
110.81494 -73.45791 $9.8\pm 1.2$ $6.5\pm 0.7$ $8.5\pm 0.5$ $8.7\pm 0.5$
$6.0\pm 1.1$ $4.2\pm 1.5$ $5.93\pm 0.05$ SC_149 110.81525 -73.45789 $4.7\pm
1.2$ $9.2\pm 0.3$ $11.1\pm 0.5$ $11.4\pm 0.7$ $6.3\pm 1.1$ $5.7\pm 1.5$
$6.22\pm 0.09$ SC_150 110.81370 -73.45776 $10.4\pm 1.2$ $11.2\pm 0.6$ $11.8\pm
0.5$ $11.3\pm 0.7$ $6.9\pm 1.0$ $8.0\pm 1.5$ $5.96\pm 0.06$ SC_151 110.81586
-73.45765 $15.9\pm 1.2$ $25.2\pm 0.6$ $24.4\pm 0.6$ $22.4\pm 1.2$ $12.1\pm
0.6$ $9.4\pm 0.3$ $6.95\pm 0.03$ SC_152 110.81782 -73.45708 $21.2\pm 1.2$
$19.1\pm 0.7$ $20.1\pm 0.6$ $16.1\pm 1.2$ $9.0\pm 1.1$ $5.7\pm 1.5$ $6.46\pm
0.02$ SC_153 110.82499 -73.45730 $9.6\pm 1.2$ $27.0\pm 0.7$ $31.1\pm 0.5$
$26.5\pm 0.6$ $14.6\pm 1.1$ $10.0\pm 0.5$ $6.85\pm 0.05$ SC_154 110.82503
-73.45740 $6.7\pm 1.2$ $17.6\pm 0.3$ $16.3\pm 0.5$ $16.4\pm 1.2$ $15.2\pm 1.1$
$13.1\pm 1.5$ $6.78\pm 0.07$ SC_155 110.82519 -73.45764 $4.6\pm 1.2$ $9.7\pm
0.7$ $10.7\pm 0.7$ $8.3\pm 1.2$ $5.0\pm 0.7$ $5.9\pm 1.5$ $6.50\pm 0.12$
SC_156 110.82888 -73.45774 $10.3\pm 1.2$ $16.0\pm 0.7$ $17.5\pm 0.7$ $13.6\pm
1.2$ $8.8\pm 1.1$ $3.5\pm 1.5$ $6.36\pm 0.04$ SC_157 110.88178 -73.45305
$5.6\pm 1.2$ $13.1\pm 0.8$ $16.2\pm 0.5$ $12.4\pm 1.2$ $8.2\pm 1.1$ $4.5\pm
1.5$ $6.63\pm 0.09$ SC_158 110.87357 -73.45284 $9.0\pm 1.2$ $12.3\pm 0.8$
$10.6\pm 0.7$ $10.0\pm 1.2$ $4.2\pm 1.1$ $4.9\pm 1.5$ $6.52\pm 0.05$ SC_159
110.87397 -73.45293 $7.5\pm 0.1$ $7.0\pm 0.5$ $7.6\pm 0.7$ $9.3\pm 1.2$
$5.0\pm 1.0$ $1.6\pm 1.5$ $5.72\pm 0.01$ SC_160 110.87266 -73.45103 $9.4\pm
1.2$ $7.5\pm 0.6$ $7.1\pm 0.3$ $11.3\pm 1.2$ $5.6\pm 1.1$ $2.6\pm 1.5$
$5.82\pm 0.06$ SC_161 110.87221 -73.45115 $5.2\pm 1.2$ $5.5\pm 0.4$ $10.9\pm
0.5$ $9.1\pm 1.2$ $9.1\pm 1.1$ $8.8\pm 0.3$ $5.97\pm 0.09$ SC_162 110.75752
-73.45268 $7.9\pm 1.2$ $11.5\pm 0.8$ $12.1\pm 0.4$ $10.6\pm 1.2$ $5.3\pm 1.1$
$6.3\pm 1.5$ $6.26\pm 0.06$ SC_163 110.75739 -73.45370 $8.8\pm 1.2$ $14.7\pm
0.8$ $11.3\pm 0.5$ $6.9\pm 1.2$ $6.8\pm 1.1$ $5.5\pm 1.5$ $6.52\pm 0.05$
SC_164 110.74766 -73.45285 $18.4\pm 1.2$ $22.9\pm 0.2$ $20.9\pm 0.5$ $20.5\pm
1.2$ $10.0\pm 1.1$ $8.1\pm 1.5$ $6.83\pm 0.03$ SC_165 110.74990 -73.44874
$21.2\pm 1.2$ $29.8\pm 0.4$ $32.3\pm 0.5$ $27.7\pm 0.5$ $17.5\pm 0.6$ $14.4\pm
1.5$ $6.68\pm 0.02$ SC_166 110.77654 -73.44677 $13.1\pm 1.2$ $12.5\pm 0.7$
$10.7\pm 0.7$ $8.0\pm 0.5$ $5.9\pm 0.7$ $3.1\pm 1.5$ $6.12\pm 0.03$ SC_167
110.77515 -73.44679 $10.0\pm 1.2$ $10.5\pm 0.3$ $7.4\pm 0.3$ $16.1\pm 1.2$
$13.3\pm 1.1$ $10.1\pm 1.5$ $5.84\pm 0.04$ SC_168 110.78108 -73.44683 $9.3\pm
1.2$ $8.7\pm 0.7$ $10.2\pm 0.3$ $11.1\pm 1.2$ $6.4\pm 1.1$ $7.3\pm 0.4$
$5.98\pm 0.05$ SC_169 110.80459 -73.44832 $10.5\pm 1.2$ $10.6\pm 0.7$ $7.2\pm
0.6$ $6.7\pm 1.2$ $5.2\pm 0.9$ $1.5\pm 1.5$ $5.90\pm 0.05$ SC_170 110.79816
-73.44769 $5.8\pm 1.2$ $11.9\pm 0.5$ $10.0\pm 0.3$ $10.9\pm 1.0$ $7.9\pm 0.1$
$2.7\pm 1.5$ $5.79\pm 0.09$ SC_171 110.79823 -73.44778 $11.9\pm 1.2$ $15.5\pm
0.6$ $12.8\pm 0.4$ $10.3\pm 1.2$ $6.8\pm 1.1$ $5.0\pm 1.5$ $6.21\pm 0.04$
SC_172 110.86482 -73.45783 $3.7\pm 1.2$ $13.8\pm 0.6$ $16.7\pm 0.6$ $13.5\pm
1.2$ $6.4\pm 1.1$ $3.0\pm 1.5$ $6.65\pm 0.14$ SC_173 110.86402 -73.45812
$6.7\pm 1.2$ $10.8\pm 0.7$ $10.2\pm 0.5$ $10.1\pm 1.2$ $6.6\pm 0.6$ $6.9\pm
1.5$ $5.77\pm 0.09$ SC_174 110.90066 -73.45376 $7.9\pm 1.2$ $13.4\pm 0.7$
$12.1\pm 0.6$ $10.2\pm 1.0$ $5.4\pm 1.1$ $3.4\pm 0.4$ $6.62\pm 0.07$ SC_175
110.70823 -73.47715 $32.5\pm 1.2$ $23.8\pm 0.5$ $17.1\pm 0.5$ $19.8\pm 1.2$
$25.9\pm 1.1$ $18.0\pm 1.5$ $7.12\pm 0.01$ SC_176 110.68084 -73.47226 $18.9\pm
1.2$ $24.8\pm 0.6$ $18.8\pm 0.5$ $12.3\pm 0.6$ $10.2\pm 1.1$ $7.9\pm 1.5$
$6.89\pm 0.03$ SC_177 110.64783 -73.47067 $5.3\pm 1.2$ $10.4\pm 0.8$ $10.6\pm
0.6$ $14.5\pm 1.2$ $12.2\pm 1.1$ $8.8\pm 1.5$ $6.33\pm 0.09$

Table 2: Stacked photometry for all of the compact star clusters. All flux densities have been corrected for Galactic extinction. F090W | F150W | F200W | F277W | F356W | F444W
---|---|---|---|---|---
(nJy) | (nJy) | (nJy) | (nJy) | (nJy) | (nJy)
$9.79\pm 0.12$ | $13.11\pm 0.07$ | $13.98\pm 0.06$ | $13.02\pm 0.12$ | $8.16\pm 0.11$ | $6.64\pm 0.15$

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