# JWST NIRCam Photometry: A Study of Globular Clusters Surrounding Bright
Elliptical Galaxy VV 191a at z=0.0513

Jessica M. Berkheimer School of Earth & Space Exploration, Arizona State
University, Tempe, AZ 85287-1404, USA  Timothy Carleton School of Earth &
Space Exploration, Arizona State University, Tempe, AZ 85287-1404, USA  Rogier
A. Windhorst School of Earth & Space Exploration, Arizona State University,
Tempe, AZ 85287-1404, USA  Department of Physics, Arizona State University,
Tempe, AZ 85287-1504, USA  William C. Keel Department of Physics and
Astronomy, University of Alabama, Box 870324, Tuscaloosa, AL 35404, USA  Benne
W. Holwerda Department of Physics and Astronomy, University of Louisville,
Louisville KY 40292, USA  Mario Nonino INAF-Trieste Astronomical Observatory,
Via Bazzoni 2, 34124, Trieste, Italy  Seth H. Cohen School of Earth & Space
Exploration, Arizona State University, Tempe, AZ 85287-1404, USA  Rolf A.
Jansen School of Earth & Space Exploration, Arizona State University, Tempe,
AZ 85287-1404, USA  Dan Coe AURA for the European Space Agency (ESA), Space
Telescope Science Institute, 3700 San Martin Drive, Baltimore,vvv MD 21218,
USA  Christopher J. Conslice Jodrell Bank Centre for Astrophysics, Alan Turing
Building, University of Manchester, Oxford Road, Manchester M13 9PL, UK  Simon
P. Driver International Centre for Radio Astronomy Research (ICRAR) and the
International Space Centre (ISC), The University of Western Australia, M468,
35 Stirling Highway, Crawley, WA 6009, Australia  Brenda L. Frye Department of
Astronomy / Steward Observatory, University of Arizona, 933 N. Cherry Ave.,
Tucson, AZ 85721, USA  Norman A. Grogin Space Telescope Science Institute,
3700 San Martin Drive, Baltimore, MD 21218, USA  Anton M. Koekemoer Space
Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA
Ray Lucas Space Telescope Science Institute, 3700 San Martin Drive, Baltimore,
MD 21218, USA  Madeline A. Marshall National Research Council of Canada,
Herzberg Astronomy & Astrophysics Research Centre, 5071 West Saanich Road,
Victoria, BC V9E 2E7, Canada  Nor Pirzkal Space Telescope Science Institute,
3700 San Martin Drive, Baltimore, MD 21218, USA  Clayton Robertson Department
of Physics and Astronomy, University of Louisville, Louisville KY 40292, USA
Aaron Robotham International Centre for Radio Astronomy Research (ICRAR) and
the International Space Centre (ISC), The University of Western Australia,
M468, 35 Stirling Highway, Crawley, WA 6009, Australia  Russell E. Ryan, Jr.
Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218,
USA  Brent M. Smith School of Earth & Space Exploration, Arizona State
University, Tempe, AZ 85287-1404, USA  Jake Summers School of Earth & Space
Exploration, Arizona State University, Tempe, AZ 85287-1404, USA  Scott
Tompkins School of Earth & Space Exploration, Arizona State University, Tempe,
AZ 85287-1404, USA  Christopher N.A. Willmer Department of Astronomy / Steward
Observatory, University of Arizona, 933 N. Cherry Ave., Tucson, AZ 85721, USA
Haojing Yan Department of Physics and Astronomy, University of Missouri,
Columbia, MO 65211, USA Jessica Berkheimer<EMAIL_ADDRESS>
###### Abstract

James Webb Space Telescope NIRCam images have revealed 443 globular cluster
(GC) candidates around the $z=0.0513$ elliptical galaxy VV 191a. NIRCam
broadband observations are made at 0.9–4.5 $\mu$m using filters F090W, F150W,
F356W, and F444W. Using photometry, the data is analyzed to present color-
magnitude diagrams (CMDs) that suggest a fairly uniform population of GCs.
Color histograms show a unimodal color distribution that is well fit by a
single Gaussian, using color to primarily trace the metallicity. The findings
show the sample’s globular cluster luminosity function (GCLF) does not reach
the turnover value and is, therefore, more luminous than what is typically
expected, with an absolute AB magnitude, $M_{F090W}=-8.70$ mag, reaching
within nearly one magnitude of the classical turnover value. We attribute this
to the completeness in the sample. Models show that the mass estimate of the
GCs detected tends to be more massive, reaching upward of $\simeq
10^{7}M_{\odot}$. However, the results show that current GC models do not
quite align with the data. We find that the models appear to be bluer than the
JWST data in the reddest (F356W–F444W) filters and redder than the data in the
bluest (F090W–F150W) filters and may need to be revised to improve the
modeling of near-IR colors of old, metal-poor stellar populations.

Instruments: James Webb Space Telescope–Techniques: photometry–Galaxies:
globular clusters

##  1 Introduction

Figure 1: Image of galaxy pair VV 191a (elliptical galaxy on the bottom) and
VV 191b (spiral galaxy on the top). The image includes near-infrared light
from Webb and ultraviolet and visible light from Hubble. In this image, green,
yellow, and red were assigned to Webb’s near-infrared data taken in 0.9, 1.5,
and 3.56 $\mu$m (F090W, F150W, and F356W, respectively). Blue was assigned to
two Hubble filters, ultraviolet data taken in 0.34 $\mu$m (F336W), and visible
light in 0.61 microns (F606W). Observations show an apparent population of GCs
surrounding the elliptical. [_Image credit: NASA, ESA, CSA, Rogier Windhorst
(ASU), William Keel (University of Alabama), Stuart Wyithe (University of
Melbourne), JWST PEARLS Team_]. We added the white polygon to their image to
outline the region useable for globular cluster searches in VV 191a, as
determined in Fig. 2.

Globular clusters (GCs) are among a galaxy’s earliest and most pristine
objects. They are stable, tightly bound collections typically ranging from
$10^{4}$ to $10^{6}$ stars (e.g., Gratton et al., 2004) and are intrinsically
bright objects that can be observed at large distances. When considered as a
system, they are excellent fossil records of the evolution and star-forming
stages of the galaxy they surround (e.g., Ashman & Zepf, 2008). This view has
been confirmed by direct measurements of their ages (e.g., VandenBerg et al.,
2013). Nearly all galaxies contain GCs, excluding dwarf galaxies down to
$10^{7}M_{\odot}$ (e.g., Harris, 1991).

The number of GCs associated with a galaxy is observed to correlate with the
galaxy’s stellar mass, which itself correlates with dark matter halo total
mass (e.g., Harris et al., 2017; Spitler & Forbes, 2009; Georgiev et al.,
2010; Hudson et al., 2014). As ellipticals dominate mass function, GCs are
particularly abundant in these galaxies — 1000s per galaxy in massive
ellipticals (Harris, 1991). Because elliptical galaxies have a much larger
cluster density than spiral galaxies, they yield much better statistics (e.g.,
Kundu & Whitmore, 2001). Elliptical galaxies are ideal candidates for GC
studies, and in these large galaxies, GCs may number in the thousands (Harris,
1991). With very little gas and dust obscuration and no star formation (SF)
activity (e.g., De Lucia et al., 2006), it is relatively straightforward to
distinguish GCs against the background of the elliptical host (Kundu &
Whitmore, 2001).

Broadly speaking, the current literature contains two categories of models for
forming and evolving GC systems in the context of galaxy formation. The first
category of models associates GC formation with special conditions in low-mass
dark matter halos, during or before reionization (e.g., Peebles & Dicke, 1968;
Katz & Ricotti, 2014). The formation times for many GCs is thought to occur in
the redshift range of $z\simeq 2$–8, and thus precede the bulk of SF in the
universe (e.g., Hudson et al., 2014). An early study by Peebles & Dicke (1968)
found that the Jeans mass at high redshift ($\sim 10^{6}M_{\odot}$) is
comparable to the GC stellar mass. More recent studies of GC formation at high
redshift have proposed cluster formation within dark-matter halos of mass
${M}_{{{h}}}\mbox{\hbox to0.0pt{\hbox{\lower 2.0pt\hbox{$\sim$}}\hss}\raise
2.0pt\hbox{$<$}}{10}^{8}\;{M}_{\odot}$ with cooling driven by H2 (e.g., Padoan
et al., 1997). Because many GCs started forming before most stars in the
universe, their formation may correlate more straightforwardly to the dark
matter distribution than the bulk of the stellar mass in galaxies (Hudson et
al., 2014). Blakeslee et al. (1997) suggested that the total numbers of GCs in
bright cluster galaxies were directly proportional to the total dark-matter-
dominated mass of the galaxy cluster.

The second category of models considers GC formation a natural byproduct of
the active SF process and places high importance on galaxy mergers in
producing GCs (e.g., Ashman & Zepf, 1992; Zepf & Ashman, 1993). This scenario
focuses on somewhat lower redshifts. Present observations suggest that many
clusters are formed during episodes of SF associated with a significant event
during the formation process of the galaxy (Zepf & Ashman, 1999; Kundu &
Whitmore, 2001; Linden et al., 2022). This hypothesis can explain the increase
in globular clusters around ellipticals (Ashman & Zepf, 1992). If elliptical
galaxies are the aftermath of spiral galaxy mergers, GCs must form in such
mergers (Schweizer, 1987; Ashman & Zepf, 1992; Whitmore et al., 1993; Zepf &
Ashman, 1999). Theoretically, massive clusters form in merger events because
of shocks and high turbulent pressure within interacting galaxies, which
supports the formation of tightly bound clusters (e.g., Elmegreen & Efremov,
1997), and allows the formation of very massive gas clouds that are necessary
to form GCs (Ashman & Zepf, 1992).

One of the most interesting discoveries from observations of elliptical
galaxies is the discovery of bimodal color distribution in many GCs (Zepf &
Ashman, 1993; Forbes et al., 1996; Kundu & Whitmore, 2001). Bimodal color and
metallicity distributions are frequently interpreted as indicating two
distinct modes of cluster formation. GCs found in the halo of progenitor
spirals, like those observed in the Milky Way and M31, are expected to have a
population of predominantly metal-poor clusters (Zepf & Ashman, 1999). The
model predicted that the GC systems of elliptical galaxies would be composed
of metal-poor populations from the progenitor spirals and metal-rich
populations formed during the merger(s) that created the elliptical (Ashman &
Zepf, 1992; Côté et al., 1998). The metal-rich population will typically be
significantly redder than the metal-poor population because most mergers occur
at moderate or high redshift. Therefore, metallicity differences dominate the
broad-band colors (Zepf & Ashman, 1993; Ashman & Zepf, 1998).

Visual inspection of the data presented first in Keel et al. (2023) reveals
dozens of point-source GC candidates in the VV 191 system not before seen with
deep HST data. This paper analyzes the globular cluster population in the
nearby elliptical VV 191a. We use AB magnitudes (Oke & Gunn, 1983) and the
Planck flat $\Lambda$CDM cosmology with $H_{0}=67.4\pm 0.5$
$kms^{-1}Mpc^{-1}$, $\Omega_{\Lambda}$=0.685, and $\Omega_{m}$=0.315 $\pm$
0.007 (Plank Collaboration et al., 2020). Section 2 describes the observations
and data reduction; Section 3 gives the color–magnitude data which shows a
fairly uniform population of GCs; Section 4 discusses the results of the GC
luminosity function; Section 5 discusses the unimodality of the GC population,
followed by modeling the data in Section 6, ending with our conclusions in
Section 7.

##  2 Observations and Data Reduction

The following section discusses the data, point spread function (PSF)
matching, and photometry.

###  2.1 Data

The JWST ”Prime Extragalactic Areas for Reionization and Lensing Science”
(PEARLS) project has started to unveil the astonishing capabilities of the
James Webb Space Telescope (JWST). PEARLS is a GTO program (PID 1176; PI: R.
Windhorst) designed to provide the community with medium-deep imaging in up to
eight near-infrared filters. PEARLS’ main focus addresses two themes: First
Light and Reionization, and the Assembly of Galaxies (Windhorst et al., 2023).
PEARLS has also observed VV 191, an overlapping galaxy pair selected initially
to provide a benchmark dust-attenuation profile for studying higher redshift,
dusty environments. The galaxy pair consists of VV 191b - a spiral galaxy in
the foreground, and VV 191a - an elliptical galaxy in the background situated
at $z=0.0513$ (Keel et al., 2023).

Previous imaging of VV 191 taken by the Hubble Space Telescope (HST) is too
shallow to detect GCs. The JWST NIRCam data goes much deeper and enables the
detection of the older population of stars in the near-IR that make up many of
these GCs. JWST imaging of VV 191 was obtained on 2 July 2022 as part of the
PEARLS GTO program. The total exposures were 901 seconds in each F090W/F356W
and F150W/F444W filter pair, all using MEDIUM8 readouts with three groups and
three dithers, respectively, as detailed by (Keel et al., 2023).

All detectors at each wavelength were drizzle-combined into single mosaic
images. However, the analysis of VV 191 only uses the single short-wavelength
(SW) detector encompassing the galaxies and matching cropped regions on the
long-wavelength detectors. For detailed steps in the data reduction process,
we refer the reader to Keel et al. (2023).

Visually, we observe what appears to be several dozen GCs surrounding the
elliptical. Infrared observations taken by NIRCam provide a means to directly
measure the metallicity of GCs, in particular, the red GCs that are
preferentially located in the high surface brightness inner regions of
ellipticals (Kundu & Zepf, 2007). We will quantify these observations in the
following sections.

###  2.2 Point Spread Function (PSF) matching

Before accurate measurements can be made between the different wavelength
NIRCam filters, we must note that images with different filters have different
PSFs. The PSF Full Width at Half Maximum (FWHM) values in each band for the VV
191 system are found in the Windhorst et al. (2023) PEARLS overview paper (see
their Table 1). PSF matching is achieved by convolving the image with a kernel
generated from the PSF corresponding to the image and the reference PSF
(Boucaud et al., 2016). To accurately conduct multi-band photometry on the
globular clusters in VV191, we first convolved all images with a kernel to
match the lowest resolution F444W image.

PSFs were created with WebbPSF (Perrin et al., 2012) with a wavefront
measurement done on July 2, 2022, i.e., $\sim$1.07 days before observations
were taken. To convolve the short wavelength images to the longer wavelength
PSF, we need a kernel that is the ratio of the two PSFs. However, doing this
on the WebbPSFs introduces artifacts. To address this, we smooth the noise
with windowing functions: tophat, cosine bell, and split cosine bell windows.
These windowing functions are then multiplied by the Fourier transform of the
PSF. The PSFs and windowing functions were grid-searched to find the windowing
function that best reproduced the F444W PSF along a 1D profile through the
centers of the PSF. The grid search was done as follows: (1) starting at
parameter values of 0.01, each window was used to convolve the F090W PSF with
the parameter value passed to each of the windowing functions; (2) a 1D
profile from the center of the convolved PSF was compared to the 1D profile
from the source F444W PSF along the same pixel values using a chi-square
routine; (3) the optimal chi-square value and windowing function were recorded
as the combination to use for each of the images. The split cosine bell
windowing function was best in all cases, with an $\alpha$ value of 0.4 and a
$\beta$ value of $-0.1$. The $\alpha$ value is the percentage of array values
that are tapered, and the $\beta$ value is the inner diameter as a fraction of
the array size beyond which the taper begins and must be $\leq$ 1.0.

Figure 2: The VV 191a image is shown after calibration and galaxy subtraction
were performed. We used Photutils to map out point source aperture objects in
the F090W filter using a 3-pixel aperture radius. We further subdivide the
region usable for GC searches — i.e., away from the outer spiral arm of the
foreground spiral — into four elliptical sections. With this method, we could
compare the colors of GC candidates within the galaxy using CMDs from data in
each ellipse. Further details are given in Figure 3. The black ellipses are
background galaxies, and their point sources are not included in the analysis.

###  2.3 Photometry

The main advantage of aperture photometry is that it provides a simple measure
of the total light within a fixed radius, and is less affected by small
object-to-object differences in the actual profile shape. All photometry was
performed on the galaxy-subtracted image (see Keel et al. (2023) for details).
Before starting the analysis, the image is cropped to exclude the spiral
galaxy as much as possible, further reducing contamination from stars and dust
found within and around the spiral arms. The objects outlined in black are
also excluded (see Figure 2) and recognized as diffuse objects (i.e.,
background/foreground galaxies). Using the Photutils (Bradley et al., 2022)
package DAOStarFinder, positions of point-source objects are located using the
NIRCam F090W filter as the reference image. The Python class DAOStarFinder is
a class that implements the DAOFIND algorithm (Stetson, 1987). It searches
images for local density maxima with a peak amplitude greater than a specified
threshold (the threshold is applied to a convolved image) and a size and shape
similar to a defined 2D Gaussian kernel FWHM of $\simeq{4.7}$ pixels. Because
stars are not likely to be bright enough to be detected, either in the
foreground galaxy or in the elliptical galaxy itself, and background galaxies
are likely to be resolved, we take all objects identified in this process as
globular clusters. This approach works particularly well since virtually all
the individual GCs appear starlike since our target galaxy has a luminosity
distance $(d_{L})$ of approximately 228 Mpc. Point sources within the F090W
filter are initially stored as $x$ and $y$ pixel coordinates before being
converted to celestial coordinates. The celestial coordinates of the point
sources found in the F090W filter will be the reference coordinates used to
locate the corresponding sources in the F150W, F356W, and F444W filters and
are referred to as aperture objects. Once object apertures have been created,
we can perform photometry on the input data by summing the flux within the
given aperture. The apparent magnitude is defined as:

$m=-2.5\log_{10}(\phi)+{\rm ZP}.$ (1)

with the flux-density measurements, $\phi$, from each individual point source
object detected by the DOAStarFinder algorithm and zero point
$\rm(ZP)=28.0865$ for a pixel scale of 0$\buildrel\prime\prime\over{.}$03 per
pixel (Windhorst et al., 2023). We then can compute the absolute magnitude by
determining the distance modulus $(m-M)=36.79$ mag from:

$m-M=5\log_{10}\left(\frac{d_{L}}{\rm Mpc}\right)+25.$ (2)

##  3 The Color–Magnitude Data

We identify GC candidates across the entirety of the elliptical galaxy, a
fraction of which is obscured in the foreground by the dust associated with
VV191b. Figure 3 shows the color–magnitude diagram for the F090W magnitude
plotted against the (F090W – F150W) color. Each of the four panels corresponds
to a specific ellipse in Figure 2, with the top-left panel representing data
from the center ellipse, moving outward. We chose to analyze the data in
sections to check that the foreground spiral was not adding reddening to the
GC sample and to study any possible variation of GC properties with a
galactocentric radius. We conclude that this is not the case when we look at
the color in each of the four panels in Figure 3 and find the average (F090W –
F150W) color to be $\sim$ 0.25–0.75 mag. We would expect that the objects
found closer to the spiral to have a redder profile if there was some
contamination from spiral arm dust; however, this does not appear to be the
case in our observations.

Objects plotted below the bold dashed line fall below the 5$\sigma$ point
source completeness limit (Windhorst et al., 2023), and, therefore, are not
formally part of a complete sample of GCs. Data analysis and figures going
forward will only include objects detected above the 5$\sigma$ completeness
limit unless otherwise stated.

Figure 3: CMDs of F090W magnitude versus the $(F090W-F150W)$ color for our GC
sample. Each of the four panels corresponds to a specific ellipse in Figure 2,
with the top-left panel representing data from the center ellipse and then
moving outward. In all four panels of the CMDs, we see a distinct population
of GCs with a fairly uniform color distribution, which is roughly located at
$-0.25\leq\rm(F090W-F150W)\leq 1.0$ mag, and continues somewhat below the
completeness limit.

The 5$\sigma$ completeness limits of each filter are shown in table 1. In all
four panels of the CMDs, we see a distinct population of GCs with a reasonably
uniform color distribution, which is roughly located at
$-0.25\leq\rm(F090W-F150W)\leq 1.0$ mag, and continues below the completeness
limit. Many objects below the completeness limit are likely also GCs but are
not a complete sample. We find approximately 443 luminous GC candidates around
the elliptical. The CMDs for the GCs can now be used to determine more
quantitative features of the color/metallicity distributions and the GC
luminosity function turnover point.

##  4 GC Luminosity Function

The luminosity function, or the relative number of GCs with any given
magnitude, is one of the most fundamental properties of GC systems (Harris et
al., 2014). The turnover luminosity of the GCLF has been found to be
exceptionally constant over a large range of galaxies and various
environments, so much so that it has been used as a distance indicator (e.g.,
Harris, 1991; Whitmore, 1997; Rejkuba, 2012). Previous studies with HST data
in the V & I bands have shown a general turnover luminosity of the GCLF at
$M_{V}\approx-7.5$ (Harris et al., 2009; Rejkuba, 2012; Kundu & Whitmore,
2001). Previous studies have reported the dispersion, $\sigma$, of the
Gaussian describing the GCLF as varying considerably from one galaxy to the
next (Secker & Harris, 1993).

Table 1: 5$\sigma$ Point-source AB Mag Limit F090W | F150W | F356W | F444W | Source
---|---|---|---|---
27.88 | 28.24 | 29.01 | 28.81 | (Windhorst et al., 2023)

###  4.1 The Standard Model

Following other work (Harris, 1991; Jordán et al., 2007), we fit a Gaussian to
the GCLF to measure the peak magnitude and standard deviation (Harris, 1991;
Jordán et al., 2007). With the mean GC magnitude denoted as $\mu\equiv\langle
m\rangle$ and the Gaussian dispersion
$\sigma_{m}=\langle\left(m-\mu\right)^{2}\rangle^{1/2}$, we obtain the GCLF
fit as

$\frac{dN}{dm}=C\exp\Biggl{[}-\frac{\left(m-\mu\right)^{2}}{2\sigma_{m}^{2}}\Biggr{]},$
(3)

where C is an arbitrary amplitude fit as a parameter. As shown in Figure 4, we
do not quite reach the peak of the GCLF in our data. We find the estimated
GCLF turnover point in the F090W filter to be $M_{\rm abs}=-8.70\pm 0.29$ mag
and its dispersion to be $\sigma_{m}\approx 1.33$ mag, which is in agreement
with typical $\sigma_{m}\approx 1.3$–1.4 mag for GCs in massive galaxies with
low redshift (Harris et al., 2014). Figure 4 shows the GCLF histogram for
observed data above the 5$\sigma$ completeness limit as measured in the F090W
filter. Deeper photometry would be able to reveal the actual peak in the GCLF,
which will be proposed for future JWST cycles.

Figure 4: Histogram showing the luminosity function in the F090W filter. The
luminosity function does not reach the turnover point due to the data not
being a complete sample. The approximate magnitude for the data above the
5$\sigma$ completeness limit is $M_{\rm abs}=-8.70$, and the dispersion
$\sigma_{m}=1.33$. GCs are binned as the number of clusters per 0.5 magnitude
bin.

##  5 Cluster Unimodality

In many of the past studies of GC systems, authors have used color histograms
with double-Gaussian fits to decide whether the system falls into a bimodal
color distribution, indicating a population of metal-rich and metal-poor GCs
(e.g., Gebhardt & Kissler-Patig, 1999; Harris et al., 2009; Larsen et al.,
2001). In the case of VV 191a, a predominant feature to arise from the data is
the unimodality of the GC population. We use color histograms to determine the
color distribution of the clusters, and see if these show evidence for
bimodality. We found that the distribution was best fitted by a single
Gaussian, demonstrating the color spread is likely dominated by a more uniform
color distribution. This is a good indication that the GCs detected in this
study also share a relatively uniform metal distribution. In a bimodal
population, we would expect to see a GC population span the full typical range
of metallicities from $\rm[Fe/H]\simeq-2$ to 0 (Harris & Reina-Campos, 2023).
There is no indication that these GCs had formed in more recent epochs. If
they had, they would appear as a population far bluer and brighter than the
typical GC sequence.

Figure 5: Color histograms in (F090W – F150W) and (F356W – F444W) showing the
color distribution of the VV 191a clusters. Data represents objects that lie
above the 5$\sigma$ completeness limits in Figure 3. The single Gaussian
distribution fits to the data strongly indicates that the GC population has a
unimodal color distribution rather than showing evidence for two distinct
populations.  Figure 6: CMDs showing GC models in the F090W vs (F090W – F150W)
and F356W vs (F356W – F444W) filters. The larger circles represent the model,
which describes a GC mass of $10^{6}M_{\odot}$, and the triangles represent
the model using $10^{7}M_{\odot}$. The red and blue lines are stellar
isochrone models for the (hypothetical) brightest individual stars in the
foreground spiral VV191b at $z=0.0514$, showing that objects detected in the
CMDs are mostly GCs in VV 191a, and in general not consistent with luminous
stars in the foreground spiral. The diagonal dashed line is the 5$\sigma$
completeness limit.

Also, NGC 4374 has a unimodal color distribution. However, it is heavily
skewed to toward red colors, suggesting that a large number of red (presumably
metal-rich) GCs exists, but these appear to form a uniform distribution rather
than a distinct population (Schindler et al., 1998).

##  6 GC model

When modeling the GC population, we used the whole data set to fully
understand how well the models represent the data, which is addressed in
Figure 6. The CMDs show F090W vs (F090W – F150W) and F356W vs (F356W – F444W).
We use the PARSEC CMD3.7 model using single-burst stellar populations,
integrated magnitudes (for 1 $M_{\odot}$) (Salpeter, 1955; Chabrier, 2003)
with a fixed age of 13 Gyr, while varying the GC mass using $10^{6}M_{\odot}$
represented by a triangle, and $10^{7}M_{\odot}$ represented by a circle, to
address how well the model fits our data. This is shown in Figure 6. We chose
to use an age of 13 Gyr because when reducing the age of the model somewhat,
there is very little change in the predicted colors. Figure 7 shows this trend
in more detail.

Figure 7: Color-color diagram plotted with both stellar isochrone and GC
models. The GC model represents ages of 1 Gyr, 5 Gyr, and 13 Gyr, while the
vertical turquoise-blue-green-orange) dot-dashed isochrone model represents
various stellar ages and metallicities of the brightest stars that may be
found within the spiral galaxy. These models lie in general outside that
populated by the data. However, we find that the GC models also do not
represent the data accurately, with the GC data in general being redder than
the models in the reddest NIRCam filters.

The model shows that the VV 191a GCs (above the completeness limit) tend to be
more massive, reaching upward of $\simeq 10^{7}M_{\odot}$. It is likely that
we are detecting the brightest and most massive members of the GC population
while the fainter and less massive GCs are left undetected or below our formal
completeness limits. We use metallicities [M/H] ranging from $\simeq-3.5$ to
$-1.2$, i.e., a range we would expect a GC population to span. However, we
find that that models do not fit the data as we would expect. In the (F090W –
F150W) CMD, the model appears to be slightly redder than the data, appearing
more dependent on color and on brightness. In contrast, the (F356W – F444W)
models are far more dependent on brightness and less on color. These filters
show that the GC model is in general bluesr than the data. Future models may
need to be revised to improve the modeling of near-IR colors of old, metal-
poor GC populations. The red and blue lines are stellar isochrone models for
the brightest individual stars in the foreground spiral VV191b at z=0.0514,
demonstrating that objects detected in the CMDs are largely GCs and are not
consistent with being tge brightest stars in the foreground spiral. Their
spatial distribution in Fig. 2 is not consistent wigh them being the brightest
stars in the foreground spiral either.

##  7 Stellar model

For a final check of objects found within the respective completeness limit
and assumed to be GCs, we use a color-color diagram plotted with PARSEC CMD3.7
stellar isochrone model (Bressan et al., 2012) as shown in Figure 7, along
with GC models for reference. The stellar isochrone model demonstrates that
most objects we detect are GCs and not residual stars from the foreground
spiral galaxy VV 191b. The stellar isochrone model is shown for stellar ages
of $10^{7}$ – $10^{9}$ years with a metallicity [M/H] of 0 and -1. The GC
model covers ages of 1 Gyr, 5 Gyr, and 13 Gyr with varying metallicity [M/H].
As mentioned in the above section, the current GC models appear too red in the
(F090 – F150W) and far too blue in the (F356W – F444W) compared to the current
data. From the models representing the GCs, we can conclude that the current
models do not fully represent the data.

##  8 Summary and conclusion

In this study, we have identified a GC sample belonging to the elliptical
galaxy VV 191a, and we present JWST photometry using the NIRCam F090W, F150W,
F356W, and F444W filters. A brief summary of our findings is as follows:

  1. 1.

Using the Photutils (Bradley et al., 2022) package DAOStarFinder, we locate
starlike point source objects and carefully reject bright background objects
that are unassociated with VV 191a. We use photometry to present CMDs to find
as many as 443 GC candidates that fall above the 5$\sigma$ completeness limits
for analysis.

  2. 2.

The color histograms show a unimodal color distribution that is well fit by a
single Gaussian, using color to primarily trace the metallicity (see Figure
5). This is a good indication that the GCs detected in this study share a
relatively uniform color distribution. In a bimodal population, we would
expect to see a GC population span the full typical range of metallicities
from [Fe/H] $\simeq$ –2 to 0 (Harris & Reina-Campos, 2023). The current data
shows no indication that these GCs have formed in more recent epochs. If they
had, they would appear as a population of bright clusters far bluer than the
typical GC sequence.

  3. 3.

We find the sample’s GCLF falls short of the turnover magnitude and is,
therefore, more luminous than what is typically expected with an absolute
magnitude of $M_{F090W}=-8.70\pm 0.29$ mag, and the approximate dispersion
$\sigma_{m}\approx 1.33$ mag, which is in agreement with typical
$\sigma_{m}\approx 1.3-1.4$ mag for GCs in massive galaxies with low redshift
(Harris et al., 2014).

  4. 4.

We use the PARSEC CMD3.7 GC model (Salpeter, 1955; Chabrier, 2003) to test how
well it describes our our JWST data. The models show that the VV 191a GCs
(above our 5$\sigma$ completeness limit) tend to be more massive, reaching
upward of $\simeq 10^{7}M_{\odot}$. It is likely we are detecting the
brightest and most massive members of the population, while the fainter and
less massive GCs remain undetected. We have chosen a typical range in
metallicities that we would expect a GC population to span. We find that the
current GC models do not describe the JWST near-IR data. The models are redder
than the data in (F090W – F150W), and are bluer than the data in (F356W –
F444W). Future models may need to be revised to improve the modeling of near-
IR colors of old, metal-poor stellar populations.

  5. 5.

With PARSEC CMD3.7 stellar isochrone model (Bressan et al., 2012) we are
confident that the objects in our analysis are indeed GCs and not objects from
background galaxies, or the brightest stars in the foreground spiral. The
stellar isochrone model in the color-color diagram confirms that the data are
not likely foreground stars in the spiral galaxy but GCs in the elliptical VV
191a.

We express our sincere thanks to Alan Dressler for helpful discussions. This
work is based on observations made with the NASA/ESA/CSA James Webb Space
Telescope. The data were obtained from the Mikulski Archive for Space
Telescopes (MAST) 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 1176 and 2738. R.A.W. acknowledges support from NASA JWST
Interdisciplinary Scientist grants NAG5-12460, NNX14AN10G and 80NSSC18K0200
from GSFC. M.N. acknowledges INAF-Mainstreams 1.05.01.86.20. M.A.M.
acknowledges the support of a National Research Council of Canada Plaskett
Fellowship and the Australian Research Council Centre of Excellence for All
Sky Astrophysics in 3 Dimensions (ASTRO 3D) through project number CE17010001.
C.N.A.W. acknowledges funding from the JWST/NIRCam contract NASS-0215 to the
University of Arizona.

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