# JWST MIRI and NIRCam Unveil Previously Unseen Infrared Stellar Populations
in NGC 6822

Conor Nally1, Olivia C. Jones2, Laura Lenkić3, Nolan Habel4, Alec S.
Hirschauer5, Margaret Meixner4, P. J. Kavanagh6, Martha L. Boyer5, Annette M.
N. Ferguson1, B. A. Sargent5,7, Omnarayani Nayak5 and Tea Temim8

1 Institute for Astronomy, University of Edinburgh, Blackford Hill, Edinburgh,
EH9 3HJ, UK
2 UK Astronomy Technology Centre, Royal Observatory, Blackford Hill,
Edinburgh, EH9 3HJ, UK
3 Stratospheric Observatory for Infrared Astronomy, NASA Ames Research Center,
Mail Stop 204-14, Moffett Field, CA 94035, USA
4 Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak
Grove Dr., Pasadena, CA 91109, USA
5 Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD
21218, USA
6 Department of Experimental Physics, Maynooth University, Maynooth, Co.
Kildare, Ireland
7 Department of Physics & Astronomy, Johns Hopkins University, 3400 N. Charles
St., Baltimore, MD 21218, USA
8 Department of Astrophysical Sciences, Princeton E-mail<EMAIL_ADDRESS>0000-0002-7512-1662 0000-0003-4870-5547 0000-0003-4023-8657
0000-0002-2667-1676 0000-0002-2954-8622 0000-0002-0522-3743
0000-0001-6872-2358 0000-0003-4850-9589 0000-0001-7934-1278
0000-0001-9855-8261 0000-0001-6576-6339 0000-0001-7380-3144

(Accepted XXX. Received YYY; in original form ZZZ)

###### Abstract

NGC 6822 is a nearby ($\sim$490 kpc) non-interacting low-metallicity (0.2
$Z_{\odot}$) dwarf galaxy which hosts several prominent H ii regions,
including sites of highly embedded active star formation. In this work, we
present an imaging survey of NGC 6822 conducted with the NIRCam and MIRI
instruments onboard JWST. We provide a description of the data reduction,
source extraction, and stellar population identifications from combined near-
and mid-infrared (IR) photometry. Our NIRCam observations reach seven
magnitudes deeper than previous _JHK_ s surveys of this galaxy, which were
sensitive to just below the tip of the red giant branch (TRGB). These JWST
observations thus reveal for the first time in the near-IR the red clump
stellar population and extend nearly three magnitudes deeper. In the mid-IR,
we observe roughly two magnitudes below the TRGB with the MIRI F770W and
F1000W filters. With these improvements in sensitivity, we produce a catalogue
of $\sim$900,000 point sources over an area of $\sim 6.0\times 4.3$ arcmin2.
We present several NIRCam and MIRI colour-magnitude diagrams and discuss which
colour combinations provide useful separations of various stellar populations
to aid in future JWST observation planning. Finally, we find populations of
carbon- and oxygen-rich asymptotic giant branch stars which will assist in
improving our understanding of dust production in low-metallicity, early
Universe analogue galaxies.

###### keywords:

galaxies: dwarf – galaxies: irregular – galaxies: individual (NGC 6822) –
infrared: galaxies – infrared: stars – stars: AGB and post-AGB

††pubyear: 2023††pagerange: JWST MIRI and NIRCam Unveil Previously Unseen
Infrared Stellar Populations in NGC 6822–A

##  1 Introduction

The dwarf irregular galaxy NGC 6822 is one of the closest ($\mathrm{d}\sim
490\pm 40$ kpc; Sibbons et al., 2012; Fusco et al., 2012) in the Local Group.
It is famously home to some of the largest, brightest star-forming regions in
the local universe (Kennicutt, 1979; Hodge et al., 1989; O’Dell et al., 1999;
Jones et al., 2019) with active star formation throughout its disk and central
bar. Its low metallicity ([Fe/H] $\approx-1.2$; $\sim$30% $Z_{\odot}$;
Skillman et al., 1989; Lee et al., 2006), elevated star formation rate, and
overall youth make it a nearby analogue of galaxies at the universal epoch of
peak star formation ($z\sim 1.5-2$; Madau & Dickinson, 2014), at which point a
majority of the universe’s star formation and chemical enrichment is expected
to have taken place. We note that while NGC 6822 is generally considered to be
isolated (de Blok & Walter, 2000; Battinelli et al., 2006) without any
detectable satellites, Zhang et al. (2021) postulate a 200 kpc close passage
within the virial radius of the Milky Way $3-4$ Gyr ago. Table 1 lists
properties of NGC 6822 that have been adopted for this study.

As a target of many stellar populations studies, NGC 6822 has been extensively
surveyed in both the optical and infrared (IR). An old ($\sim$11 Gyr) stellar
component within the galaxy was inferred with the first discovery of RR-Lyrae
stars (Clementini et al., 2003; Baldacci et al., 2003), while several
localised bright H ii regions in the central bar Cannon et al. (2006) show the
galaxy is still actively forming stars (Jones et al., 2019). After steady star
formation over its evolution, NGC 6822 began a burst of star formation $\sim$3
Gyr ago (Tolstoy et al., 2001) and has continued to increase over the last
$100-200$ Myr (Gallart et al., 1996). Optical surveys with the _Hubble Space
Telescope_ (HST; Wyder, 2001) and _Subaru_ (Tantalo et al., 2022) detect
intermediate age red clump (RC) and red giant branch (RGB) stars. The
asymptotic giant branch (AGB) stars within the galaxy trace the intermediate
to old stellar populations and have been extensively studied in the IR (see
e.g., Cioni & Habing, 2005; Sibbons et al., 2012; Hirschauer et al., 2020).
These cool luminous stars evolve from low- to intermediate-mass ($\sim 1.5-10$
$M_{\odot}$) main sequence (MS) progenitors and may play a vital role in the
dust evolution of galaxies.

The dust contribution from evolved stars in metal-poor environments and at
high redshift is not currently well defined. In particular, for young galaxies
inhabiting the early universe, it can be expected that insufficient time has
elapsed for MS stars to reach the AGB phase, which suggests that they do not
contribute significantly to the overall dust budget. Observations have thus
far shown, however, that large reservoirs of dust appear to exist at redshifts
out to $z$ $\sim$ 6 (Bertoldi et al., 2003; Robson et al., 2004; Beelen et
al., 2006; Algera et al., 2023). Studies of nearby metal-poor systems such as
dwarf galaxies and globular clusters have shown that dust can originate from
AGB stars in these environments (McDonald et al., 2010; Whitelock et al.,
2018; Jones et al., 2018), however the effects of metallicity on AGB star dust
production are disputed (van Loon et al., 2005; McDonald et al., 2011; Sloan
et al., 2012, 2016). The Surveying the Agents of a Galaxy’s Evolution (SAGE)
surveys (Meixner et al., 2006; Gordon et al., 2011) mapped the Magellanic
Clouds with _Spitzer_ from 3.6 to 160 µm. These data enabled detailed studies
characterising the evolved stellar populations within the Magellanic Clouds
and their contributions to dust production (Blum et al., 2006; Srinivasan et
al., 2009; Boyer et al., 2011). Boyer et al. (2011) find that the very dusty
“extreme” carbon-rich AGB stars dominate the return of dust into the
interstellar medium (ISM) in both galaxies ($\sim$90% of the dust input from
evolved stars; Boyer et al., 2012), while supergiant (SG) stars do not
contribute significantly ($<$4%). The authors also find that in the higher
metallicity Large Magellanic Cloud (LMC), oxygen-rich AGBs produce overall
more dust than the lower-mass carbon-rich AGB stars, while in the Small
Magellanic Cloud they contribute dust roughly equally.

While studies such as SAGE have made great progress towards understanding dust
production mechanisms at low metallicity, it is now possible to extend this
work to more distant systems with JWST. The JWST imaging program of NGC 6822
(program ID: 1234, PI: M. Meixner) that we present in this work allows us to
investigate the evolved star population out to $\sim$500 kpc at the resolution
and depth that was achieved by _Spitzer_ in the Magellanic Clouds. This work
builds upon the studies of Jones et al. (2017), Hirschauer et al. (2020), and
Kinson et al. (2021) that characterised the stellar populations of NGC 6822.

This paper presents the overview of the NGC 6822 JWST imaging program,
including the observation details, data reduction, photometric extraction, and
combined NIRCam and MIRI colour-magnitude diagrams (CMDs) used to identify its
various stellar populations, with a focus on the evolved stars. Section 2
presents the observational strategy in detail. We describe the data reduction
and photometric extractions in Section 3. In Section 4, we present and discuss
our resulting images, stellar classifications, and luminosity functions.
Finally, we summarise the results in Section 5.

##  2 Observation Strategy

We have imaged the central bar of the galaxy NGC 6822 with JWST (Program ID:
1234; PI: M. Meixner), utilizing both the Near Infrared Camera (NIRCam; Rieke
et al., 2005, 2023) and Mid-Infrared Instrument (MIRI; Rieke et al., 2015). In
total, 19.92 hours of integration time were split between NIRCam ($\sim$4.80
hours) and MIRI ($\sim$15.12 hours). The spatial coverage for the two
instruments, which focus on the central stellar bar of NGC 6822, is
illustrated in Figure 1. The FoV of both instruments includes the newly-
discovered young, massive, embedded super star cluster (SSC) candidate region
Spitzer I (e.g., Jones et al., 2019; Hirschauer et al., 2020; Lenkić et al.,
2023), in addition to a plethora of IR-bright, dusty sources in the galaxy’s
central stellar bar (Sibbons et al., 2012; Jones et al., 2019; Hirschauer et
al., 2020; Kinson et al., 2022). Additionally, we obtained coordinated
parallel observations of off-target regions.

Figure 1: Spitzer three-colour image of NGC 6822 from Cannon et al. (2006)
with the JWST NIRCam and MIRI survey regions superimposed (solid lines). The
left image shows the NIRCam coverage and the right image the MIRI coverage.
The NIRCam tile with an associated MIRI parallel is shown in green, while the
MIRI tile with its associated NIRCam parallel is in red with detector modules
A and B labelled accordingly. North is up and east is to the left. Properties
of NGC 6822
---
Nominal centre point | 19:44:56 -14:47:51
Distance | 490 $\pm$ 40 kpc (Fusco et al., 2012)
Distance modulus $(m-M)_{0}$ | 23.45
E(B-V) | 0.35 $\pm$ 0.04 (Tantalo et al., 2022)
Metallicity | [Fe/H]$=-1.2$ (Lee et al., 2006)
Table 1: Summary of NGC 6822 properties and survey details. NIRCam Observation
Properties
---
Survey area ($arcmin^{2}$) | 29.0
Total time (hr) | 4.80
Filters | F115W, F200W, F356W, F444W
Central $\lambda$ ($\mu m$) | 1.154, 1.990, 3.563, 4.421
FWHM at $\lambda$ (pixel) | 1.194, 2.065, 1.810, 2.222
Completeness limits at $\lambda$ (mag) | 26.56 26.49 24.99 25.34
Table 2: Summary of NIRCam observation properties. Note that the quoted values
for the PSF full widths at half maximum are that of the simulated PSF. MIRI
Observation Properties
---
Survey area ($arcmin^{2}$) | 14.5
Total time (hr) | 15.12
Filters | F770W, F1000W, F1500W, F2100W
Central $\lambda$ ($\mu m$) | 7.528, 9.883, 14.932, 20.563
FWHM at $\lambda$ (pixel) | 2.445, 2.982, 4.436, 6.127
Completeness limits at $\lambda$ (mag) | 23.81 23.7 24.55 20.48
Table 3: Summary of MIRI observation properties.

###  2.1 NIRCam

Our observations with NIRCam comprised a total of $\sim$4.80 hours of
integration time and were obtained on 2022 September 4 utilizing the F115W and
F200W short-wavelength filters and the F356W and F444W long-wavelength
filters. The observations were taken with a full subarray and implemented the
fullbox 4tight primary dither pattern, which ensures that the gaps between the
four short-wavelength detector subarrays in each module are filled, as is the
$\sim$43″ gap between the A and B modules. We positioned the east and west
portions of our mosaic such that there is a 10.0% overlap in both the rows and
columns of the resultant 2$\times$1 mosaic. The bright2 readout pattern was
selected to optimize the signal-to-noise ratio (S/N), with one integration per
exposure and seven groups per integration. With a three-point sub-pixel dither
pattern to sample the point spread function (PSF), this resulted in 12 total
dithers, with an overall total exposure time of 1803.8 seconds for each of the
short- + long-wavelength filter combinations (i.e., F115W + F356W and F200W +
F444W). See also Table 2 for filter properties and appendix Table 5 for a
complete summary of exposure parameters.

Coverage of NGC 6822’s central stellar bar was achieved by restricting the
aperture position angle (PA) of the JWST spacecraft to between 92.0∘ and
93.0∘. Finally, observations of the east and west halves of the mosaic were
grouped to be non-interruptible, ensuring a consistent relative orientation.
The NIRCam mosaic was centred at RA = 19:44:56.1990, Dec. = –14:47:51.29; the
tile with a MIRI coordinated parallel is centred at RA = 19:45:00.2644, Dec. =
–14:47:55.23.

Our selection of NIRCam filters was based upon prior work on stellar
populations at similar wavelengths. The F115W and F200W filters are the
closest equivalent to standard Johnson _J_ and _K s_ filters, respectively,
while the F356W and F444W filters are equivalent to _Spitzer_ IRAC [3.6] and
[4.5], respectively. With these filter selections, we are able to construct a
standard collection of diagnostic near-IR CMDs, such as F115W – F200W vs.
F200W (equivalent to _J_ – _K s_ vs.  _$K_{s}$_). This allows for comparative
study with previous observations made of other galaxies, including the SAGE
studies of the Magellanic Clouds (e.g., Blum et al., 2006; Meixner et al.,
2006; Whitney et al., 2008; Gordon et al., 2011), the DUST in Nearby Galaxies
with Spitzer (DUSTiNGS) project which surveyed local group dwarf galaxies in
the mid-IR (e.g., Boyer et al., 2015a; McQuinn et al., 2017; Goldman et al.,
2019), and others (e.g., Jones et al., 2015, 2018, 2019; Hirschauer et al.,
2020).

###  2.2 MIRI

MIRI observations totalling $\sim$15.12 hours were obtained between 2022
September 4 and 2022 September 15. The 1$\times$6 mosaic was restricted to a
PA of 93∘ and positioned to run along the central stellar bar of NGC 6822.
Each pointing in the mosaic included a 10.0% overlap between the rows to
ensure smooth background matching between the fields. Due to an error in the
program implementation, only five of the six MIRI tiles in the mosaic were
observed on 2022 September 4. The final MIRI tile (and its coordinated NIRCam
parallel observations) were subsequently obtained on 15 September 2022. Our
program employed the F770W, F1000W, F1500W, and F2100W filters using a small
four-point cycling dither pattern, the full subarray and fastr1 readout
pattern. A list of filter properties can be found in Table 3 and a list of
exposure parameters including groups per integration and integrations per
exposure for each filter is provided in appendix Table 6. The MIRI mosaic was
centred at RA = 19:44:58.0949, Dec. = –14:48.20.62; the MIRI tile with a
NIRCam coordinated parallel was centred at RA = 19:44:58.4923, Dec. =
–14:46:40.85.

Our selection of MIRI filters was guided by the predicted MIRI colours of mid-
IR bright stellar populations from Jones et al. (2017): CMDs constructed from
these wavelengths reveal the reddest and dustiest sources, distinguishing
evolved (SGs and AGB stars) and young (YSOs) stellar populations. In addition,
the F770W filter traces polycyclic aromatic hydrocarbon (PAH) emission which
is expected to be prevalent in star-forming regions, while the F1000W filter
is sensitive to the 10 $\mu$m silicate absorption present in the spectral
signatures of dusty, embedded YSOs.

###  2.3 Parallel Imaging

Accompanying our primary pointings, we obtained parallel observations in both
NIRCam and MIRI. Only one of the two 2$\times$1 mosaic tiles in our primary
NIRCam observations has an associated MIRI coordinated parallel (see Figure
1). This parallel observation was designed to provide background comparison
images by observing a field offset from the primary target by the intrinsic
physical separation between NIRCam and MIRI on the JWST focal plane. We were
able to position our pointing such that the eastern tile of our primary NIRCam
mosaic was placed along the galaxy’s main body, and the coordinated MIRI
parallel was located north of the disk, offset from the Hubble X star-forming
region. The MIRI parallel images were obtained at this location in the F1000W
and F1500W filters using a full subarray, a slowr1 readout pattern, with five
groups per integration and one integration per exposure over the 12 total
dithers, resulting in a total exposure time of 1433.4 seconds per filter
(appendix Table 6). The total footprint encompasses 74″$\times$113″. This
readout pattern was selected in contrast with the MIRI prime observations
which used fastr1 (see subsection 2.2) due to data rate limits.

One of our six mosaic tiles in the primary MIRI observation has a NIRCam
coordinated parallel (second from the top; see Figure 1). This tile was
selected due to the advantageous position in the instrument focal plane of the
Hubble IV star-forming region, which falls into NIRCam’s Module B. Module A is
situated further from the galaxy and is thus a useful pointing for obtaining
information on a region of the galaxy that is not actively forming stars. The
two regions image an area of 132″$\times$132″each. These parallels imaged in
the F140M, F150W, F277W, and F335M bands. A complete summary of the NIRCam
parallel observing parameters including read mode, groups, integrations, and
total exposure time is given in appendix Table 5.

##  3 Data reduction and Photometry

###  3.1 NIRCam Image Processing

The uncalibrated NIRCam images were processed through all three stages of the
JWST pipeline using version 1.9.6 and Calibration Reference Data System (CRDS)
version 11.16.20. For Stage-1 processing, we used CRDS context 1063
(jwst_1063.pmap). We implemented the frame0 correction to recover stars that
saturated in the first group ($\sim$21 s), but were unsaturated in the first
10.7 seconds comprising frame0 (ramp_fit.suppress_one_group=False). Stage-2
processing was run with CRDS context 1075 (jwst_1075.pmap). The output of
Stage-2 (*_cal.fits) were corrected for 1/f noise using the image1overf.py
tool from Willott (2022). The resulting files were then aligned to Gaia DR3
using the JWST/Hubble Alignment Tool (JHAT; Rest, 2023). Stage-3 mosaics were
created with CRDS context 1077 (jwst_1077.pmap). We skipped the tweakreg step
in Stage-3 since the WCS alignment was provided already by JHAT. The
difference in pmap for each stage of the pipeline occurred due to a rapid
succession of reference file deliveries while we were processing the data. The
only update relevant to this dataset between the 1063 and 1075 pmaps is an
update to the snowball correction step. Snowballs are rare in this dataset, so
we did not apply that correction.

###  3.2 MIRI Image Processing

A description of the MIRI processing for this observational program is given
in Lenkić et al. (2023) but we give a short overview here and describe the
treatment of the background in more detail. To create calibrated MIRI images
we used JWST pipeline version 1.9.5 with CRDS version 11.16.21 and context
jwst_1084.pmap. Each of the raw MIRI files was processed through
Dectector1Pipeline and the output through Image2Pipeline with default
parameters. The resulting images were then aligned to _Gaia_ DR3 using the
tweakreg step in the pipeline.

We generated instrumental backgrounds from Visits 001 and 005 of Observation
007 (i.e., the two tiles at the mosaic edges), as these are least affected by
real diffuse emission. While this is not the ideal strategy, it helps to
mitigate detector effects and reveal fainter sources in the galaxy. To
generate an instrumental background image free of point sources and diffuse
emission, we median combined all dithers of a given filter in both tiles.
However, in the case of the F770W and F1000W filters, significant structure
due to the extent of real diffuse emission in these tiles rendered these
backgrounds unusable. For these filters we instead created a model
instrumental background by taking comparatively unaffected detector rows and
columns in the median combined background in order to create a representative
median row and column. These were then mapped onto the detector plane to
produce the model background which also accounts for row and column
calibration artefacts (Dicken et al., in prep.). An example of this is shown
in Figure 2.

For the F1500W and F2100W filters, only minimal structure around the brightest
sources remained in the median background. Even though the residual
contamination is low, it can still manifest in background subtracted images as
faint shadows dispersed on the image. To remove the residuals we manually
masked their location and applied an approximate ‘filling’ of the gaps using
the ndimage.distance_transform_edt module in SciPy. Once backgrounds were
created for all filters, we subtracted the instrumental background images from
each dither in the mosaic tiles. Since Visit 001 of Observation 009 was
performed 10 days after the other visits, we found that the background levels
had increased slightly and corrected for this by determining a simple
background offset from regions on the detector free of diffuse emission.
Overall we found that our background subtraction methods performed well in
reducing the background level across all mosaic tiles in all filters. We then
constructed mosaics from the background subtracted images using
Image3Pipeline.

Figure 2: Example of background model applied to an F770W dither. The
uncorrected image, the model instrumental background, and background
subtracted images are shown in left, middle, and right, respectively. Only the
main imager field is shown as we exclude the Lyot coronagraph from our
mosaics.

###  3.3 Source Detection

Point-source photometry was extracted using the starbugii (Nally & Jones,
2022) photometric tool and pipeline which is optimised for JWST observations
of crowded stellar populations within complex environments (e.g. Jones et al.,
2023). This pipeline performs point-source extraction and band merging across
multiple observations and wavelengths utilising core functions from the python
photutils (Bradley et al., 2022) package. A complete set of relevant starbugii
parameters and their values adopted for our photometric extractions are listed
in appendix Table 7.

The individual exposures from the Gaia-aligned Stage-2 images are used for
source detection with starbug2 $--$detect. Sources with a $5\sigma$ detection
above the sky, which is initially estimated locally within an annulus, are
first located by centroid fitting. The geometry of each point source is
calculated and sharpness and roundness values are assigned. We remove cosmic
rays from the catalogue by setting an upper limit on sharpness and faint peaks
in the dust structure by setting a lower limit. The source symmetry is
measured using roundness; we are able to remove most resolved background
galaxies and further spurious detections within the dust structure by limiting
the allowed level of asymmetry.

The NIRCam fullbox 4tight dither mode results in four sets of three
overlapping exposures for a given pointing. Only sources detected in at least
two frames of each set are retained in the resulting catalogue; any sporadic
source not meeting this threshold is discarded as a likely cosmic ray or other
detector artefact while retaining true sources at the detector edges. For the
MIRI images, the full cycling, small mode results in four dithers, so we
stipulate that a source must be detected in three or more exposures. The flux
distribution between the exposures is examined and sources with asymmetric
distributions (the mean and median differ by more than 5%) are assigned the
flag SRC_VAR. Matching between frames in the image stack is done with a
nearest neighbour calculation with a threshold separation of 0.1 arcseconds.

We conduct aperture photometry on these sources in each individual frame. A
fixed aperture radius of 1.5 pixels and a sky annulus with an inner and outer
radius of 3.0 and 4.5 pixels, respectively, is used for all NIRCam bands, and
the aperture correction is interpolated between values given in CRDS
jwst_nircam_apcorr_0004.fits. The MIRI images are treated the same but we
increase the aperture radius to 2.5 pixels for F770W and F1000W, and 3.0
pixels for F1500W and F2100W to account for the larger PSFs at longer
wavelengths. The backgrounds are calculated within a 4.0-5.5 and 4.5-6.0 pixel
annuli respectively, and aperture corrections are calculated from
jwst_miri_apcorr_0005.fits. The data quality array within the aperture of each
source is inspected and we flag sources with saturated or DO_NOT_USE pixels
with the starbugii flag SRC_BAD and pixels that contained a jump during
detection with SRC_JMP.

We present Table 4 containing a list of source counts for every filter and an
estimate of sensitivity values.

###  3.4 PSF Photometry

The nebulous background emission underlying our images of NGC 6822 is modelled
using starbug2 $--$background. This routine places masking apertures of
varying sizes, calculated on the flux of each source, and fills them with the
median pixel value within a local annulus. For every pixel in the image, the
background is measured by averaging all the local pixels within a set box
size. This process creates an effective representation of the nebulous
emission; by subtracting this diffuse emission background from a single
exposure, we create a clean image of our field with nebulous emission removed
onto which PSFs can be accurately fit.

For each detector subarray within NIRCam, we generated a five arcsecond PSF
with webbpsf (Perrin et al., 2014) version 1.1.1. The single exposures have
their nebulous background estimated and subtracted, and we run PSF photometry
using starbug2 $--$psf on the residual image at the source positions from the
combined and cleaned source list generated in our aperture photometry step.
The centroid position is left as a free parameter, allowing both flux and
position to be fit during the routine. If the newly fitted centroid position
differs from the initial guess by greater than 0.1 arcseconds, we refit the
flux but hold the position fixed at the initial guess. This results in a
poorer fit and therefore we flag the source with SRC_FIX.

Unfortunately, the MIRI PSFs simulated by webbpsf do not currently include the
cruciform structure which is known to contain up to $\sim$26% of the flux in
the F770W band (Gáspár et al., 2021), resulting in poor PSF fits and some flux
which is unaccounted for. In this work, we therefore use aperture photometry
for all the MIRI detections in our catalogue, rather than PSF photometry.

###  3.5 Photometric Corrections

We calculate and apply instrumental zero point magnitudes to calibrate the PSF
photometry because they are not normalised to physical units. For each filter,
a cleaned aperture photometry catalogue which retains only the most reliable
point sources is used as the base to determine the zero point. To produce the
clean source list from the main catalogue, both the faintest and brightest
sources are removed to limit sources with low S/N, partially-saturated
objects, and any potential remaining detector artefacts. Sources must have a
photometric error of less than 0.1 and must not have any poor-quality data
flags. These cuts eliminate over 80% of the sources in the main catalogue.
Finally, these sources are matched to the equivalent source in the PSF
catalogue. We use starbug2 $--$calc-instr-zp to calculate the median
difference in the source magnitudes measured by aperture photometry and PSF
fitting to obtain instrumental zero point magnitudes which are subsequently
used to calibrate the PSF photometry from starbugii to the AB magnitude
system. For easier comparison with past works, we convert these magnitudes to
the Vega system using the reference files jwst_nircam_abvegaoffset_0001.asdf
and jwst_miri_abvegaoffset_0001.asdf.

Finally, as NGC 6822 is located at a low galactic latitude it is necessary to
correct the NIRCam photometry for foreground reddening. We adopt the value
E(B$-$V) $=0.36$ (Tantalo et al., 2022) to correct for the moderate Galactic
foreground extinction and apply the extinction curve of Cardelli et al. (1989)
assuming $R_{V}=3.1$. No extinction corrections were applied to the MIRI data,
as foreground reddening in mid-IR wavelengths is negligible. Nor was
differential extinction internal to NGC 6822 accounted for as this is assumed
to be insignificant compared to photometric uncertainties due to crowding.

###  3.6 Catalogue

Individual filter band catalogues are merged together to form a combined
NIRCam and MIRI point-source catalogue for NGC 6822 with starbug2-match
$--$band. Prior to any matching, the photometric uncertainty of each source is
assessed, and anything with a magnitude error greater than 10% is removed from
the individual catalogues. This reduces the likelihood of mismatching high-
quality sources with any remaining spurious sources, producing a reliable
band-matched catalogue at the possible cost of completeness.

Initially, we treat the NIRCam and MIRI catalogues separately, applying the
same methodology to the band matching within each instrument. The matching
routine starts with the shortest-wavelength catalogue, as the smaller PSF full
width at half maximum (FWHM) leads to the highest astrometric certainty. This
is matched with a nearest neighbours method to the next-shortest wavelength
catalogue, with any unmatched sources above the separation threshold appended
to the end. The position used for each source is taken from the shortest-
wavelength catalogue in which it initially appeared, allowing for faint red
objects such as highly dust-enshrouded AGB stars that are not visible in the
near-IR to be retained. We used a separation threshold that increases as the
PSF size increases, as using a single threshold larger than the astrometric
uncertainty of the longest MIRI wavelengths would cause mismatching in the
shortest NIRCam filters. We match short wavelength NIRCam filters using a
threshold of 0.06″ and long wavelength NIRCam filters with 0.1″. Within MIRI
we adopt 0.15″ for F770W and F1000W, 0.2″ for F1500W, and 0.25″ for F2100W.

Finally, we merge the NIRCam and MIRI catalogues with a separation threshold
of 0.3″. We expect many of the reddest and most dust-enshrouded sources
detected in the long-wavelength MIRI data to be missing from the shortest-
wavelength NIRCam images. However, the depth and sensitivity of F115W and
F200W result in a catalogue populated by many faint blue sources.
Consequently, a simple positional matching approach between a long-wavelength
MIRI band and a short-wavelength NIRCam band would likely result in a
significant number of mismatches because of the many sources present at short
wavelengths which lie along similar lines of sight. To combat this issue we
require any sources matched between NIRCam and MIRI to have an F444W
detection. In other words, a source in our MIRI catalogue will be compared
with all sources in the NIRCam catalogue within the matching radius and paired
with the nearest source for which a detection in the F444W band exists. If no
NIRCam sources within the matching radius are detected in the F444W band, the
MIRI source will be assumed to have no NIRCam counterpart and will
subsequently be appended to the catalogue as a new object. Thus both blue and
red objects in the catalogue will be retained and the chance of a mismatch
between co-located sources reduced.

###  3.7 Foreground Contamination

To remove foreground Milky Way stars from our JWST NGC 6822 source list we
examine Gaia Data Release 3 (DR3 Gaia Collaboration et al., 2021) for
foreground contamination. First, the Gaia catalogue is cleaned of sources with
poor astrometry and possible non-single objects within our JWST FoV, as
outlined by Fabricius et al. (2021). This involves keeping sources with:
RUWE$\leq$1.4, astrometric_excess_noise_sig$\leq$2.0,
visibility_periods_used$\geq$9 and ipd_gof_harmonic_amplitude$\leq$0.1. The
cleaned Gaia catalogue is matched to our NGC 6822 photometry, resulting in 656
positive matches within the main field. Sources that exhibit a significant
($5\sigma$) parallax or proper motion are considered to be foreground sources
and are thus removed from our catalogue. Due to the relative proximity of NGC
6822, we check that the proper motion of the sources do not deviate
significantly from the global proper motion of the galaxy, as outlined by
Dimitrova et al. (2021).

In total, we find that 179 sources exhibit proper motion above the threshold
with all but one also deviating significantly from that of the galaxy. We also
find that every source with significant parallax also exhibits proper motion.
This allows for 178 sources to be removed from the catalogue as foreground
contaminates. Despite NGC 6822’s proximity to the galactic plane, we see a low
number of foreground stars in our data set. Our detection routine is unable to
recover many of the bright foreground stars due to the saturation limits of
our data. Furthermore, _Gaia_ only detects the brightest IR sources in NGC
6822; this paired with the small FoV of our observations means that the number
of foreground contaminating stars in our catalogue is low, as expected.

##  4 Results and Discussion

###  4.1 Mosaic Images

The NIRCam prime mosaics shown in Figure 3 cover a FoV of $\sim$29.0 arcmin2,
whilst the MIRI mosaic covers a $\sim$14.5 arcmin2 FoV, with the NIRCam FoV
overlapping nearly the entirety of that of MIRI. These mosaics image NGC 6822,
located at a distance of 490 kpc, with resolutions from 0.037″ (0.087 pc) to
0.139″ (0.332 pc) in NIRCam, and from 0.268″ (0.638 pc) to 0.673″ (1.601 pc)
in MIRI. This provides an improvement over existing _Spitzer_ imaging by up to
a factor of 10.

The NIRCam field shows a smooth distribution of stars increasing in density
towards the centre of the FoV. Scanning by eye reveals an assortment of clear
extreme candidates with bright blue or red colours on a backdrop of many faint
stars. The background galaxies are evenly distributed across the image, with
some showing detailed spiral structures and others only visible in the longest
wavelengths. A dense globular cluster (Hubble VII) is visible in the centre
right of the image. The extent of the MIRI footprint is overlaid as a white
dotted line. The NIRCam data is devoid of all dust structure whereas the MIRI
data of the same region is completely dominated by complex diffuse emissions.
The centre of our FoV covers the young massive star forming region Spitzer I,
for which a detailed study of the young stellar objects has been conducted by
Lenkić et al. (2023).

Figure 3: JWST full-colour mosaics displaying the spatial coverage from both
instruments. Above shows MIRI coverage with F770W (blue), F1000W (green),
F1500W (yellow) and F2100W (red), image credited to ESA/Webb, NASA & CSA, M.
Meixner. Below shows the NIRCam coverage with F115W (blue), F200W (cyan),
F356W (yellow) and F444W (red) with the extent of the MIRI footprint marked
with the white dotted line. East is up and north is to the right.

###  4.2 Stellar Population Classification

This section presents JWST CMDs covering the galaxy within the full extent of
our survey. We select colour combinations that highlight significant
population separation and those which represent similar wavelength coverage as
_Spitzer_ filters used in the SAGE surveys (Meixner et al., 2006; Gordon et
al., 2011). We adapt classification boundaries from prior work (Blum et al.,
2006; Hirschauer et al., 2020) and investigate the location various stellar
populations occupy in different JWST colour combinations, which we anticipate
will be useful in future stellar surveys.

Figure 4 shows one NIRCam-only CMD (F115W$-$F200W vs. F200W) in contour and
Hess diagram format, one MIRI-only CMD (F770W$-$F1500W vs. F770W), and one
combined CMD (F444W$-$F770W vs. F770W) with the most identifiable populations
overlaid. The first CMD, with a filter combination most similar to the
($J-K_{s}$ vs. $K_{s}$) CMDs of previous NGC 6822 studies (e.g., Cioni &
Habing, 2005; Sibbons et al., 2012; Whitelock et al., 2013), was chosen as it
utilizes the most sensitive photometry and therefore reveals the faintest
populations. The diagram is shaped as a collection of sources that splits
vertically into two main fingers from the base, with the broadness of the base
likely being a product of greater scatter as the sensitivity limit of the
photometry is approached. The blue finger follows the Upper Main Sequence
(UMS), with more massive stars appearing higher up. The right-hand fork is
primarily the Red Giant Branch (RGB), with the Red Clump (RC) appearing as a
dense bulge at F200W$=$22.0 and the AGB bump (AGBb) embedded just above at
F200W$=$21.0. The vertical track seen above the RC is formed by red helium
burning (RHeB) stars evolving toward the AGB. The supergiant (SG) track splits
from the RGB below the Tip of the RGB (TRGB) and runs diagonally upward,
consisting of some of the brightest sources in the galaxy. Above the TRGB the
thermally pulsing AGB (TP-AGB) stars separate into oxygen-rich AGB (OAGB) and
carbon-rich AGB (CAGB). A fraction of the TP-AGB will likely be mid thermal
pulse and sit below the TRGB. Formal separation of these stars is difficult
photometrically but they make up only a small percentage ($<10\%$) of the
overall count (Boyer et al., 2015a).

Figure 4: Colour-magnitude diagrams over three filter combinations with broad
stellar classification tracks overlaid and labeled accordingly, point density
displayed as contours where appropriate: $\mathrm{F115W}-\mathrm{F200W}$ vs.
$\mathrm{F200W}$ (top), $\mathrm{F444W}-\mathrm{F770W}$ vs. $\mathrm{F770W}$
(lower left) $\mathrm{F770W}-\mathrm{F1500W}$ vs. $\mathrm{F770W}$ (lower
right). Upper right plot shows a second $\mathrm{F115W}-\mathrm{F200W}$ vs.
$\mathrm{F200W}$ CMD in Hess format.

####  4.2.1 Upper Main Sequence

The upper main sequence population is clearly visible in the top left panel of
Figure 4 as the prominent branch located at
$\mathrm{F115W}-\mathrm{F200W}<0.5$ and approaching
$\mathrm{F115W}-\mathrm{F200W}=0.0$. At $\mathrm{F200W}=25.0$ this branch
connects with the base of the RGB, though it is unclear if this constitutes
the Main Sequence Turn-Off (MSTO) for an aged population as the confusion
introduced into the photometry as it approaches the completeness limit merges
the populations together. An optical survey of NGC 6822 by Zhang et al. (2021)
isolated the UMS with ages $<$100 Myr and confirmed that the population
perfectly traced the HI gas distribution that lies orthogonal to the bulk of
the stellar component of the galaxy. Because they trace recent star formation,
these stars offer information about the underlying gas and how it evolves over
time.

UMS stars are generally very bright and have dispelled any nearby dust, they
possess spectral energy distributions (SEDs) peaking in blue wavelengths. As
such, they are detectable in the short NIRCam filters but become difficult to
detect at longer wavelengths.

####  4.2.2 Red Giant Branch

The RGB begins at $\mathrm{F200W}=25$ and $\mathrm{F115W}-\mathrm{F200W}=0.8$
in the top left panel of Figure 4 and extends vertically in a steep diagonal
towards the red. This sequence is formed by stars that have just left the MS
and have begun H-shell burning. In a single-aged population the MSTO will
appear as a tight track connecting the MS to the base of the RGB. The multi-
aged population of NGC 6822, a product of continuous star formation, elongates
the RGB and is consistent with an old population spanning $2-10$ Gyr.
Previously Zhang et al. (2021) isolated the brighter portion of this branch to
show that the old stars contribute to the galaxy’s eccentric elliptical
stellar component that twists radially and is perpendicular to the younger
stellar component.

The TRGB is well defined in the shorter wavelengths in Figure 4 but unresolved
in the longer MIRI filters. Our method of roughly calculating its position is
discussed in Section 4.3.

The positioning of the RGB on a given CMD is fairly independent of star
formation history (SFH) but there are two effects that cause it to spread in
colour space: Younger populations appear slightly red and older populations
appear more blue when considering a fixed value of metallicity. Whereas when
given a fixed population age with varying metallicity, more metal poor stars
appear bluer than more metal rich stars. This effect is known as the age-
metallicity degeneracy (Carrera et al., 2008) as for a given individual star,
it is difficult to determine with certainty if its position on the RGB is
caused by its age, metallicity or both. The width of the RGB in our CMDs
exceeds the expected characteristic scatter caused by uncertainty in the
photometry and therefore is likely caused by a broad range of ages and
metallicities across the galaxy. Detailed surveys of the metallicity gradient
across the galaxy have been conducted by Patrick et al. (2015).

####  4.2.3 Red Clump

As old or intermediate-aged stars undergo a helium flash, they leave the RGB
and collect in the RC. The RC structure is very dense in our CMDs, sitting
just left of the RGB at $\mathrm{F200W}\sim 22.2$. In our shortest-wavelength
filters we resolve sources three magnitudes below the RC, but decreased depth
of photometry cuts off its detection above 4 $\mu$m, as seen in Figure 4.

The RC is a useful standard candle and has been used to measure SFH in NGC
6822 in the past (Wyder, 2001) by comparing age-sensitive RGB with the age-
insensitive RC. The increased sensitivity of our catalogue will allow for more
finely sampled calculations of the SFH within the inner regions of the galaxy.
Additionally, differential reddening in NGC 6822 introduces a spread in the
photometry of the theoretically tight RC. This effect can be used to build an
extinction map of the galaxy (Wyder, 2001). Such an exercise is beyond the
scope of this study, however it will be addressed in a forthcoming paper.

####  4.2.4 Red Helium Burning Sequence

Above the RC extends a vertical sequence known as the red helium-burning
(RHeB) stars or the vertical red clump (VRC). The RHeB track is formed as
young stars collect at the right side of the “blue loop". In older stars the
distance covered during the blue loop is much smaller and they appear at the
fainter end of this population. The younger stars appear brighter as the
extension of the blue loop increases and sit at the upper end of the RHeB
track. As the height of this sequence is directly indicative of the age of the
population, it can be used to measure the SFH within the galaxy (Dohm-Palmer
et al., 1997).

####  4.2.5 AGB Bump

The AGBb is a population of rarely-observed stars that emerges as evolving
early AGB stars stall momentarily as their H-burning shells are extinguished
by the expansion of their convective layers. Observing this feature is
difficult, as it requires a large number of sources and may be quickly
obscured by even small photometric errors. Yet, it is clearly visible in top
left plot of Figure 4 embedded in the RGB at $\mathrm{F200W}=21$. The age and
metallicity of the stars influences its positioning on the CMD and as such,
along with its younger and more populated counterpart, the RGB bump (RGBb),
the AGBb can be used to gain some insight into the SFH of the galaxy (Ferraro,
1992). Unlike the AGBb which always appears above the RC, the RGBb appears
below or is overlaid onto the RC (Gallart, 1998); deeper analysis of our data
is be required to isolate it. Although the AGBb is visible in optical data in
NGC 6822 (Tantalo et al., 2022), this often neglected population is a useful
mark to constrain evolutionary tracks.

####  4.2.6 Supergiants

At $\mathrm{F200W}=19$, the SG branch forks blueward from the RGB and extends
steeply to the saturation limit of our data. The sequence is clearly visible
in the upper-right plot of Figure 4, although the source density drops at the
brightest end. The existence of a SG population in the galaxy has been shown
by Whitelock et al. (2013), Hirschauer et al. (2020), and Dimitrova et al.
(2021), and they follow the structure of the central bar. This result was
expected as SG stars are young and massive, so have not had sufficient time to
wander far from the star forming sites in the centre of the galaxy.
Incorporating NIRCam and MIRI photometry, SG stars are separated effectively
with $\mathrm{F444W}-\mathrm{F770W}$ vs. $\mathrm{F770W}$ as seen in the
lower-left panel of Figure 4 where they form a distinct blue “horn” in the
CMD.

####  4.2.7 Asymptotic Giant Branch

Formal separation of the evolved populations is outwith the scope of this
overview but will be included in the following papers in this survey. Here we
present initial cuts to determine the general positions of the SG, OAGB, and
CAGB. To inspect the locations of these evolved populations in colour space,
we show in the first panel of Figure 5 a zoom-in of the F115W$-$F200W vs.
F200W CMD, where they appear to follow diagonal sequences. Above the TRGB at
$\mathrm{F200W}=17.5$, a small gap separates the TP-AGB stars from the RGB.
The two main groups in this classification are separated by the chemical
makeup of their photospheres. Free carbon and oxygen are bound in very stable
CO molecules. The overabundance of one of the two components is then left
unbound in the photosphere and will form the basic ingredient for dust grain
formation once it is lifted into the circumstellar dust shell of the star.
AGBs with a $C/O$ ratio $>1$ are defined to be C-rich and those with $C/O<1$
are O-rich. The dust species formed are dictated by this chemical difference,
with CAGBs forming carbonaceous dust grains and OAGBs forming sulphates,
emissions from which can be photometrically separated (Potter et al., 2004).

Figure 5: Evolved population separation from near-IR to mid-IR. The SGs in
green, OAGBs in blue, and CAGBs in red are defined in the first figure showing
$\mathrm{F115W}-\mathrm{F200W}$ vs. $\mathrm{F200W}$. The upper plot also
shows classified OAGB (blue) and CAGBs (red) by Sibbons et al. (2012) (stars)
and Hirschauer et al. (2020) (triangles). Boundaries adopted to separate AGB
species and SGs are drawn in solid lines. Stars classified in above boundaries
are drawn in the second CMD plot $\mathrm{F115W}--\mathrm{F770W}\ vs.\
\mathrm{F770W}$.

We separate the CAGB and OAGB sequences with a diagonal line above the TRGB at
$\mathrm{F115W}-\mathrm{F200W}\geq 1.5$. Historically the AGBs in NGC 6822
have been split with a vertical line in the near-IR (see e.g., Cioni & Habing,
2005; Sibbons et al., 2012). Combining mid-IR Spitzer (where the molecular
emissions separate the AGBs more effectively) and near-IR United Kingdom
Infrared Telescope (UKIRT) data for broader baseline photometry, Hirschauer et
al. (2020) developed a novel statistical approach to separate them with more
complex colour cut boundaries. We cross-match our catalogue with Sibbons et
al. (2012) and Hirschauer et al. (2020) to identify where these populations
lie on our JWST CMDs. We show this comparison in the first panel of Figure 5,
where blue data points indicate OAGBs and red data points indicate CAGBs. The
stars correspond to AGB identifications from Sibbons et al. (2012) and
triangles correspond to those of Hirschauer et al. (2020). We find that the
classification of sources as CAGB stars by both of these previous studies are
broadly consistent with the colour space that they occupy in our JWST CMDs
(red region). A handful of sources ($\sim$10) from Hirschauer et al. (2020)
are classified as CAGB, but appear to fall within the region we define as
corresponding to OAGB stars (blue region).

Separating the OAGBs and SGs is more involved due to the low point density in
our limited CMD. Here we adopt a diagonal line above the TRGB at
$\mathrm{F115W}-\mathrm{F200W}=1.3$ and draw it down the edge of the RGB with
the increased sensitivity of our photometry; this region (denoted in green) is
where we classify objects as SGs. In the LMC, the $J-K_{s}$ vs. $K_{s}$ CMD of
Blum et al. (2006) had a similar SG feature. A significant fraction of the
previously identified OAGB stars from Sibbons et al. (2012) and Hirschauer et
al. (2020) are identified as such with our JWST data. However, a larger number
of these (several 10s) appear to fall within the space we define as
corresponding to SGs. More in depth follow-up studies will need to be
conducted to formalise this separation. Finally, there are a few sources that
were previously classified as OAGB or CAGB that fall along the RGB; these are
likely TP-AGBs that are mid-pulse.

A caveat of this comparison is that the improved resolution of JWST resolves
previous bright _Spitzer_ sources into multiple fainter stars. These would
appear on the CMD in the first panel of Figure 5 to the right of the RGB and
below the space occupied by CAGBs. These sources (roughly half from the
catalogues of Sibbons et al., 2012; Hirschauer et al., 2020) have however been
omitted from the figure for clarity.

While the colour cuts we have applied here effectively distinguish the evolved
stellar populations, we caution that extinction imposes limitations for the
dustiest sources. We expect that the for most dust enshrouded AGBs, extinction
can cause the star to dip below horizontal colour cut we have applied above
the TRGB to identify the evolved stars. As such, these sources will be
excluded from our CAGB classification and spectroscopic follow-up studies will
be required to distinguish them from YSOs. Additionally, although it is
normally assumed that everything to the right of the diagonal cut we have
defined at F115W$-$F200W$=1.3$ (red line) is a CAGB (Boyer et al., 2015b), in
cases where OAGBs produce large quantities of silicate dust, they will also
move rightward and occupy a similar colour space (Aringer et al., 2016).
Separating the dustiest OAGB and CAGB stars will also require spectroscopic
observations.

Using the classification schemes defined above, we overlay the sources onto
F115W$-$F770W vs. F770W in the second panel of Figure 5. The SGs, OAGBs, and
CAGBs are still visible as three distinct populations, although increasing
absorption effects caused by dust in the longer wavelengths begin to increase
the scatter of the populations. This colour combination separates the CAGBs
from the OAGBs, with the bulk of the two populations being separated with
nearly one magnitude of colour space between them. This combination holds
close comparison with the $J-[8.0]$ CMD of the LMC from Blum et al. (2006),
where the SGs and CAGBs fork above the bulk of OAGBs; with NIRCam- and MIRI-
equivalent filters we see the exact same morphology.

Figure 6: Colour-magnitude diagram with MIRI $\mathrm{F770W}--\mathrm{2100W}\
vs.\ \mathrm{F2100W}$.

Long-wavelength MIRI photometry is key to chemically separating the most dust-
enshrouded sources in our catalogue. The bottom panel of Figure 6 shows the
distribution of sources in $\mathrm{F770W}-\mathrm{F2100W}$ vs. F2100W, where
the source density is very low due to the significant dust presence and rarity
of sources which are bright at these wavelengths. The CMD splits into three
distinct groups stretching across six magnitudes in colour space. This
combination has shown to be analogous to _Spitzer_ $[8.0]-[24]$ vs. $[24]$ in
work by Jones et al. (2017), which allows us to draw comparison to SAGE work
on the LMC where Srinivasan et al. (2009) demonstrated a triple forking
sequence. In their work, CAGB (and extreme-AGBs) lie on the most-luminous and
blue finger of the fork, whereas the OAGBs are fainter and more red but
bifurcate into two fingers above $[8.0]-[24]>1$. Later, Sargent et al. (2011),
using the Grid of Red supergiant and Asymptotic giant branch star ModelS
(GRAMS) models, showed that the central fork is occupied by the OAGBs
exhibiting the highest mass loss as well as some SG stars. Our CMD may be
showing the same feature, but, limited by the sensitivity of F2100W, we only
see its brightest portions. The small number of sources will require a more
detailed investigation than the scope of this work.

####  4.2.8 Young Stellar Objects

In all filter combinations shown in Figure 4, the YSOs inhabit the red area to
the right of the RGB below the CAGB sequence. These dusty objects have
characterisable SEDs and Lenkić et al. (2023) identifies 129 YSOs in the
Spitzer I region. This area in the CMD is also inhabited by any contaminating
background galaxies that remain after the cuts described in Section 3.3 have
been applied, but their SED shapes are distinct from that of a YSO and are
easily removed from the catalogue.

###  4.3 Luminosity Functions

Figure 7: Luminosity functions for the F115W (upper), F356W (middle) and F770W
(bottom) filters. Log scaled distributions are drawn in black and linear
scaled distributions in filled grey. Bin sizes have been scaled optimally for
the number of sources detected in each band. The inferred completeness
estimates are denoted with a solid purple line and the calculated TRGB is
denoted in a dashed line. In F115W the catalogue is cropped with
F115W-F200W>0.5 to remove the UMS and highlight the features within the RGB,
this is plotted in the solid red line.

In Figure 7 we present three representative luminosity functions from our full
band merged catalogue. The logarithmic scaled distribution is plotted in black
and its linearly scaled version is plotted in filled gray. The optimal bin
width is calculated for the number of sources present in each case using
Knuth’s rule (Knuth, 2006). We crudely estimate the completeness of our sample
in each JWST filter by identifying the location of the turnover of the
luminosity functions at the faint end of the magnitude distribution for each
band.

We measure the TRGB for every filter in our catalogue sensitive enough to
detect it. The TRGB is an important feature from an astrophysical perspective
as it is a well constrained standard-candle, depending only weakly on age and
metallicity (Cioni et al., 2000). It represents the final stage of the RGB for
a low mass star before its eventual evolution onto the AGB. This prominent
feature is used to separate the RGB stars from the dust producing TP-AGB stars
as the majority ($\sim$90$\%$) are situated above the TRGB (Boyer et al.,
2015a). Due to molecular emissions in the photosphere of the RGB stars, we
expect the TRGB to not be flat but to slope upwards in the IR (e.g., Cerny et
al., 2020; Durbin et al., 2020). This results in a less steep drop in a
luminosity function than would be expected in the optical, consequently, the
TRGB positions measured here are only estimations. To measure the position of
the TRGB, we randomly sample a subset of magnitudes from the catalogue and
smooth the distribution with a kernel density estimate. The first order
derivative of the smoothed distribution is calculated with a Savitizky-Golay
filter and the TRGB is located at the point of steepest decline, seen in the
differential as a sharp trough. This process is repeated thousands of times
with different samples of the catalogue and the results averaged to determine
the TRGB. The SED of an RGB star steadily falls with increasing wavelength in
the IR and the TRGB is faint in MIRI. We flag F115W TRGB sources, to ensure
that the TRGB feature is visible above the noise of the completeness turnover
in the mid-IR luminosity functions. We find that the TRGB is measurable up to
and including F1000W. Table 4 lists the number of sources detected at each
wavelength, the corresponding faint and bright source limits for that filter,
and where appropriate, the magnitude of the TRGB.

In F115W we are roughly complete to $\mathrm{F115W}=25.78$, around $\sim$2.8
magnitudes below the RC population visible at $\mathrm{F115W}\sim 23.0$ mag.
The RC is fairly independent of stellar age and metallicity, and as such they
are known to be reasonable standard candles, occupying a tight region in CMD
space, deviations from which can be used to derive differential reddening
effects within the galaxy. Blue sources on the UMS contaminate the distinctive
features in the post-MS luminosity function. Thus we construct a second
luminosity function for this filter consisting solely of red objects with
$\mathrm{F115W}-\mathrm{F200W}>0.5$. In doing so a new structure is revealed;
a shallower slope on the faint side of the RC emerges. The red luminosity
function also shows the prominent AGBb (Ferraro et al., 1999) at
$\mathrm{F115W}=22.0$ and the TRGB at $\mathrm{F115W}=19.06$. The prominent
nature of the position of the TRGB will allow us to constrain the distance to
NGC 6822 and improve the understanding of the sloped relation visible in the
IR. Above this, we begin to see the AGB form a shoulder to
$\mathrm{F115W}=17.8$. Saturation affects the completeness of our catalogue at
around $\mathrm{F115W}=16.0$. This low saturation limit will cause our sample
to be less sensitive to the brightest sources detected in _JHK_ s data in
previous surveys.

In F356W the bright central peak in the luminosity function at
$\mathrm{F356W}=22.2$ corresponds to the RC. The distribution begins to rise
with the increased number of sources at the lower end of the RGB, however
sensitivity limits take effect at this point, and as such we place the faint
limit at the peak of this shoulder $\mathrm{F356W}=23.27$. Above the RC, the
small peak of the AGBb is at $\mathrm{F356W}=21$, from which the smooth
decline of the RGB turns over at the TRGB at $\mathrm{F356W}=17.5$. The
distribution of evolved stars is in steady decline until saturation limits the
detections from $\mathrm{F356W}\sim 14.5$.

Finally, we present F770W which is limited to $\mathrm{F770W}=19.35$, below
the TRGB at $\mathrm{F770W}\sim 17.8$. The position of the TRGB is uncertain
as it is highly affected by the bin sizes due to the low source count; later
work will formalise this value. Above the TRGB the AGB population forms a
smooth flat shoulder until bright dusty sources peak the distribution just
below the saturation limit at $\mathrm{F770W}=12.2$.

Overall we see an increase in the lower sensitivity limit as the wavelength of
the filter increases and an increase in the upper sensitivity limit, but the
range between these limits shrinks. This effect, paired with the low
luminosity of the Rayleigh-Jeans tail at these longer wavelengths, causes the
source count to drop significantly.

Filter | Source Count | Faint Limit | Bright Limit | TRGB (error)
---|---|---|---|---
|  | [VegaMag] | [VegaMag] | [VegaMag]
F115W | 765756 | 25.78 | 15.3 | 19.06(05)
F200W | 539361 | 24.70 | 14.9 | 17.85(13)
F356W | 175346 | 23.27 | 14.5 | 17.74(30)
F444W | 147328 | 23.06 | 14.0 | 17.65(12)
F770W | 7212 | 19.25 | 12.2 | 17.81(04)
F1000W | 4782 | 19.98 | 11.5 | 17.48(21)
F1500W | 1352 | 16.06 | 10.0 | -
F2100W | 269 | 14.43 | 10.0 | -
Table 4: Source count per filter and sensitivity limits estimated by locating
the turnover at the lower end of the luminosity functions, and upper limits
placed around the brightest collection of sources. The TRGB is calculated by
finding the point of steepest decline in the luminosity function. All
magnitudes are given in the Vega system.

###  4.4 Parallel Field Photometry

Figure 8: Colour-Magnitude Diagrams $\mathrm{F115W}-\mathrm{F200W}$ vs.
$\mathrm{F200W}$ in Hess format for the parallel imaging fields. Parallel
$\mathrm{B}$ (left) is the NIRCam module B, appearing closest to the centre of
NGC 6822, containing Hubble $\mathrm{IV}$ the star forming region. Parallel
$\mathrm{A}$ (right) is the NIRCam module A, the furthest field away from the
centre of the galaxy.

The spatial coverage of the two parallel fields is shown in Figure 1. NIRcam
parallel $\mathrm{B}$ contains the localised star forming region Hubble
$\mathrm{IV}$ and NIRCam parallel $\mathrm{A}$ contains no known areas of
active star formation but is contaminated the PSF spikes of a bright off-field
foreground star. We conduct photometry for the two NIRCam parallel imaging
fields and plot the $\mathrm{F115W}-\mathrm{F200W}$ vs. $\mathrm{F200W}$ CMD
in Figure 8. starbugii photometric parameters listed in appendix Table 7 are
kept the same for consistency across fields.

Both parallels $\mathrm{A}$ and $\mathrm{B}$ have source detections
approximately 0.5 magnitudes deeper than the main field, likely due to the
decreased crowding in the regions. The deeper detection and lower photometric
scattering allows us to detect the base of the RGB. This will enable us to
constrain the population age range accurately in future work.

NIRCam parallel $\mathrm{B}$ contains young UMS stars in a tight track on the
left of the CMD. The RGB turns off and extends upwards but the TRGB is not
well defined. The RC sits prominently out of the RGB to the left and the
intermediate-age RHeB track extends vertically from it. A faint track of SG
stars splits from the RGB at F200W$\sim$19 and is well separated from a small
collection of AGB stars above the TRGB calculated in Table 4.

NIRCam parallel $\mathrm{A}$ does not contain many UMS stars beyond a short
scattered track above the MSTO. Similarly the RHeB stars are only marginally
present and no obvious SG sequence is seen. The relative lack of very young
stars is due to there being no active star-forming region in the FoV.

##  5 Conclusion and Summary

We observed the central stellar bar of NGC 6822, utilizing the spatial
resolution and sensitivity afforded by JWST NIRCam and MIRI to characterise
the IR stellar populations of this isolated metal-poor dwarf galaxy. Our
observations were designed to image the most dust enshrouded stars from
evolved TP-AGBs to young YSOs embedded within the super star cluster Spitzer
I.

  * $\blacksquare$

We produce initial catalogues with starbugii and estimate the point-source
sensitivities for these observations at 25.78 – 14.0 for the NIRCam filters,
and 19.25 – 10.0 for the MIRI filters. In both cases, the brightest stars in
NGC 6822 are saturated.

  * $\blacksquare$

We estimate positions of the TRGB in NIRCam and MIRI filters up to and
including F1000W. The falling SED of RGB stars in IR wavelengths cause the
stars to be too faint to detect in our F1500W and F2100W data.

  * $\blacksquare$

We show CMDs of varying colour combinations, using JWST equivalents of UKIRT
_JHK_ s and Spitzer filter combinations from previous surveys of NGC 6822 and
the Magellanic Clouds to guide the placement of source classifications when
pairing NIRCam and MIRI data.

  * $\blacksquare$

We detect a population of carbon- and oxygen rich AGB stars and matching
independently classified IR catalogues to determine the boundary between them.
They are distinct from one another and separate from a younger SG population
also detected.

  * $\blacksquare$

We observe for the first time in the IR, the RC and RHeB populations as well
as the illusive and short live AGBb phase and demonstrate the position they
inhabit on several CMD colour combinations.

  * $\blacksquare$

Using parallel near-IR imaging of fields outside the central stellar bar of
NGC 6822, we show that the young populations are absent or heavily reduced in
number, owing to the probable lack of star formation in this area of the
galaxy.

Facilities: JWST (NIRCam & MIRI) - James Webb Space Telescope.

Software: jhat (Rest, 2023), image1overf.py (Willott, 2022), astropy (Astropy
Collaboration et al., 2013), starbug ii (Nally & Jones, 2022) , and topcat
(Taylor, 2005).

## Acknowledgements

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 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 program
#1234. CN acknowledge the support of an STFC studentship. OCJ has received
funding from an STFC Webb fellowship. MM and NH acknowledge support through
NASA/JWST grant 80NSSC22K0025 and MM and LL acknowledge support from the NSF
through grant 2054178. MM and NH acknowledge that a portion of their research
was carried out at the Jet Propulsion Laboratory, California Institute of
Technology, under a contract with the National Aeronautics and Space
Administration (80NM0018D0004). PJK acknowledge support from Science
Foundation Ireland/Irish Research Council Pathway programme under Grant Number
21/PATH-S/9360. ASH is supported in part by an STScI Postdoctoral Fellowship.

## Data availability

The data used in this study may be obtained from the Mikulski Archive for
Space Telescopes (MAST; https://mast.stsci.edu/) and are associated with
program #1234.

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##  Appendix A Observational and Photometric Tables

Filter | Field | Readout Pattern | Groups/Int. | Int./Exp. | Dithers | Total Exp. Time
---|---|---|---|---|---|---
|  |  |  |  |  | [sec]
F115W | NIRCam Prime | bright2 | 7 | 1 | 12 | 1803.777
F200W | NIRCam Prime | bright2 | 7 | 1 | 12 | 1803.777
F356W | NIRCam Prime | bright2 | 7 | 1 | 12 | 1803.777
F444W | NIRCam Prime | bright2 | 7 | 1 | 12 | 1803.777
F140M | NIRCam Parallel | shallow4 | 8 | 1 | 4 | 1674.936
F335M | NIRCam Parallel | shallow4 | 8 | 1 | 4 | 1674.936
F115W | NIRCam Parallel | shallow2 | 3 | 1 | 4 | 515.365
F150W | NIRCam Parallel | shallow2 | 4 | 1 | 4 | 730.100
F200W | NIRCam Parallel | shallow4 | 4 | 1 | 4 | 815.995
F277W | NIRCam Parallel | shallow2 | 4 | 1 | 4 | 730.100
F356W | NIRCam Parallel | shallow2 | 3 | 1 | 4 | 515.365
F444W | NIRCam Parallel | shallow4 | 4 | 1 | 4 | 815.995
Table 5: Observing Parameters for the NIRCam Prime and Parallel Imaging. Filter | Field | Readout Pattern | Groups/Int. | Int./Exp. | Dithers | Total Exp. Time
---|---|---|---|---|---|---
|  |  |  |  |  | [sec]
F770W | MIRI Prime | fastr1 | 52 | 1 | 4 | 577.208
F1000W | MIRI Prime | fastr1 | 36 | 2 | 4 | 810.312
F1500W | MIRI Prime | fastr1 | 15 | 8 | 4 | 1409.72
F2100W | MIRI Prime | fastr1 | 20 | 9 | 4 | 2086.83
F1000W | MIRI Parallel | slowr1 | 5 | 1 | 12 | 1433.395
F1500W | MIRI Parallel | slowr1 | 5 | 1 | 12 | 1433.395
Table 6: Observing Parameters for the MIRI Prime and Parallel Imaging. Parameter | F115W | F200W | F356W | F444W | F770W | F1000W | F1500W | F2100W
---|---|---|---|---|---|---|---|---
SIGSRC | 5.0 | 5.0 | 5.0 | 5.0 | 3.0 | 3.0 | 3.0 | 3.0
SIGSKY | 2.0 | 2.0 | 2.0 | 2.0 | 1.5 | 1.5 | 1.3 | 1.3
RICKER_R | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 2.0 | 5.0 | 5.0
SHARP_LO | 0.4 | 0.4 | 0.55 | 0.4 | 0.3 | 0.25 | 0.2 | 0.2
SHARP_HI | 1.1 | 0.9 | 0.9 | 0.85 | 0.9 | 0.8 | 0.8 | 0.7
ROUND_LO/HI | $\pm 1.5$ | $\pm 1$ | $\pm 1$ | $\pm 1$ | $\pm 1$ | $\pm 0.8$ | $\pm 0.8$ | $\pm 0.8$
APPHOT_R | 1.5 | 1.5 | 1.5 | 1.5 | 2.5 | 2.5 | 3.0 | 3.0
SKY_RIN | 3.0 | 3.0 | 3.0 | 3.0 | 4.0 | 4.0 | 4.5 | 4.5
SKY_ROUT | 4.5 | 4.5 | 4.5 | 4.5 | 5.5 | 5.5 | 6.0 | 6.0
BOX_SIZE | 15 | 15 | 5 | 5 | 2 | 5 | 5 | 8
CRIT_SEP | 5 | 6 | 8 | 8 | 8 | 8 | 8 | 8
MATCH_THRESH | 0.1 | 0.1 | 0.1 | 0.1 | 0.15 | 0.2 | 0.2 | 0.2
NEXP_THRESH | 2 | 2 | 2 | 2 | 3 | 3 | 3 | 3
Table 7: starbugii parameters used for all photometry.


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