# JWST reveals widespread CO ice and gas absorption in the Galactic Center
cloud G0.253+0.016

Adam Ginsburg Department of Astronomy, University of Florida, P.O. Box 112055,
Gainesville, FL, USA  Ashley T. Barnes European Southern Observatory (ESO),
Karl-Schwarzschild-Straße 2, 85748 Garching, Germany  Cara D. Battersby
University of Connecticut, Department of Physics, 196A Auditorium Road, Unit
3046, Storrs, CT 06269  Alyssa Bulatek Department of Astronomy, University of
Florida, P.O. Box 112055, Gainesville, FL, USA  Savannah Gramze Department of
Astronomy, University of Florida, P.O. Box 112055, Gainesville, FL, USA
Jonathan D. Henshaw Astrophysics Research Institute, Liverpool John Moores
University, 146 Brownlow Hill, Liverpool L3 5RF, UK  Max-Planck-Institut für
Astronomie, Königstuhl 17, D-69117 Heidelberg, Germany  Desmond Jeff
Department of Astronomy, University of Florida, P.O. Box 112055, Gainesville,
FL, USA  Xing Lu Shanghai Astronomical Observatory, Chinese Academy of
Sciences, 80 Nandan Road, Shanghai 200030, P. R. China  E. A. C. Mills
Department of Physics and Astronomy, University of Kansas, 1251 Wescoe Hall
Dr., Lawrence, KS 66045, USA  Daniel L. Walker UK ALMA Regional Centre Node,
Jodrell Bank Centre for Astrophysics, The University of Manchester, Manchester
M13 9PL, UK

(September 2023)

###### Abstract

We report JWST NIRCam observations of G0.253+0.016, the molecular cloud in the
Central Molecular Zone known as “The Brick,” with the F182M, F187N, F212N,
F410M, F405N, and F466N filters. We catalog 56,146 stars detected in all six
filters using the crowdsource package. Stars within and behind The Brick
exhibit prodigious absorption in the F466N filter that is produced by a
combination of CO ice and gas. In support of this conclusion, and as a general
resource, we present models of CO gas and ice and CO2 ice in the F466N, F470N,
and F410M filters. Both CO gas and ice contribute to the observed stellar
colors. We show, however, that CO gas does not absorb the Pf$\beta$ and
Hu$\epsilon$ lines in F466N, but that these lines show excess absorption,
indicating that CO ice is present and contributes to observed F466N
absorption. The most strongly absorbed stars in F466N are extincted by $\sim
2$ magnitudes, corresponding to $>80\%$ flux loss. This high observed
absorption requires very high column densities of CO, and thus a total CO
column that is in tension with standard CO abundance and/or gas-to-dust
ratios. This result suggests the CO/H2 ratio and dust-to-gas ratio are greater
in the Galactic Center than the Galactic disk. Ice and/or gas absorption is
observed even in the cloud outskirts, implying that additional caution is
needed when interpreting stellar photometry in filters that overlap with ice
bands throughout galactic centers.

##  1 Introduction

G0.253+0.016, AKA “The Brick”, is among the best-studied infrared dark clouds
in the Galaxy (Lis et al., 1991; Lis & Carlstrom, 1994; Lis et al., 1994; Lis
& Menten, 1998; Lis et al., 2001; Longmore et al., 2012; Kauffmann et al.,
2013; Rodríguez & Zapata, 2013; Clark et al., 2013; Rathborne et al., 2014a,
b, 2015; Johnston et al., 2014; Bally et al., 2014; Pillai et al., 2015;
Federrath et al., 2016; Marsh et al., 2016; Walker et al., 2016; Henshaw et
al., 2019, 2022; Petkova et al., 2023). It is well-known for being dense and
turbulent (Clark et al., 2013; Rathborne et al., 2015; Federrath et al., 2016;
Mills et al., 2018; Henshaw et al., 2019, 2020) while exhibiting few signs of
star formation, much less than is typical for such a massive cloud (Longmore
et al., 2012; Rodríguez & Zapata, 2013; Mills et al., 2015; Walker et al.,
2016, 2021). Several explanations have been offered for its relatively poor
star formation: that it is young (Kruijssen et al., 2015; Henshaw et al.,
2016), that it is highly turbulent (Federrath et al., 2016), that it is
supported by magnetic fields (Pillai et al., 2015), and that it is many clouds
along the line of sight (Henshaw et al., 2019, 2022). Each of these
explanations is likely to play some role in the cloud’s state and evolution.

Gas in the Galactic Center is notably different from gas seen elsewhere in our
Galaxy. It is richer in complex molecules (Jones et al., 2012) and warmer (Ao
et al., 2013; Ginsburg et al., 2016; Krieger et al., 2017). Despite high gas
temperatures, the dust in the CMZ is not terribly warm (Tang et al., 2021), so
ice can accumulate on dust grains. Ice has long been seen in Galactic Center
mid-infrared spectra (Lutz et al., 1996; Chiar et al., 2000; Moneti et al.,
2001), as has CO gas. Toward Sgr A*, ice comprises a minority ($<10\%$) of the
CO, which is dominated instead by gas, as expected given the high gas
temperatures and extreme velocity dispersion of gas in the inner parsec
(Moneti et al., 2001; Moultaka et al., 2009). Beyond the inner parsec, though,
the ice properties of the Galactic Center are little explored. A handful of
Infrared Space Observatory (ISO) spectra were taken toward various positions,
revealing both CO2 and CO ice features, but little has been written about
them. An et al. (2011) and Jang et al. (2022) used Spitzer IRS spectra to show
that CO2 ice is common toward massive young stellar objects (MYSOs) in the GC,
and that CO2 is present in both gas and ice phases.

More generally, ice is observed throughout the molecular interstellar medium
(Boogert et al., 2015). However, ice is much more poorly studied than gas in
the interstellar medium because observable ice features occur only in the
infrared, either in narrow, difficult-to-observe bands from the ground (e.g.
Günay et al., 2020, 2022), or in bands observable only from from space. The
majority of published ice studies use spectroscopy, not photometry, in large
part because the effects of ice on broadband filters (e.g., Spitzer’s IRAC)
are usually small. The wide range of medium- and narrow-band filters on JWST
NIRCam change the state of the field, enabling extensive broad-field ice study
through photometry.

We present JWST observations in narrow-band filters toward The Brick,
highlighting the first striking result that CO ice is widespread. In Section
3, we describe the data processing and catalog creation. Section 4 describes
the measurements of both star colors (§4.1) and diffuse gas emission (§4.2),
then describes models of both CO gas (§4.3) and ice (§4.4) absorption that
explain some of the observed colors. We briefly discuss these results in
Section 5 and then conclude in Section 6. All of the analysis tools, including
the notebooks used to make the figures in this document, are made available
through a GitHub repository111https://github.com/keflavich/brick-jwst-2221/;
DOI: 10.5281/zenodo.8313307.

##  2 Observations

Observations were taken on August 28, 2022 as part of JWST program 2221 in
visit 001. The data presented in this paper were obtained from the Mikulski
Archive for Space Telescopes (MAST) at the Space Telescope Science Institute
(STScI). The specific observations analyzed can be accessed via
https://doi.org/10.17909/2ffq-e139 (catalog DOI 10.17909/2ffq-e139). This
program consists of two observations focused on The Brick, with coordinated
parallel observations performed toward Central Molecular Zone Cloud C. We
present only the Brick NIRCam observations in this work; the MIRI observations
of The Brick and NIRCam and MIRI observations of Cloud C will be presented in
future works. We obtained images in six filters listed in Table 1. We observed
in narrow-band filters in order to measure the extended line emission from
hydrogen recombination lines (Pa$\alpha$, Br$\alpha$, Pf$\beta$) and to search
for outflows (H2 in F212N) and hot CO emission from disks (F466N). The GTO
program 1182 has observed approximately the same field in broad-band filters.

Figure 1: The full-field star-subtracted image as described in §3.5. This
image captures extended recombination line emission from Pf$\beta$ and
Hu$\epsilon$ in F466N (466m410, continuum-subtracted F466N, is shown in red)
and Br$\alpha$ in F405N (405m410. continuum-subtracted F405N, is shown in
blue), highlighting The Brick as the dark cloud spanning the image. The green
channel is the sum of the red and blue channels and therefore adds no
information. Most of the extended emission is approximately white because both
the F466N and F405N filters contain recombination lines
(Pf$\beta$+Hu$\epsilon$ and Br$\alpha$, respectively). The color is more red
when dust extinction is the dominant absorption effect and more blue when CO
absorption is dominant (see §4.2), but the colors should not be interpreted
quantitatively. Note that significant artistic license has been taken to fill
in regions where star PSFs have made pixel fluxes unrecoverable; the image
represents the overall structure of the cloud well, but many small-scale
features are artifacts of the star subtraction. Declination is on the X-axis,
contrary to convention. A full resolution version is available online (which
we hope to make available through the journal; for now use
https://www.dropbox.com/scl/fi/39cfq8yr40460qaoy1wlf/BrickJWST_merged_longwave_narrowband_lighter.png?rlkey=lusbv81fsr9rvupt99zqmvpqj&dl=0).

In the NIRCam data we present, each image is comprised of 24 exposures taken
in the 6-TIGHT FULLBOX mosaic strategy,222https://jwst-docs.stsci.edu/jwst-
near-infrared-camera/nircam-operations/nircam-dithers-and-mosaics/nircam-
primary-dithers with six independent positions and four subpixel dithers per
position. Frames were read out in BRIGHT-2 mode with 2 groups per integration
for a total exposure time of 1031 seconds.333https://jwst-docs.stsci.edu/jwst-
near-infrared-camera/nircam-instrumentation/nircam-detector-overview/nircam-
detector-readout-patterns.

##  3 Data processing

We downloaded the data from the MAST archive using astroquery (Ginsburg et
al., 2019; Brasseur et al., 2020). We reprocessed data starting from L2
products, i.e., the cal files, which include 24 individual flux-calibrated
frames for each filter.

Our reduction code is provided on GitHub444https://github.com/keflavich/brick-
jwst-2221/releases/tag/resubmission_20230903; DOI: 10.5281/zenodo.8313307.

###  3.1 Frame matching astrometry

Images were processed with a slightly modified version of the JWST pipeline
based on version 1.11.1 (Bushouse et al., 2023). The tweakreg command was run
on long-wavelength NIRCam data using the VVV DR2 catalog (Saito et al., 2012)
as an astrometric reference instead of the Gaia catalog (there were too few
stars detected in common by both Gaia and JWST, and most were saturated). We
then created a reference catalog based on the F405N catalog, which had fewer
saturated bright stars than F410M and therefore more good associations with
the ground-based NIR data. In the make_reftable.py script, we cut the F405N
catalog based on crowdsource quality flags (qf$>0.95$, spread $<0.25$, frac
$>0.9$). This reference catalog was then used as the input to tweakreg for the
other filters. We found that the tweakreg pipeline did not adequately correct
the image registration to the absolute coordinates we provided, so we manually
cross-matched the catalogs and computed shifts using the realign_to_catalog
and merge_a_to_b functions in align_to_catalogs.py.

###  3.2 1/f noise removal

The narrow-band filters, particularly F187N, F212N, and F466N, exhibited
significant ‘streaking’ noise that is strongly evident in the low-signal
regions of the image, i.e., the majority of the molecular cloud. This
streaking was caused by 1/f noise in the detectors (STScI helpdesk ticket
INC0181624). As a first pre-processing step, we performed ‘destreaking’ on
each detector following a method suggested by Massimo Robberto (priv. comm.),
in which:

  1. 1.

Each detector was split into four horizontal quadrants with width 512 pixels
and height 2048 pixels.

  2. 2.

The median across the horizontal axis was calculated, resulting in a
2048-pixel array.

  3. 3.

In a slight departure from Massimo’s method, we then smoothed the median array
using a 1D median filter with length that varied depending on the filter.
’F410M’: 15, ’F405N’: 256, ’F466N’: 55, ’F182M’: 55, ’F187N’: 256, ’F212N’:
512. We found that the original method, which was to obtain a single constant
at this step, turned the destreaking process into a high-pass filter and
therefore removed significant extended emission.

  4. 4.

We subtracted the median array from each quadrant, then added back the
smoothed median.

We evaluated the effectiveness of this process by eye. While the original
destreaker completely removed the 1/f horizontal features, it also removed all
of the extended background. The modified version removed most of the
horizontal features while preserving the large-scale extended structure. It is
likely that some intermediate-scale features (i.e., physical features
comparable to 512 pixels across) are not recovered by this procedure, which
will need to be accounted for in analysis of the extended emission.

###  3.3 Photometric and Astrometic Cataloging

For photometry of unsaturated stars, we used the crowdsource python package
(Schlafly, 2021). We used a PSF model from webbpsf (Perrin et al., 2015).
Because we were using mosaiced images, the webbpsf PSF is not a perfect
representation of the data; each individual frame had to be shifted and
drizzled to form our final images. Furthermore, for the short wavelength
bands, we adopted the PSF for a single detector (NRCA1 or NRCB1 as
appropriate) for the full frame, since webbpsf does not provide a tool to
produce a PSF grid across the whole module.

We identified saturated stars so that we could ignore them, and stars too
close to them (which are likely to be affected by the extended PSFs of
saturated stars), for further analysis. To identify these stars, we measured
the centroids of all regions in which either the data (FITS extension SCI) or
the variance (FITS extension VAR_POISSON) was zero. We then fitted the PSF of
these stars excluding the saturated pixels and a surrounding set of pixels
identified through binary dilation. The detailed values of the dilation size
are given in saturated_star_finding.py. While we measured both photometry and
astrometry of these saturated stars, we use only the astrometry in subsequent
sections, and only as a means to automatically exclude saturated stars and
their nearest neighbors.

###  3.4 Catalog matching

We assembled a catalog consisting of all sources found in any of our six
filters. To assemble the coordinate list, we started with all coordinates in
the F405N catalog, then for each other filter, we added all sources that did
not have a match in the existing catalog within $d<0.15\arcsec$. The
crossmatch shows a large peak for matches within $d<0.1\arcsec$ with large
tails at greater separation; we have not investigated the origin of these
large-offset sources, but suspect low signal-to-noise sources, PSF artifacts,
and features in the extended background may contribute. We then excluded all
sources with a crossmatch distance to the reference filter’s coordinates
$d>0.1\arcsec$ (the reference filter is F405N by default, but for sources with
nondetections in F405N, a different reference filter was adopted).

For subsequent analysis, we then rejected all sources with magnitude errors
$\sigma_{m}>0.1$, ‘quality factor’ qf $<=0.6$, spread $>0.25$, or fracflux
$<0.8$, all of which are values calculated by crowdsource. These choices
select for round, pointlike, unblended stars. We also limited our analysis to
sources with detections in all six bands.

The resulting crossmatched catalogs had RMS positional offsets $<0.02$ ″(Table
1). We do not concern ourselves further with astrometry in this manuscript,
but caution that, with these sizeable crossmatch errors, our catalogs likely
are not yet of sufficient quality to support proper motion measurements.

We found 377,236 stars with a good measurement in at least one filter, and
56,146 with good measurements in all six filters. The number of good
measurements found in each filter is given in Table 1 (these include sources
with offsets from the reference filter $d>0.1\arcsec$).

Table 1: Observations

Filter Name | RMS Offset | 90th percentile | # of sources
---|---|---|---
| ′′ |  $\mathrm{mag}$$\mathrm{\left(\mathrm{AB}\right)}$ |
F182M | 0.020 | 20.4 | 337561
F187N | 0.021 | 20.3 | 213894
F212N | 0.020 | 19.5 | 236077
F405N | - | 19.5 | 85126
F410M | 0.016 | 19.6 | 102344
F466N | 0.021 | 19.6 | 79629

The RMS offset reports the standard deviation of the source position
difference between the specified filter and the reference filter, F405N. The
90th percentile column reports the 90th percentile magnitude in the catalog to
give a general sense of depth.

###  3.5 Starless Image Creation

For comparison of star locations to extinction features, we preferred to work
with an image with stars removed. Note that, because of significant
uncertainty in this process, we have used the star-subtracted images only for
qualitative, not quantitative, analysis. A starless image is the natural
residual of an image that has been processed through a PSF photometry routine
that appropriately accounts for the non-point-source background. However, when
we produced such images, they had substantial residual features, which were
caused by a combination of an imperfect PSF model and oversubtraction of
sources on extended backgrounds. To create a cleaner starless image, we took
the difference between the narrow-band and medium-band images after
appropriately scaling the narrow-band image. The F405N image was convolved
with a 0.3 pixel Gaussian to better match the PSF of the F410M filter.

(a)

(b)

Figure 2: Stars with blue F410M-F466N colors ([F410M]-[F466N] $<-0.45$ mag in
green and $<-1.45$ mag in blue) shown with X’s on the star-subtracted RGB (a,
top) and not-star-subtracted (b, bottom) image. Note that declination is on
the X-axis, contrary to convention.

We produced a line-free F410M image, labeled 410m405, by the following
equation:

$S_{410m405}=\frac{S_{F410M}-S_{F405N}\cdot w}{1-w}$ (1)

where $w$ is the fractional bandwidth of F410M covered by F405N and
$S_{filtername}$ is the surface brightness in a given filter. This process
effectively creates a continuum-only ‘notch’ filter image. We produced a star-
free F405N image, labeled 405m410, by subtracting the (theoretically
continuum-only) 410m405 image from F405N. Note that the images are in units of
surface brightness, MJy sr-1, such that line emission in broad-band filters is
diluted (will have a lower surface brightness), while spectrally flat
continuum sources (to a coarse approximation, stars) will have the same
brightness in broad and narrow filters. We then produced a somewhat star-free
F466N image, which we label 466m410, by subtracting the 410m405 image scaled
by $R=(4.66/4.10)^{-2}=0.77$ (assuming a blackbody on the Rayleigh-Jeans tail,
$S_{\lambda}\propto\lambda^{-2}$).

$S_{466m410}=S_{F466N}-S_{410m405}\cdot R$ (2)

This $S_{466m410}$image has much greater residuals, since the wavelengths do
not overlap and differences in dust extinction (and ice absorption; see below)
render the subtraction somewhat poor. Nevertheless, the stars are largely
removed, and in particular, their extended PSFs are mitigated. The subtraction
process is recorded in the notebooks BrA_separation_nrca.ipynb,
BrA_separation_nrcb.ipynb,
F466N_separation_nrca.ipynb,
and F466N_separation_nrca.ipynb.

This process still left significant residuals throughout both the 405m410 and
466m410 images. To further remove stars—at this stage, purely for aesthetic
purposes—we identified the locations of significant residuals and masked them
out, then interpolated across them. We performed this process iteratively,
using larger masks for stars with more extended PSF features and smaller masks
for more compact, fainter stars. The details of the process were largely
decided ‘by hand’, i.e., testing a small variation in a parameter (e.g., the
mask size) and revising if it did not look good. We also created custom masks
to remove residuals from extended PSFs. The masking process is recorded in the
StarDestroyer_nrca.ipynb and StarDestroyer_nrcb.ipynb notebooks. After each
module was fully star-subtracted, the images were merged in the
Stich_A_to_B.ipynb notebook.

Figure 1 shows the merged full-frame
image.555https://www.dropbox.com/scl/fi/39cfq8yr40460qaoy1wlf/BrickJWST_merged_longwave_narrowband_lighter.png?rlkey=lusbv81fsr9rvupt99zqmvpqj&dl=0
This image is composed of the 466m410 image in red, 405m410 in blue, and
405m410+466m410 in green. We created it by building three layers, 466m410,
405m410, and (466m410 + 405m410), which we then composed into an RGB image
cube. Figure 2a shows the same image, and Figure 2b shows the version with
stars un-removed. Figure 2 also shows a subset of the cataloged stars in green
and blue X’s, as will be described in §4.1.

##  4 Results

The Brick stands out in infrared images as a dark feature against a background
both of stars and of diffuse emission (e.g., Figure 1). We start by
highlighting in §4.1 that The Brick is an extinction feature, but that it
exhibits peculiar colors in the F466N filter. We then discuss the diffuse
emission from recombination lines in §4.2. Both from absorption of this
diffuse emission and from the colors of extincted stars, we infer that gas
(§4.3) and ice (§4.4) are contributing to the line-of-sight absorption that
defines The Brick. This physical explanation is summarized in Figure 3, which
shows the atomic and molecular lines and the ice bands overlaid on the
observed filters. The observational result is summarized in Figure 4, which
shows the photometric data.

(a)

(b)

Figure 3: CO ice can absorb recombination line emission, but CO gas cannot.
This figure shows the transmission curve, relative intensity of hydrogen
recombination emission lines, and optical depth of CO gas absorption lines in
selected NIRCam long-wavelength filters. F410M and F405N are shown in (a) and
F466N is shown in (b). This is a schematic figure showing where lines and ice
features appear and what their relative strengths are, but the amplitude
scales are arbitrary: we selected column densities of CO such that the peak
$\tau\approx 1$, while the inferred column densities are $\sim 2$ orders of
magnitude greater. Both the F466N and F405N filters cover hydrogen
recombination lines. We show these as orange stick spectra (i.e., they have no
width), with peak levels set as the ratio of the emissivity of the labeled
line to that of Br$\alpha$ under case B conditions for $n_{e}=10^{4}$
$\textrm{cm}^{-3}$ and T$=10^{4}$ K (see §4.2). The CO gas, discussed in §4.3,
overlaps extensively with the F466N filter. The CO gas absorption optical
depth $\tau$ is shown using a synthetic spectrum with $N(CO)=5\times 10^{16}$,
T=50 K, and $\sigma=5$ km s-1 (§4.3). Both 12CO and 13CO are shown with the
same column density, but we expect $N(^{13}\mathrm{CO})\approx
25N(^{12}\mathrm{CO}$) (e.g. Henkel et al., 1985). 13CO is shown with a
greater temperature, T=100 K, because at 50 K the lines near Hu$\epsilon$ are
too weak to appear in the figure. As shown in the inset in figure (b), the
Pf$\beta$ line lies between the CO v=1$\leftarrow$0 J=1$\leftarrow$0 and
J=2$\leftarrow$1 transitions ($\Delta v\approx 200-300$ km s-1), while
Hu$\epsilon$ is close to the J=0$\leftarrow$1 transition ($\Delta v\approx
100$ km s-1). These lines would therefore would require implausibly large
broadening and/or doppler shift to overlap. The red thin curves show CO and
CO2 ice optical depth $\tau$ using Hudgins et al. (1993) transmission curves,
which overlap with the recombination lines.

###  4.1 Some stars are too blue in F466N colors

The first intriguing result from these data is that, in colors including
F466N, which is our longest-wavelength filter, the stars that are most
extincted appear too blue. In general, dust extinction causes reddening, i.e.,
the shorter-wavelength photons are more attenuated than the long-wavelength
photons; in this case, we see the inverse effect happening. This feature is
evident in color-magnitude and color-color diagrams (CMDs and CCDs; Figure 4).
Figure 4c shows a CCD with an extinction vector from Chiar & Tielens (2006,
hereafter CT06) overlaid666We used the CT06_MWGC extinction curve from the
dust_extinction package because it was implemented in that package, was
appropriate for the Galactic Center, and covered the range of filters used in
this work. The data used by CT06 come from Lutz (1999) and Indebetouw et al.
(2005)., demonstrating that colors including the F466N filter go in a
direction not accounted for by normal dust-extinction-driven reddening. We see
excess absorption in the F466N filter of roughly 0.035 magnitudes per $A_{V}$
with substantial scatter.

The bluest stars in [F410M]-[F466N]777We use the bracket notation, e.g.,
[F466N], to indicate a magnitude measurement. [F410M]-[F466N] indicates a
difference in magnitudes, i.e., a flux ratio or a color. Negative colors are
blue, positive colors are red, by convention. are seen at the edge of the
cloud. Figure 2 shows the location of these bluest ([F410M]-[F466N] $<-0.75$
mag) stars. The most extincted stars, which are the reddest in most colors but
are bluest in colors involving F466N, are primarily seen along the outskirts
of the cloud. Figure 4a shows stars color-coded by [F187N]-[F405N] color. We
use [F187N]-[F405N] color as a consistency check: this color is very well
correlated with both [F182M]-[F212N] and [F212N]-[F410M] color in panel (b),
indicating that the trend seen in panel (c) is not caused by F410M. The
interior of the cloud appears relatively blue in Fig. 4a because only low-
extinction stars are detected in the shorter-wavelength filters, and we plot
only stars with detections in all six filters in this figure. Figure 4b
highlights that colors not involving the F466N filter are consistent with
extinction.

(a)(b)(c) Figure 4:  (a, top) Location of the 34,150 stars with detections in
all six bands that met the quality criteria specified in §3.3 and that have
[F410M]$<$15.4 mag. Note that declination is on the X-axis. (b, lower left)
Comparison of [F182M]-[F212N] to [F212N]-[F410M] color. (c, lower right)
Comparison of [F182M]-[F212N] to [F410M]-[F466N] color. An extinction vector
$A_{V}$=30 using the CT06 curve is overlaid, corresponding to about 1
magnitude of [F182M]-[F212N] color excess. In (b), the extinction vector
parallels the stars in the CCD, while in (c), the dust extinction vector
points in a different direction: the [F410M]-[F466N] color becomes bluer,
rather than redder, with increasing extinction. The correlation between the
colorbar and each of the colors in (b) indicates that all of these colors
align with dust extinction. We adopted a sequential colormap to emphasize the
most extincted sources, which show up as dark red in the displayed
[F187N]-[F405N] colors. The colormap uses [F187N]-[F405N] to demonstrate that
all observed colors not involving F466N exhibit reddening consistent with dust
extinction).

###  4.2 The F466N recombination lines are fainter than expected

The diffuse emission circumscribing The Brick, seen in F405N and F466N in
Figure 1, is comprised primarily of Br$\alpha$ (F405N) and Pf$\beta$ plus
Hu$\epsilon$ (F466N) emission. Figure 3 shows where these lines reside with
respect to the transmission profiles of the filters. There are no other
expected sources of emission in this band, as there are no known PAH features
in the 4-5$\mu\textrm{m}$ range and free-free emission is expected to be
weaker by $\sim 100\times$ in the narrow bands.

The ratio of hydrogen recombination lines is governed by simple rules under
the assumption of Case B recombination, which is expected at moderate
densities. The expected ratio of Pf$\beta$ / Br$\alpha$ under Case B
recombination at electron temperature $T_{e}\sim 5000-10^{4}$ K is
$R_{Pf\beta/Br\alpha}=0.202$ (Storey & Hummer, 1995). The ratio of
Pf$\beta$+Hu$\epsilon$, the sum of the two lines in F466N, to Br$\alpha$ is
$R_{(Pf\beta+Hu\epsilon)/Br\alpha}=0.234$. The average foreground extinction
toward the CMZ (Launhardt et al., 2002; Nogueras-Lara et al., 2021) is
$A_{V}=30$. Using a CT06 extinction curve, in the absence of narrow spectral
features, the ratio above rises to
$R_{(Pf\beta+Hu\epsilon)/Br\alpha}(A_{V}=30)=0.269$. At greater extinction,
this ratio (which is equivalent to [F405N]-[F466N] color) is expected to rise
(become redder). However, contrary to this expectation, we see the
[F405N]-[F466N] color becoming more negative (bluer) along the edge of The
Brick (Figures 1 & 2). We are therefore seeing that, in regions of greater
extinction, the ratio is the inverse of what is expected from dust extinction
alone.

####  4.2.1 CO absorption of the F466N recombination lines

There are additional absorption processes that affect only the F466N filter.
The F466N filter covers both CO gas and ice features (we will discuss these
further in §4.3 & §4.4), and therefore we expect the [F405N]-[F466N] color to
be more negative than the theoretical Case B recombination value if CO ice is
present along the line of sight. We observe this decrease: the edges of the
molecular cloud appear brown in Figure 1, indicating a relative deficiency in
the F466N filter compared to regions farther from the molecular cloud.

To assess whether the absorption is caused by CO gas or ice, we model the
absorption caused by CO. Figure 3b shows a CO line profile modeled assuming
local thermodynamic equilibrium (LTE) conditions for a column density of
N(CO)=$5\times 10^{16}$ $\textrm{cm}^{-2}$, temperature $T=50$ K, and
linewidth $\sigma=5$ km s-1. This figure shows that there is a greater than
$100$ km s-1 offset between the CO gas lines and the hydrogen recombination
lines. The broadest linewidths observed in the molecular gas are less than
$20$ km s-1 (Henshaw et al., 2019), so CO lines are unlikely to strongly
absorb the recombination line emission.

By contrast, CO ice produces broadband absorption that affects both the
Pf$\beta$ and Hu$\epsilon$ lines. Figure 3 shows CO and CO2 absorption
profiles both with assumed N(CO) $=10^{17}$ $\textrm{cm}^{-2}$. The CO ice
profile overlaps significantly with both recombination lines in the F466N
filter. We also model the CO2 ice feature as a consistency check: if CO ice is
present, CO2 ice is also likely present, and therefore we verify that CO2 ice
would not undo the observed blue colors in [F405N]-[F466N]. The CO2 ice, shown
in panel (a), significantly overlaps with the F410M filter but has little
overlap with the Br$\alpha$ line, confirming that CO2 ice can be present
without driving [F405N]-[F466N] toward the red.

Based on the observation that there is excess absorption of the diffuse F466N,
and the modeling shown in Figure 3, we conclude that CO ice, and not CO gas,
is absorbing Pfund $\beta$ and Humphreys $\epsilon$ emission.

###  4.3 CO Gas

As shown in Figure 3, the 12CO lines in the F466N band can produce significant
absorption against stellar continuum light. In this section, we evaluate
whether CO gas can produce the observed stellar colors. We already saw in §4.2
that CO gas is unlikely to produce selective extinction of
Pf$\beta$+Hu$\epsilon$. We find here that CO gas contributes to, but does not
dominate, the total absorption in F466N.

We model this absorption as a function of temperature, column density, and
linewidth assuming local thermodynamic equilibrium (LTE) conditions. Details
of this modeling are given in an associated Jupyter notebook,
COFundamentalModeling.ipynb, that can be found in the associated GitHub
repository. The model implementation is in the pyspeckit-models package, which
implements models compatible with pyspeckit (Ginsburg et al., 2022). We used
transition and level tables from the exomol database (Tennyson et al., 2016)
derived from Li et al. (2015) using Yurchenko et al. (2018) as an
implementation reference.

Figure 5 shows example optical depth spectra overlaid on the transmission
profile of the F466N filter. The v=1$\leftarrow$0 and J=4$\leftarrow$3,
3$\leftarrow$2, 2$\leftarrow$1, 1$\leftarrow$0 R-branch transitions and the
v=1$\leftarrow$0 J=0$\leftarrow$1 P-branch transition all lay within the range
where F466N has $>50$% of peak transmission (we use $\leftarrow$ in the
transition names to indicate that these are absorption lines). The maximum
absorption in this filter occurs for temperatures between 10-20 K, while we
expect gas temperatures near 50-100 K (Ginsburg et al., 2016; Immer et al.,
2012; Krieger et al., 2017). At greater temperatures, a large fraction of CO
molecules are in states that only produce transitions outside of the F466N
band, reducing the absorption for a fixed assumed column density. It is
possible that some of the CO gas is at moderate densities ($n(H_{2})\lesssim
10^{4}$ $\textrm{cm}^{-3}$) and therefore is sub-thermally excited, which
would concentrate the CO molecules into the lower-J levels, thereby reducing
the effect of high gas temperature. Nevertheless, the LTE models shown in
Figure 5 capture the range of expected behavior.

We model the CO gas absorption for the expected range of line width and column
density in the Galactic Center. For narrow line widths, such as those caused
by thermal broadening at $T<100$ K, the absorption is negligible. In the
Galactic Center, there is significant doppler broadening that is generally
attributed to turbulence. The total linewidth in the cloud may range from
$\sigma\sim 5-20$ km/s (Henshaw et al., 2019). CO column densities will span
the full range from effectively zero (since CO is destroyed by UV at
$A_{V}\lesssim 2$) to $\sim$ a few$\times 10^{19}$ cm-2 (Rathborne et al.,
2015) assuming $X_{CO}=10^{-4}$. In our observations, we detect stars at
wavelengths short of 2$\mu\textrm{m}$ only at intermediate column densities,
most likely below $A_{V}<80$ mag ($N(H_{2})<10^{23}$ $\textrm{cm}^{-2}$),
since dust extinction hides the stellar continuum at greater column density at
the current level of sensitivity.

Figure 6 summarizes the modeling results. Given the plausible range of column
density and line width, the total CO gas absorption in F466N may range from
$\sim 1\%$ to at most $\lesssim 20\%$.

(a)

(b)

(c)

Figure 5: Example spectra showing the optical depth of gas-phase 12CO
v=1$\leftarrow$0 absorption superposed on the transmission spectrum of the
F466N filter for a variety of physical conditions. The thick black curve in
each case shows the transmission function of the F466N filter. The thin blue
curves show the absorbed light fraction $1-e^{-\tau}$. Panel (a) shows the
effect of this absorption for a low column density case (N(CO) = $1\times
10^{16}$ $\textrm{cm}^{-2}$ or N(H2) $=1\times 10^{20}$ $\textrm{cm}^{-2}$ for
a typical CO abundance of $X_{CO}=10^{-4}$). Panel (b) shows N(CO)=$10^{17}$
$\textrm{cm}^{-2}$ (N(H2) $=10^{21}$ $\textrm{cm}^{-2}$). Panel (c) shows
transmission for CO column density $10^{17}$ $\textrm{cm}^{-2}$ (N(H2) =
$1\times 10^{21}$ $\textrm{cm}^{-2}$) but with a broader line, illustrating
that more of the band is absorbed but the peak optical depth is lower. We
model low column densities to illustrate the behavior that affects the
majority of stars in our sample, which are at relatively low column density,
and to highlight the effects of gas temperature on the lines that are excited.
The modeled column densities here fall significantly short of the peak column
in The Brick, N(H2)$\approx 5\times 10^{23}$, but panel (b) captures the
behavior at greater column densities: the line optical depths are large, so
the lines are saturated. At greater column densities, there is very modest
optical depth broadening, but qualitatively even extremely high column density
resembles that model spectrum.

(a)

(b)

(c)

Figure 6: The fractional absorption by gas-phase CO v=1$\leftarrow$0
absorption within the F466N band for 20K (left), 60 K (middle), and at a fixed
column density $N_{CO}=10^{18}$ $\textrm{cm}^{-2}$ (right). The grayscale
shows the fractional absorption as labeled in the colorbar; an absorption of
1.0 implies that no photons are received in the band. Colored lines are placed
at levels=[0.01, 0.05, 0.1, 0.15, 0.2, 0.3, 0.4, 0.5] with colors=[white,
yellow, green, cyan, red, blue, purple, orange], respectively, to help guide
the eye. These curves occur in order from bottom to top and the line widths
progress from thick to thin. These levels correspond to magnitude differences
$\Delta m=$ [0.011, 0.056, 0.114, 0.176, 0.242, 0.387, 0.555, 0.753].

At the column densities where the absorption is easily detectable (fractional
absorption $\gtrsim 0.1$ results in a change in magnitude $\Delta m\gtrsim
0.1$; green line in Figure 6), change in linewidth dominates over the change
in column density or temperature. The foreground Galactic disk clouds, which
have narrow lines, produce relatively little absorption; we therefore argue
that intervening material between us and the Galactic Center is not primarily
responsible for the blue [F410M]-[F466N] color of the stars. These models also
imply that, even at very extreme column densities ($N_{CO}>10^{19}$
$\textrm{cm}^{-2}$), “normal” galactic disk clouds with $\sigma<10$ km s-1
will produce minimal CO absorption in the F466N band, while typical galaxy
center and galactic bar clouds with $\sigma\sim 10-50$ km s-1 will produce
readily detectable absorption. However, even for very broad lines
($\sigma=50\textrm{km~{}s}^{-1}$) at high column ($N_{CO}\sim 10^{19.5}$
$\textrm{cm}^{-2}$), CO gas produces $\lesssim 1$ magnitude ($<50\%$) of
absorption in the F466N band.

###  4.4 CO ice absorption

While we show above that CO gas can produce a substantial amount of
absorption, the observed absorption depths reach levels difficult to explain
with gas alone. Figure 6 shows that CO column densities $N(CO)>10^{19.5}$
$\textrm{cm}^{-2}$, implying $N(H_{2})>3\times 10^{23}$ $\textrm{cm}^{-2}$,
are required to explain the $\gtrsim 2$ magnitudes of F466N absorption shown
in Figure 4. Such high column densities are rare in The Brick (Rathborne et
al., 2014a), occurring primarily in the inner regions (see their Figure 2) and
in dense cores (Walker et al., 2021), while the high-extinction and high-CO-
absorption stars we detect are primarily in the outskirts (Figure 2). Stars
behind these high column densities would be too extincted to detect in the
shorter wavelength band; the highest extinction we report in §4.4.2 is
$A_{V}\sim 80$ mag, or $N(H_{2})\sim 10^{23}$ $\textrm{cm}^{-2}$.
Additionally, in Section 4.2, we showed that CO gas is unlikely to absorb
recombination lines. We therefore examine the possibility that ice absorption
is responsible for the observed F466N deficits.

There is evidence that The Brick contains some ice, but also that CO is not
entirely frozen out. Pure CO ice forms at low temperatures, $T<20$ K (Hudgins
et al., 1993). The average dust temperature in The Brick is close to 20 K
(Tang et al., 2021), so it is probable that some of the volume of The Brick is
cold enough to freeze CO. The Brick exhibits signs of substantial freezeout in
its center based on gas observations (Rathborne et al., 2014b), but still has
substantial gas-phase CO detected (Ginsburg et al., 2016; Rigby et al., 2016;
Eden et al., 2020). It is likely that much of the observed gas-phase CO is on
the cloud surface, while further into the interior, CO is more completely
frozen out.

####  4.4.1 CO ice modeling

To model CO ice absorption, we convolved a given filter transmission curve
with a synthetic stellar model spectrum. We began with a 4000 K PHOENIX
stellar atmosphere (Husser et al., 2013) as the base model, then examined the
fractional flux lost in the F466N band as a function of CO column density. We
retrieved optical constants for pure CO ice and CO mixed with OCS and CH4 in a
20:1 ratio from Hudgins et al. (1993) via the JPL Optical Constants
Database888https://ocdb.smce.nasa.gov/page/toc. We do not know which ice
mixture is most appropriate for our data, so we chose to show all available
laboratory mixtures in which CO was the primary constituent. We also
considered the possibility that CO is embedded in other ices (e.g., H2O and
$\textrm{CH}_{3}\textrm{OH}$ Pontoppidan et al., 2003; Boogert et al., 2008),
but found little practical difference from pure CO ice when using the Hudgins
et al. (1993) and Rocha et al. (2016) optical constants.

Figure 7 shows the effects of CO ice absorption999Figure 7a includes the F470N
filter, which we have not used in this work, to caution other JWST users that
there may be significant, albeit weaker, CO absorption in this filter.: at
$\mathrm{N(CO)}\approx 10^{19}$ $\textrm{cm}^{-2}$, we expect $\approx 0.5-1$
mag of absorption from the ice band. The greatest observed column density
within The Brick, based on ALMA dust emission observations with $\sim
3\arcsec$ resolution, is $\mathrm{N}(\mathrm{H}_{2})\sim 5\times 10^{23}$
$\textrm{cm}^{-2}$ (Rathborne et al., 2014a), which implies an upper limit on
the ice column density $\mathrm{N(CO)}<5\times 10^{19}$ $\textrm{cm}^{-2}$ if
we assume the CO/H2 ratio is $10^{-4}$ and the gas-to-dust mass ratio is 100.
If _all_ of the CO is frozen out into pure CO ice, in the highest column-
density line-of-sight, the absorption in F466N could just about reach 1.2 mag
($\sim 65$%).

Figure 8 shows similar plots for the F405N and F410M filters for CO2 ice to
demonstrate that CO2 ice can have some effect, but less than CO, on our
observed colors.

(a)

(b)

Figure 7:  (a) Overlap of the transmission profiles of the F466N and F470N
filters with CO ice absorption models superimposed on a PHOENIX 4000 K stellar
photosphere model. The absorption profiles are produced using Hudgins et al.
(1993) opacity measurements. (b) The expected absorption as a function of
column density in the F466N band for three different CO ices. The absorption
is given in fractional value on the left and magnitudes on the right. The
arrows show the highest observed column density of CO ice from the Boogert et
al. (2022) sample of high-mass young stellar objects and the maximum possible
CO column density assuming a CO abundance with respect to H2 of 10-4 given the
observed column density in The Brick (but see §5.1 for a discussion of this
assumption).

(a)

(b)

Figure 8:  (a) Overlap of the transmission profiles of the F405N and F410M
filters with CO2 ice absorption models superimposed on a PHOENIX 4000 K
stellar photosphere model. The absorption constants are for pure CO2 ice from
Hudgins et al. (1993) via the Optical Constants Database (OCDB). (b) The
expected absorption as a function of column density in the F405N and F410M
bands. The absorption is given in fractional value on the left and magnitudes
on the right.

####  4.4.2 CO ice as a function of extinction

We compared the inferred extinction to the CO ice column to obtain a coarse
estimate of how CO ice varies with $A_{V}$. We use [F182M]-[F212N] color to
estimate $A_{V}$ using the CT06 extinction curve, which we justify by
comparing to ground-based GALACTICNUCLEUS colors in Appendix A.

To measure the CO absorption, we used the [F410M]-[F466N] color. Figure 4c
shows that the [F410M]-[F466N] color becomes bluer at greater extinction. We
calculated the absorption from pure CO ice in the F466N band to obtain a
mapping from N(CO) to [F410M]-[F466N] color. We dereddened our measured
[F410M]-[F466N] color using the $A_{V}$ computed above with the CT06
extinction curve. Note that the assumed extinction curve introduces a strong
systematic uncertainty: using a Fritz et al. (2011) extinction curve would
reduce the estimated $A_{V}$ by a factor of 1.8. Figure 9 shows the resulting
N(CO) as a function of $A_{V}$. Note that this curve assumes that 100% of the
deficit in the [F466N] band is produced by ice, which is an upper limit and
likely overestimate because CO gas (§4.3) also contributes, especially at low
column density.

The red curve in Figure 9 shows the maximum possible CO at each $A_{V}$
adopting standard values of N(H${}_{2})=2.21\times 10^{21}A_{V}$ (Güver &
Özel, 2009) and CO abundance relative to hydrogen $X_{CO}=10^{-4}$. Some of
the data points reside above this curve, suggesting that one or both of these
assumptions may be incorrect, which we will evaluate further in §5.1.

While there is overall correlation between N(CO) and $A_{V}$, the dispersion
at any given $A_{V}$ is large, greater than one order of magnitude. Such a
large scatter indicates a wide range of conditions, with many lines-of-sight
containing little CO at the lowest observed $A_{V}$.

Figure 9: N(CO ice) vs $A_{V}$. The black dashed line is shown as a
representative typical value; it is not a fit to the data. The green solid
line is from Boogert et al. (2015, Figure 7). The red dotted line shows the CO
column density obtained by converting N(CO) = N(H2)/104. $A_{V}$ is computed
from [F182M]-[F212N] color using the CT06 extinction law. We caution that the
X-axis is subject to systematic uncertainty from the choice of extinction
curve; using the Fritz et al. (2011) curve instead of CT06 would compress the
X-axis by a factor of 1.8. Additionally, N(CO ice) is calculated assuming 100%
of the F466N deficit is produced by ice, not gas, while gas certainly
contributes to the absorption, especially at lower column density (see §4.3).
Statistical errors are limited to $\sigma(\log N(CO))\lesssim 0.17$ dex and
$\sigma(A_{V})\leq 4.4$ mag, which come from the selections imposed on the
catalog (we include only stellar measurements with $\sigma<0.1$ mag) and a
simple linear propagation of error for N(CO).

##  5 Discussion

###  5.1 CO produces F466N absorption

The CO ice models can qualitatively explain most of the observed F466N
deficits. However, neither the gas nor ice models appear to quantitatively
explain the most deeply absorbed sources. In both the gas and ice absorption
cases, it is possible to achieve substantial absorption in the F466N band,
enough to be easily detected, but less than the 1-2 mag seen in Figure 4 if
typical CO abundance and gas-to-dust ratios are used.

One possible explanation lies in our assumptions about how to convert column
densities between dust, molecular hydrogen, and CO: if the CO/H2 ratio is
greater than the assumed 10-4, or the gas-to-dust ratio is less than 100 (e.g.
Giannetti et al., 2017), the total CO column could be greater. Increasing the
CO abundance or decreasing the gas-to-dust ratio, both of which are plausible
because gas in the CMZ is higher-metallicity than the solar neighborhood,
would both have the effect of shifting the red dashed line upward in Figure 9.
These changes would therefore increase the maximum allowed CO abundance and
explain the large observed F466N absorption.

###  5.2 Ice freezeout and gas thermodynamics

The presence of significant quantities of CO ice in The Brick highlights the
fact that the dust is significantly colder than the gas. Gas temperatures in
the CMZ generally (Ginsburg et al., 2016; Krieger et al., 2017), and The Brick
specifically (Johnston et al., 2014), are observed to be high, $T\gtrsim 50$
K, and in many locations $T>100$ K. Freezing of pure CO into ice is expected
to occur at dust temperatures $T\lesssim 20$ K, though CO can be integrated
into H2O and $\textrm{CH}_{3}\textrm{OH}$ ices that freeze out at greater
temperatures ($T\gtrsim 80$ K; Boogert et al., 2015; Garrod & Herbst, 2006).
The dust temperatures observed in The Brick have been in the range $T\sim
20-30$ K, albeit at lower resolution (Marsh et al., 2016; Tang et al., 2021),
which is somewhat too warm for pure CO freezeout but cold enough to freeze
other molecules. However, dust temperature measurements are biased toward
warmer dust, since it is brighter, so it is likely that colder dust is present
deep inside The Brick.

Both an excess of CO in Galactic Center gas, and freezeout during
gravitational collapse, may result in a change in the effective equation of
state of the gas. In the dense molecular medium ($n\gtrsim 10^{3}$
$\textrm{cm}^{-3}$) that comprises The Brick, CO is the dominant gas-phase
coolant (Ginsburg et al., 2016). If the CO abundance is greater than in the
solar neighborhood (§5.1), we expect more efficient cooling in the lower-
density outskirts of CMZ clouds. By contrast, as the clouds collapse to
greater density, there may be a point at which the CO has frozen out to the
point that it is no longer the dominant coolant, but where the densities are
still too low for dust to be an efficient coolant. We suggest that systematic
variations in the cooling function as a function of density or column density
should be explored in future simulations of CMZ cloud thermodynamics like
those in Clark et al. (2013).

###  5.3 Broader implications & future applications

The prevalence of CO ice in our own Galactic Center hints that ice is likely
widespread in galactic centers generally. At least in the local universe,
then, JWST observations using the long-wavelength narrowband filters should
carefully treat CO absorption in addition to extinction effects. Our Figure 9
gives an empirical tool to link extinction and ice, though we caution that the
large scatter demonstrated in that plot limits the usefulness of the linear
relation given in its legend.

The easy detection of ices in the F466N narrow band filter also opens
opportunities to better understand dust and ice in the ISM and to understand
cloud structures. While NIRSpec will be capable of studying hundreds of stars
with ice absorption in detail, NIRCam observations can easily measure tens of
thousands of sightlines simultaneously, enabling detailed correlation analyses
like those shown in Fig. 9. By adding comparable-resolution gas observations
from ALMA, it should be possible to trace the freezeout of CO from gas to ice
in detail. With a few other bands, such as F300M and F335M, it will be
possible to track H2O and $\textrm{CH}_{3}\textrm{OH}$ ice and determine when
and how much CO is incorporated into H2O ice, which freezes at a substantially
greater temperature.

The overlap of the CO ice feature with Pf$\beta$+Hu$\epsilon$ also opens the
possibility of making $\sim 0.1\arcsec$ resolution maps of CO ice absorption
against the diffuse ionized emission. From the Pa$\alpha$/Br$\alpha$ ratio, we
can determine the dust extinction on a per-pixel basis, which will enable
specific measurement of CO ice absorption from the now known
Br$\alpha$/Pf$\beta$ ratio. Since the CO ice feature affects the Pf$\beta$
line, but CO gas does not, this approach will also allow us to distinguish
whether ice or gas is the dominant absorber on most sightlines.

##  6 Conclusions

We report observations of G0.253+0.016, an infrared dark cloud known as “The
Brick,” with JWST’s NIRCam in narrow-band filters. We produce a crossmatched
photometric catalog using the crowdsource package. We find 377,236 unique
sources, of which 56,146 are detected in all six photometric bands.

In this first publication on these data, we show that there is significant
absorption toward stars in the F466N band, which is caused by CO ice and gas.
We argue that ice is predominant along most sightlines and provide modeling
results to show the effect of ice and gas absorption on this and other JWST
filters. While CO absorption is a suitable explanation for the observed F466N
absorption, the quantities of both ice and gas required to produce the
observed absorption are in some tension with the observed line-of-sight column
density. This result indicates that the standard abundance of CO
($X_{CO}=10^{-4}$) and/or the dust-to-gas ratio (10-2) are too low for the
Galactic Center environment.

Acknowledgements We thank the referee for a helpful and very detailed report,
particularly on their review of labeling conventions and figure clarity. We
thank Eddie Schlafly and Andrew Saydjari for their assistance with crowdsource
technical issues. AG acknowledges support from STSCI grant JWST-
GO-02221.001-A, and from the NSF through AST 2008101, AST 220651, and CAREER
2142300. CB gratefully acknowledges funding from the National Science
Foundation under Award Nos. 1816715, 2108938, 2206510, and CAREER 2145689, as
well as from the National Aeronautics and Space Administration through the
Astrophysics Data Analysis Program under Award No. 21-ADAP21-0179 and through
the SOFIA archival research program under Award No. 09$\\_$0540\. XL
acknowledges support from the National Natural Science Foundation of China
(NSFC) through grant No. 12273090, and the Natural Science Foundation of
Shanghai (No. 23ZR1482100). JDH gratefully acknowledges financial support from
the Royal Society (University Research Fellowship; URF\R1\221620).

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##  Appendix A Comparison to GALACTICNUCLEUS

The GALACTICNUCLEUS (GN) near-infrared survey (Nogueras-Lara et al., 2019,
2021) partially overlaps with the targeted field of view presented here. GN
has better resolution than VVV and therefore presents a better match to our
data set, but we chose to use VVV as our primary astrometric reference in
Section 3 because GN covers only about half of the southern field we observed.
The greater resolution and sensitivity of GN, however, mean that it is more
appropriate for photometric comparison.

Figure 10: Spatial plot (top) and color-color diagrams (bottom) for the subset
of our sample cross-matched with the GALACTICNUCLEUS survey (Nogueras-Lara et
al., 2021). The left CCD shows our [F182M]-[F212N] color against the GN (H-Ks)
color, demonstrating that there is very good correlation between these colors
and justifying the use of [F182M]-[F212N] as an extinction estimator. The
right CCD shows our [F410M]-[F466N] against GN (H-Ks) color, demonstrating
that the F466N deficit is anticorrelated with (H-Ks) color.

To verify our use of narrow- and medium-band filters in our extinction
measurements, we cross-matched our catalog to the GN catalog and produced
color-color diagrams using the GN (H-Ks) color as a more typical tracer of
extinction. We found the closest match in our catalog to each GN source and
kept all sources with a separation of $<0.2$ ″. In the field in which GN
overlaps our observations, there are a total of 16,021 GN sources and 69,918
sources detected in all three of our short-wavelength bands. Of the GN
sources, 14,557 sources have JWST sources within 0.2 arcseconds, of which
6,844 pass quality criteria specified in §3.4 for all JWST short-wavelength
filters and 3,958 pass quality criteria for all six filters. Figure 10 shows
that we reproduce the same qualitative result as shown in Figure 4 with these
data. This plot demonstrates that our color used to measure extinction in the
JWST data, [F182M]-[F212N] color, is well-correlated with the standard ground-
based (H-Ks) color.

##  Appendix B Ice-affected filters

We demonstrate in this paper that ice absorption affects at least the F466N
filter in Galactic center photometry. We highlight the narrow- and medium-band
NIRCam filters that are potentially affected by ices in Figure 11. This plot
was made using optical constants from the JPL Optical Constants
Database101010https://ocdb.smce.nasa.gov/page/toc using the icemodels
package111111https://github.com/keflavich/icemodels/. This figure provides a
quick-look tool for determining how likely an observation in a given filter is
to be affected by ice absorption, and therefore is a good first stop to check
if one encounters unexpected colors in the long-wavelength NIRCam bands.

Figure 11: Plot of ice absorption and JWST NIRCam filter profiles. The
normalized filter profiles are shown as the positive features above 1.0; all
are peak-normalized. Orange colors are medium-band, blue are narrow-band. The
blue are scaled to a lower peak to avoid overlapping labels. The ice
absorption profiles from several ices are shown in the bottom part of the
plot; each ice is plotted with a column density $N(ice)=10^{18}$
$\textrm{cm}^{-2}$. For many of these molecules, this is an unrealistically
high column density, but it is helpful to illustrate where absorption occurs.
The lower panel includes extinction profiles for three different models: Chiar
& Tielens (2006), Fritz et al. (2011), and Gordon et al. (2021).