# A Molecular Gas Ring Hidden in the Sombrero Galaxy

Jessica Sutter SOFIA Science Center, USRA, NASA Ames Research Center, M.S.
N232-12 Moffett Field, CA 94035, USA  Dario Fadda SOFIA Science Center, USRA,
NASA Ames Research Center, M.S. N232-12 Moffett Field, CA 94035, USA

###### Abstract

We present Herschel, ALMA, and MUSE observations of the molecular ring of
Messier 104, also known as the Sombrero galaxy. These previously unpublished
archival data shed new light on the content of the interstellar medium of
M104. In particular, molecular hydrogen measured by CO emission and dust
measured by far-infrared light are uniformly distributed along the ring. The
ionized gas revealed by H$\alpha$ and [CII] emission is distributed in knots
along the ring. Despite being classified as an SAa galaxy, M104 displays
features typical of early-type galaxies. We therefore compared its [CII] and
dust emission to a sample of early-type galaxies observed with Herschel and
SOFIA. The [CII]/FIR ratio of M104 is much lower than that of typical star-
forming galaxies and is instead much more similar to that of early-type
galaxies. By classifying regions using optical emission line diagnostics we
also find that regions classified as HII lie closer to star-forming galaxies
in the [CII]/FIR diagram than those classified as low-ionization emission
regions. The good match between [CII] and H$\alpha$ emission in conjunction
with the lack of correlation between CO emission and star formation suggest
that there is very limited active star formation along the ring and that most
of the [CII] emission is from ionized and neutral atomic gas rather than
molecular gas. From the total intensity of the CO line we estimate a molecular
hydrogen mass of $0.9\times 10^{9}$M⊙, a value intermediate between those of
early type galaxies and the content of the molecular ring of our galaxy.

Infrared galaxies (790) – Molecular gas (1073) – Galaxy environments (229) –
Interstellar Medium (847)

††facilities: SOFIA (FIFI-LS), Herschel (PACS, SPIRE), Spitzer (MIPS, IRAC),
WISE, ALMA, GALEX, SDSS, 2MASS, VLT(MUSE)††software:  astropy (Astropy
Collaboration et al., 2013, 2018), sospex (www.github.com/darioflute/sospex,
Fadda & Chambers, 2018), HIPE (www.cosmos.esa.int/web/herschel/hipe-download),
CIGALE (https://cigale.lam.fr/, Boquien et al., 2019)

##  1 Introduction

Galaxies are complex structures that can be shaped by a variety of factors.
Each galaxy has its own unique formation history, which can lead to the
creation of spiral arms, rings, bars, or even a lack of structure all
together. In addition to the distinct structural nature of each galaxy, our
observing perspective can have significant effects on the measurable
properties of a galaxy. A dusty, edge-on disk galaxy may appear devoid of
optical tracers of star-formation from our viewing angle, but could present a
different picture if viewed face-on. Piecing together observations of a single
galaxy across the electromagnetic spectrum provides the context to disentangle
different structures and determine how viewing angles affect our ability to
distinguish galaxy characteristics.

Figure 1: Coverage of ALMA, Herschel/PACS, and MUSE data marked with yellow
dashed, red dash-dotted, and cyan dotted lines, respectively, over a three
color HST image of M 104 appeared as Astronomy Picture of the Day on March 29,
2019. The HST data were obtained by the Hubble Heritage Team in the filters
F435W (B), F555W (V), and F625W (r).†

†Credits: ESA/Hubble & NASA/R. B. Andreo,
https://apod.nasa.gov/apod/ap190329.html

One particularly interesting galaxy for studying how unique histories and
observing perspectives can effect certain diagnostics is the nearby galaxy
Messier 104, commonly referred to as the ‘Sombrero Galaxy’. The general
properties of this galaxy are summarized in Table 1. M 104 has been classified
as a SAa spiral, although there has been some debate about the exact nature of
this galaxy (see e.g. Krause et al., 2006, and references therein). While it
appears as an edge–on spiral galaxy with a thick ring of dust, visible as a
dark ring in the HST image shown in Figure 1, the bulge has properties similar
to those of an elliptical galaxy (Krause et al., 2006) and measurements of
star–formation rate (SFR) and dust temperatures match more closely with
early–type galaxies than similar nearby spirals. In addition, decomposition of
the structures observed at 3.6 $\mu$m show that M 104 does not follow
classical bulge/disk relations, and instead is better represented as an
elliptical galaxy with a large halo (Gadotti & Sánchez-Janssen, 2012).

M 104 is of further interest due to the multiple forms of observational
evidence indicating it hosts an active galactic nucleus (AGN). A $10^{9}$M⊙
black hole in the center of M 104 was confirmed by Kormendy et al. (1996), a
mass value further refined to $6.6\times 10^{8}$M⊙ by Jardel et al. (2011).
X-ray and radio observations confirm the presence of a low–luminosity AGN with
powerful jets (Fabbiano & Juda, 1997; Pellegrini et al., 2002, 2003; Nicholson
et al., 1998; Hada et al., 2013; Vlahakis et al., 2008; Krause et al., 2006).
Further analysis of the radio data by Bendo et al. (2006) indicate that the
AGN is the dominant energy source in the central nucleus, while the outer disk
is characterized by an infrared bright ring. This complex structure and
interplay between the active nucleus, unique bulge, and dusty ring makes M 104
an exciting source for studying how an edge–on early type galaxy might appear
different than typical star–forming disk galaxies, providing key indicators
that could identify other similar galaxies.

Table 1: General properties Quantity | Value | Reference
---|---|---
R.A.(J2000) | 12:39:59.4 |
Dec (J2000) | -11:37:23 |
Distance | 31.1 Mpc | McQuinn et al. (2016)
Scale | 70 pc/arcsec |
Inclination | 84.3${}^{o}\pm 0.2^{o}$ | This work
vsys | 1089.2$\pm$1.1 km/s | [LSRK] This work
Type | SA(s)a | de Vaucouleurs et al. (1991)

In order to further delve into the mysteries still surrounding M 104, we
compare different gas and dust tracers from a wide–array of archival datasets.
As individual emission lines and features trace different component of the
interstellar medium (ISM), by compiling multi–wavelength observations of M 104
we can build a more complete picture of what is happening inside this galaxy
and determine how these ISM tracers could identify similar, unresolved sources
in the more distant universe. Figure 1 shows the footprint of the ALMA
(Atacama Large Millimetre/submillimetre Array), VLT/MUSE (Very Large
Telescope/Multi Unit Spectroscopic Explorer), and Herschel/PACS (Photodetector
Array Camera and Spectrometer) observations of M 104. One tracer of particular
interest is the 157.7 $\mu$m line of singly–ionized carbon (the [CII] line).
The [CII] line has risen in prominence as a tracer of SFR not affected by dust
attenuation in distant galaxies thanks to recent surveys like ALPINE (ALMA
Large Program to Investigate C+ at Early Times, Le Fèvre et al., 2020) and
REBELS (Reionization-Era Bright Emission Line Survey, Fudamoto et al., 2022).
As the wavelength of this line is in the far–infrared, it can pass through
dust and gas with minimal attenuation while its role as a key cooling channel
for photodissociation regions (PDRs, Wolfire et al., 2003) provides a physical
cause for the correlation between [CII] luminosity and SFR (De Looze et al.,
2014; Herrera-Camus et al., 2015). Unfortunately, this relationship seems to
break down in the most actively star–forming galaxies (Díaz-Santos et al.,
2017). This is caused by an effect commonly referred to as the “[CII]
deficit,” which describes the decreasing trend in [CII]/FIR in galaxies with
increasing FIR surface brightness (Sutter & Fadda, 2022), star–formation
surface density (Smith et al., 2017), or dust temperature (Croxall et al.,
2012).

Table 2: Early Type Galaxy Sample

Galaxy | RA | Dec | D | $z$ | [CII] | [CII] Luminosity | $\Sigma_{FIR}$ | UVAtten | i | Refb
---|---|---|---|---|---|---|---|---|---|---
| J2000 | J2000 | Mpc |  | ObsIDa | $10^{6}L_{\odot}$ |  $10^{8}L_{\odot}$ kpc-2 |  $10^{6}L_{\odot}$ kpc-2 | deg |
NGC 1266 | 03:16:04 |  $-$02:25:40.0 | 29.9 | 0.00724 |  P 1342214219 | $21.84\pm 0.41$ | $1.93\pm 0.19$ | 82.05 | 34.8 | 1
NGC 3032 | 09:52:08 | +29:14:10.84 | 22.0 | 0.00517 |  P 1342231734 | $8.65\pm 0.03$ | $1.40\pm 0.14$ | 23.52 | 26.4 | 2
NGC 3607 | 11:16:55 | +18:03:06.34 | 18.2 | 0.00310 |  P 1342232317 | $1.48\pm 0.06$ | $2.32\pm 0.23$ | 12.73 | 42.4 | 3
NGC 3665 | 11:24:43 | +38:45:45.82 | 22.9 | 0.00690 |  P 1342234055 | $6.30\pm 0.12$ | $2.13\pm 0.21$ | 2.80 | 39.2 | 4
NGC 4459 | 12:29:00 | +13:58:41.48 | 16.5 | 0.00398 |  P 1342234949 | $1.13\pm 0.10$ | $2.12\pm 0.21$ | 2.38 | 30.9 | 5
NGC 4526 | 12:34:03 | +07:41:58.35 | 14.9 | 0.00206 |  P 1342233262 | $5.13\pm 0.08$ | $1.66\pm 0.17$ | 0.98 | 73.8 | 5
NGC 4636 | 12:42:50 | +00:10:45.07 | 15.1 | 0.00313 |  P 1342236884 | $0.58\pm 0.07$ | $0.56\pm 0.06$ | 9.51 | 64.5 | 2
NGC 4710 | 12:49:39 | +15:09:55.61 | 16.8 | 0.00368 |  P 1342236273 | $10.9\pm 0.05$ | $65.3\pm 6.52$ | 2.21 | 90.0 | 6
NGC 5322 | 13:49:15 | +60:11:25.92 | 21.2 | 0.00594 |  F 07_0105_2 | $0.85\pm 0.05$ | $0.07\pm 0.01$ | 29.61 | 34.5 | 7
NGC 5576 | 14:21:04 | +03:16:15.6 | 25.0 | 0.00502 |  F 07_0105_3 | $1.80\pm 0.21$ | $1.06\pm 0.11$ | 134.8 | 25.5 | 2
NGC 5866 | 15:06:30 | +55:45:47.57 | 14.7 | 0.00252 |  P 1342223744 | $4.10\pm 0.28$ | $59.6\pm 5.96$ | 4.91 | 90.0 | 2

Note. — $a$: P marks Herschel/PACS observations, F indicates SOFIA/FIFI-LS
observations. $b$: References for Distances: (1) Cappellari et al. (2011), (2)
Tully et al. (2013), (3) Humphrey (2009), (4) Theureau et al. (2007), (5)
Villegas et al. (2010), (6) Tully & Fisher (1988), (7) Willick et al. (1997)

Understanding the source of this [CII] deficit is further complicated by the
ubiquity of singly–ionized carbon. As neutral carbon has an ionization
potential of 11.3 eV, well below one Rydberg, C+ can exist in a variety of ISM
environments spanning HII regions to giant molecular clouds (GMCs). By
investigating the [CII] emission from nearby galaxies like M 104, we can
better isolate where within the galaxy the [CII] emission originates, allowing
for further refinement of [CII]–based SFR indicators. Viewing M 104 nearly
edge–on also gives us an unique perspective to study the distribution of
different ISM phases, especially as we can observe the inner and outer edges
of the dusty ring. By comparing the observed [CII] emission to indicators of
unattenuated star formation like H$\alpha$ and FUV, indicators of dust heating
like polycyclic aromatic hydrocarbon (PAH) emission, and indicators of
molecular gas like CO, we can better determine what physical processes lead to
an increase or decrease in the amount of [CII] emission we observe from a
galaxy. This will place important constraints on how [CII] is used to study
the evolving properties of the ISM over cosmic time.

This paper is organized as follows. In Section 2 we describe the archival
datasets used to complete our analysis along with the necessary reductions
used for each. In Section 3 we describe the different methods used to assess
the properties of individual regions across M 104, as well as global
measurements including the inclination angle and the mass of molecular gas in
the ring. Finally, in Section 4 we list the main findings from our analysis.

##  2 Data and Observations

###  2.1 Herschel/PACS spectra

Herschel observations of M 104 were executed as part of the “Key Insights in
Nearby Galaxies: a Far Infrared Survey with Herschel” program (KINGFISH,
Kennicutt et al., 2011). Several hours were needed to scan the entire ring of
dust with PACS (see the red dash-dotted line in Figure 1). In particular, an
observation of 19,060 s (approx 5.3 hours) covered the [CII] and [OIII]
88$\mu$m lines (obsID 1342212603) and an even longer observation of 23,988s
(6.7 hours) was performed to observe the [OI] 61$\mu$m line (obsID
1342213142). In this paper we focus our attention on the [CII] observation
which detected faint emission across the entire observed region. The oxygen
lines, which are much fainter, are mainly detected in the nuclear region.

The standard mode of observation with PACS used chopping between target and
sky to get rid of the varying background radiation during the observation.
However, because the maximum chopper throw was 6’, this method did not work
for extended sources (Poglitsch et al., 2010). In this case, the alternative
“unchopped mode” which does not involve chopping, was used (Fadda et al.,
2016). Data reduction of this mode is known to be problematic because it is
impossible to completely remove transient behaviours of the response of the
detector without using off-target data taken when chopping. Instead, transient
behaviours of the response have to be modeled and removed from the data to
obtain cleaner spectral cubes. As explained in more detail in the appendix A,
the case of M 104 is particularly challenging because of the presence of a
strong transient in the data which lasts for almost the entirety of the
observation. In particular, at the beginning of the observation, the response
is 20% to 25% lower than in at the end. Since the scan is repeated twice, data
from one side of the galaxy are taken at the beginning and at the end of the
observation and are combined by the standard pipeline without correcting the
discrepancy in response. This generates a large gradient in the final data
which is clearly visible in the spectral cubes stored in the Herschel archive.
This does not only affect the level of the continuum but also the shape of the
[CII] line. For this reason, previous studies did not consider these
observations, citing the poor quality of the data (see, e.g., Herrera-Camus et
al., 2015).

Another important point of concern is the flux calibration of the PACS data.
All the data obtained in the standard spectroscopic mode of PACS (chop-nod)
have been normalized to the telescope background which is extremely stable and
well known during the entire mission. The unchopped data conserved in the
Herschel archive instead uses the calibration blocks at the beginning of the
observation for the absolute calibration. These are very sensitive to
transients in the data occurring while the detector points away from sky
regions with fluxes very different from the flux of the actual target. In our
analysis, we use the telescope background to calibrate the data. As shown in
the appendix, this introduces a correction of 50% to 60% with respect to the
calibration obtained using the calibration blocks.

Figure 2: Integrated intensity, velocity, and FWHM maps of the CO, [CII], and
H$\alpha$ emission lines. Sky positions where lines have signal-to-noise
ratios less than 5 are left black.

The data reduction has been done using the unchopped pipeline with transient
corrections available in HIPE 15 (see Fadda et al., 2016) with some important
modifications which are described in detail in the appendix A.

###  2.2 ALMA CO data

We used unpublished archival observations of the ${}^{12}CO_{J=1\rightarrow
0}$ line in the 2.61–2.63 mm wavelength range taken with ALMA in band 3
(program ID: 2018.1.00034.S, P.I. Catherine Vlahakis). The data were taken on
2019 March 29 and cover the whole region observed with [CII] (see Fig. 1). M
104 was observed for a total of 5241 s with the 7 m compact array for an
expected line sensitivity of 16.2 mJy/beam. The spatial beam is an ellipse
with axes of 14$\farcs$3 and 7$\farcs$7 and major axis oriented along the
major axis of the galaxy disk. The spectral resolution is 2.57 km/s.
Velocities are expressed in the LSRK reference frame. No reduction was
necessary since the archival data products already had a quality sufficient
for our study.

###  2.3 MUSE spectroscopy

M 104 was observed with MUSE during the science verification phase (program
60.A-9303(A)) for a total of 5.4 hours. The data quality is excellent: the
median seeing during the acquisition of the data was 1.3 (with a dispersion of
0.3). The reduced data are available directly from the ESO archive as spectral
cubes with 0.2 arcsec spatial pixels. However, some of the observations were
coadded with incorrect offsets producing fake double sources. We decided to
reprocess the 10 observations covering the region observed in [CII] and CO,
shown by the blue dotted line in Figure 1. We used the MUSE pipeline version
2.8.5 and the pre–processed calibration data from the archive (Weilbacher et
al., 2020). Data were processed through the modules object and scipost, and
then combined into a single spectral cube with the module exp_combine. The
final cube was reprojected to a 0.4 arcsec pixel grid which roughly
corresponds to a third of the spatial resolution and therefore allows a good
PSF reconstruction, since the Nyquist-Shannon theorem requires a minimum of 2
pixels per resolution element. The wavelength calibration is done using arc
lamps in standard air. The zero point is refined by using the sky lines
observed in the spectrum. Small shifts are expected since the temperature of
the telescope varies between the arcs and the observations by several degrees.
The spectra of the different observations are shifted by less than 0.2 Å.

To check the quality of the wavelength calibration, we also reduced a few off-
target observations obtained during the same nights in a position close to M
104 by obtaining sky spectra with the module create_sky. We verified that the
corrections were of the same order of those of the M 104 observations (around
0.2 Å) and that the main lines close to the H$\beta$ and H$\alpha$ lines had a
shift of less than 0.01 Å. Finally, a correction of approximately $-28.5$ km/s
is applied to put the spectra into the barycentric reference frame. ALMA and
PACS spectral cubes are set to the kinematic local standard of rest (LSRK). To
directly compare the cubes we changed the spectral reference system to LSRK by
adding 0.9 km/s to the MUSE data (accounting for the angle between the LSRK
vector and the observation direction toward M 104).

Table 3: Inclination angle Filter | Wavelength | Inclination
---|---|---
| $\mu$m | Degs
IRAC Ch4 | 7.870 | 84.6$\pm$0.1
MIPS 24 | 23.70 | 84.6$\pm$0.3
PACS 70 | 71.11 | 84.8$\pm$0.5
PACS 100 | 101.20 | 83.9$\pm$0.4
PACS 160 | 162.70 | 84.2$\pm$0.5
12COJ=1→0 | 2600.75 | 84.3$\pm$0.2

###  2.4 Photometric Data

Near and far-UV fluxes were obtained from archival GALEX images retrieved
using the MAST archive from the Nearby Galaxy Atlas (obsid
2490422561716830208, Gil De Paz et al., 2007). For the visible bands we used
SDSS data from the SDSS DR12 Science Archive Server (Alam et al., 2015).

The near-IR photometry in J, H, and Ks bands was obtained from 2MASS images
retrieved from the 2MASS Large Galaxy Atlas through the IRSA archive (Jarrett
et al., 2020).

The photometry between 3$\mu$m and 24$\mu$m was obtained using WISE,
Spitzer/IRAC and Spitzer/MIPS (24$\mu$m) images from the IRSA archive. The
WISE band 3 image at 11.3$\mu$m was obtained from the all–sky survey (WISE
Team, 2020), while the Spitzer data were obtained from the Spitzer archive
(Spitzer Science Center, 2020) as part of the Spitzer Infrared Nearby Galaxy
Survey (SINGS, Kennicutt et al., 2003).

Far-IR photometric observations were performed by the PACS instrument onboard
Herschel as part of the KINGFISH program (Kennicutt et al., 2011). The 70
$\mu$m, 100 $\mu$m, and 160 $\mu$m level 2 images acquired in this survey were
obtained from the ESA Herschel archive. No further reprocessing was required
for these images as the photometric measurements obtained were sufficiently
accurate for our analysis.

###  2.5 ETG comparison sample

Although M 104 is classified as an SAa galaxy by de Vaucouleurs et al. (1991),
the classification is uncertain given the high inclination which does not
allow us to discern the features of its disk. A study of the kinematical
properties of its globular clusters (Dowell et al., 2014) found that M 104 is
has similar properties to early-type galaxies. In this paper we consider a set
of early-type galaxies (ETGs, in the following), which have been observed
either with PACS on Herschel or with FIFI-LS on SOFIA as a comparison set.
Specifically, the data from these galaxies are included in Sections 3.7 and
3.8, where the [CII] fluxes are compared to the amount of attenuated UV light
and the FIR luminosities.

Figure 3: The ring of the Sombrero galaxy as seen from UV to sub-millimeter
wavelengths. The PSF of each image is shown in the left bottom corner of each
panel. The ellipse fitted to the ring is marked in black. NUV, H$\alpha$, and
[CII] intensity images only have bright spots along the ring and weak
continuous component.

The selected galaxies have a complete set of optical and near- to far-IR
observations to perform the same analysis used with M 104 when comparing their
total infrared and [CII] emission. The list of galaxies is given in Table 2.
All values listed are global measurements, as individual regions in these ETGs
were not resolved in the available data.

###  2.6 Additional Reference Samples

In addition to the ETGs described above, we compare M 104 to nearby,
star–forming galaxies which have similar data available in the literature. As
there are limited local galaxies with measurements of [CII], CO, FIR
luminosity, and PAH emission of similar quality and resolution as the M 104
data described previously, this sample is limited and not all the galaxies
described here can be included in the full analysis. Primarily, we include
data from local star–forming galaxies NGC 7331 (Sutter & Fadda, 2022), NGC
1097 and NGC 4559 (Croxall et al., 2012), M 31 (Kapala et al., 2017), as well
as the KINGFISH survey (Kennicutt et al., 2011). In our comparison between
[CII] and FIR we also include data from the Great Observatories All sky LIRG
Survey (GOALS Díaz-Santos et al., 2017) and a survey of $z\sim 0.02-2$
galaxies from Ibar et al. (2015) to provide further context for our data.

##  3 Results and Discussion

###  3.1 CO, [CII], and H$\alpha$ maps

We fit the CO, [CII], and H$\alpha$ lines in the ALMA, PACS, and MUSE spectral
cubes to produce maps of the line intensity, velocity, and velocity dispersion
using the interactive software sospex (Fadda & Chambers,
2018)111https://github.com/darioflute/sospex. The results are displayed in
Figure 2. The pixels where the signal-to-noise ratio of the line fit was lower
than 5 are left black. In all the maps is evident that the ring of molecular
gas and dust is well defined. However, while the CO map shows almost uniform
emission along the entire ring, the [CII] and H$\alpha$ emissions originate
from multiple individual knots. The regions with peaks of H$\alpha$ emission
are also traced in the [CII] map, taking into account the different spatial
resolution. The apparent higher intensity at the extremes of the ring is due
to a projection effect. In fact, since the galaxy has an high inclination
angle, we see a larger portion of the ring along the line of sight at the two
ends of the ellipse (along the major axis) than in the other regions.

Figure 4: Circular apertures selected for the detailed study of the different
parts of the ring and the inner regions plotted over the H$\alpha$ and [CII]
images in the top and bottom panels, respectively. The independent apertures
uniformely sample the ring and are usually centered on star forming knots. The
aperture diameter corresponds to the [CII] beam. The circles are orange or
green if the region is classified as HII or LIER according to the diagnostic
diagrams (see Section 3.5).

The velocity map has a very well defined gradient across the galaxy. In
particular, taking into account the projection, the angular velocity along the
ring is constant (see the analysis in section 3.4). The map of the velocity
dispersion is rather interesting. It appears that the CO ring has a very low
velocity dispersion at the two extremes of the major axis of the ellipse. By
analyzing the spectra (see examples in Fig. 5), we can see that at the two
ends of the major axis of the ellipse we see a single component of the
molecular gas emission. Therefore, the velocity dispersion is very low. The
vertical extension of the region with low velocity dispersion perfectly
corresponds to the beam of the ALMA observation. As we consider parts of the
ring in other angles, the beam intercepts several molecular clouds with
slightly different velocity. These components are very close in velocity and
difficult to resolve. For this reason, the profile of the line is
approximately Gaussian and its velocity dispersion increases dramatically
along the rest of the ring. The minima of the velocity dispersion are visible
in the parts of the ring along the minor axis of the ellipse where, because of
the projection angle, the smallest arc of the circular ring is covered by the
ALMA beam. In the case of the Herschel observations, the velocity resolution
of the [CII] line is not sufficient to distinguish different components along
the ring. So, the velocity dispersion map appears rather uniform. The velocity
dispersion peaks on the nucleus of the galaxy and in a few regions inside the
ring.

The H$\alpha$ observations have a spectral resolution better than Herschel and
enough spatial resolution to detect single regions with peaks of star
formation. For this reason, MUSE does not see the same projection effects as
ALMA and the velocity dispersion is quite uniform along the ring. In the inner
region, parts of the bar have higher velocity dispersion. The velocity
dispersion peaks in the nuclear and circumnuclear regions.

###  3.2 Galaxy inclination angle

An important property needed to correctly compute the surface brightness of a
spiral galaxy is the inclination of the disk. In literature, the inclination
of M 104 has been measured at values between 84o(Emsellem et al., 1996; Bendo
et al., 2006) and 90o(Jardel et al., 2011). Figure 3 shows the appearance of
the ring at different wavelengths from the GALEX observations in the UV to the
CO observations with ALMA. It is clear that the ring is very well defined by
its dust emission, while the emission from the nucleus becomes much less
dominant when moving into the far-IR. Taking advantage of the clarity with
which the ring of the Sombrero galaxy is visible in infrared and millimeter
images, it is possible to fit an ellipse and compute a more accurate value of
the inclination, based on the hypothesis of a circular ring. We found that the
ring is perfectly fit by an ellipse once the central bulge is masked using the
direct linear least squares fitting method as described by Halir & Flusser
(1998).

We report the results of the fit in the different images in Table 3. The
errors reported have been computed by using different flux thresholds to
select the pixels used in the fitting of the ellipses and can be considered an
estimate of the stability of the fit. The values are within a small range
(0.7o). Since the images which are less disturbed by the nuclear emission are
the PACS 160$\mu$m and the ALMA CO intensity image, we accept the value fitted
in the case of the CO: 84.3${}^{o}\pm 0.2^{o}$. This value is in very good
agreement with the ones reported by Emsellem et al. (1996) and Bendo et al.
(2006).

###  3.3 Aperture spectra

To study the different parts of the ring and its interior we defined a series
of apertures. Such apertures have the diameter of the [CII] beam (10.7
arcsec). We placed them all along the ring usually centered on star forming
regions, locations of which were determined using the peaks of the [CII] and
H$\alpha$ images (see Fig. 4). For this reason, some of the aperture have very
faint H$\alpha$ counterparts or some apertures are not centered on the point
source in the H$\alpha$ image (see, e.g., N7). In the region inside the ring,
we placed an aperture on the position of the nucleus and a series of apertures
on both sides of it.

For each of these apertures we extracted spectra from the MUSE, ALMA, and
Herschel spectral cubes. The same circular apertures have been also used to
define the spectral energy densities (SEDs) to derive the total infrared flux
(see Section 3.6). In the case of ALMA we used apertures with the same center
but with the elliptical shape of the ALMA beam.

In Fig. 5 we show a few significant examples of spectra extracted from three
regions in the ring. We notice in particular that some of the optical spectra
show signatures of high absorption, such as the N11 aperture (spectra in the
right column). In many cases, this strong absorption makes it impossible to
see the H$\beta$ line in emission. The H$\alpha$ and surrounding [NII] lines
are visible in all the extracted spectra. The example of aperture S2 shows a
case where CO has probably multiple components, while the N1 aperture capture
a single component along the line of sight for the CO line which appears
intense and with very low velocity dispersion. Finally, N11 is situated almost
in the direction of center of the ring. Since the aperture covers an arc on
the ring much smaller than that of S2, it includes less components and appears
to have a velocity dispersion intermediate between N1 and S2.

We fit the CO and [CII] spectra using sospex (Fadda & Chambers, 2018) while
for the MUSE spectra we used the software showspectra
222https://github.com/darioflute/showspectra which has been developed for the
analysis of optical spectra.

###  3.4 Kinematics of stars and gas

Figure 5:  Examples of spectra in three apertures. The CO, [CII], and
H$\alpha$ lines are shown in the top, middle, and lower panels, respectively.
The orange line corresponds to the adopted fit.  Table 4: Bands used for SED
Fitting

Filter | Wavelength | Beam | Pixel | $\sigma_{\rm{cal}}$ | Refs
---|---|---|---|---|---
| $\mu$m | arcsec | arcsec |  |
GALEX_FUV | 0.152 | 4.2 | 1.5 | 0.05 mag | 1
GALEX_NUV | 0.227 | 5.3 | 1.5 | 0.03 mag | 1
SDSS_$u$ | 0.354 | 1.4 | 0.4 | 2% | 2
SDSS_$g$ | 0.477 | 1.4 | 0.4 | 2% | 2
SDSS_$r$ | 0.632 | 1.4 | 0.4 | 2% | 2
SDSS_$i$ | 0.762 | 1.4 | 0.4 | 2% | 2
SDSS_$z$ | 0.913 | 1.4 | 0.4 | 2% | 2
2MASS_$J$ | 1.235 | 2.9 | 2.0 | 0.03 mag | 3
2MASS_$H$ | 1.662 | 2.8 | 2.0 | 0.03 mag | 3
2MASS_$Ks$ | 2.159 | 2.9 | 2.0 | 0.03 mag | 3
IRAC_1 | 3.550 | 1.66 | 1.2 | 1.8% | 4
IRAC_2 | 4.490 | 1.72 | 1.2 | 1.9% | 4
IRAC_3 | 5.730 | 1.88 | 1.2 | 2.0% | 4
IRAC_4 | 7.870 | 1.98 | 1.2 | 2.1% | 4
WISE_3 | 11.56 | 6.5 | 2.75 | 4.5% | 5
MIPS_24 | 23.70 | 4.9 | 2.5 | 4.0% | 6
PACS_70 | 71.11 | 5.6 | 3.2 | 5% | 7
PACS_100 | 101.20 | 6.8 | 3.2 | 5% | 7
PACS_160 | 162.70 | 10.7 | 6.4 | 5% | 7

Note. — Beam sizes for SDSS and 2MASS are median seeing values. References:
(1) Morrissey et al. (2007), (2) Padmanabhan et al. (2008), (3) Skrutskie et
al. (2006), (4) Reach et al. (2005), (5) Jarrett et al. (2011), (6)
Engelbracht et al. (2007), (7) Balog et al. (2014)

Figure 6:  Line-of-sight velocity along the ring for the optical, [CII], and
CO emission as a function of the projected distance from the galaxy center.
The error bars correspond to 3-sigma errors. The different measurement sets
have been spaced for clarity by 100 km/s intervals. In the legend, XC and EM
stand for cross-correlation and emission lines, the two methods used to
estimate redshifts from the optical spectra. The inset displays the ellipses
of confidence for the 4 linear fits at the 1, 2, and 3-sigma levels (39%, 86%,
and 99% level of confidence for two variables, see e.g. Wang et al., 2015).
Table 5: Parameter values for CIGALE modules

Name | Values
---|---
| SFH Delayed
tau_main [Tyr] | 0.5, 1.1, 1.7, 2.6, 3.9, 8.8, 13, 20
age_main [Tyr] | 4.5, 7, 9.5, 12
f_burst | 0.0
| SSP
Model | Bruzual & Charlot (2003)
imf | 1 (Chabrier)
| Nebular Emission
logU | -3.0
| Dust Attenuation
Model | Calzetti et al. (2000)
E_BV_nebular [mag] | 0, 0.005, 0.0075,
| 0.011, 0.026, 0.058,
| 0.2, 0.44, 0.66, 1
uv_bump_amplitude | 0, 1.5, 3 (Milky Way)
powerlaw_slope | [-0.5, 0], $\delta=0.1$
Name | Inner | Ring
| Dust Emission
Model | Draine et al. (2014)
qpah | 0.5, 1.1 | 0.5, 2.5, 4.6, 6.6
umin | 0.1, 0.3, | 0.1, 0.5,
| 0.5, 1.2, 2 | 1, 2.5, 5
gamma | 0, 0.001, | 0.001, 0.002,
| 0.008,0.03, | 0.01, 0.016, 0.03
| 0.13, 0.25, 0.5 | 0.06, 0.13
| AGN Emission
Model | Fritz et al. (2006)
f_AGN | 0.1, 0.25, 0.5 | 0
psy | 0.001, 50, 90 | 50

Note. — Multiple values for a parameter define a grid of models. Values of
unlisted parameters are left at the CIGALE defaults.

CO, [CII], and optical spectra lines give information about the kinematics of
the different components of the ring. In particular, the CO emission is
directly related to molecular gas, [CII] is mainly emitted by molecular and
atomic gas, the H$\alpha$ emission line is linked to ionized gas, and the
absorption lines in the optical spectra are related to stars (see, e.g., Sofue
& Rubin, 2001). The kinematics of these different components can be visualized
by plotting the line-of-sight velocities as a function of the projected
distance from the center of the galaxy. In fact, assuming a circular ring
rotating with the angular velocity $\Omega$, the component of the velocity
along the line of sight is:

$v_{los}=r_{0}\Omega\cos\phi+v_{sys}=r_{p}\Omega+v_{sys},$ (1)

where $r_{0}$ is the radius of the ring in kpc, $r_{p}$ is the projected
distance from the galaxy center of a point in the ring at the angle $\phi$,
and $v_{sys}$ is the systemic velocity. We therefore expect a linear
relationship between the velocity along the line of sight and the projected
distance from the galaxy center with slope equal to the angular velocity
$\Omega$ and intercept corresponding to the systemic velocity $v_{sys}$.

For each component we used a different technique to obtain accurate
measurements of velocities.

In the case of the the ALMA and Herschel data, we fit the CO and [CII] lines
using sospex. We fit the [CII] line using a Voigt function which accurately
describes the profile of the line. In the case of the ALMA data we opted for
fitting Gaussian functions, since the apertures across the ring intercept
several molecular clouds with slightly different velocities, but these are
unresolved. This observational effect broadens the emission line and makes the
Gaussian model a better fit for the CO data.

In the case of the MUSE data, we measured the redshifts from the optical
spectra of the selected apertures using two methods: cross-correlation with
SDSS templates (mainly based on absorption features) and measurement of
emission lines (mainly H$\alpha$, [NII], [SII], and occasionally [OIII]5007Å
and H$\beta$). Since the SDSS templates are expressed in vacuum wavelengths
and the MUSE spectra in air wavelengths, we converted the MUSE spectra to
vacuum wavelengths for the cross-correlation using the IAU standard conversion
specified in Morton (1991). The redshift errors for the cross-correlation
estimates were computed as in Tonry & Davis (1979). The redshifts based on the
emission lines were computed through the mean weighted with the fitting errors
of the lines.

Figure 6 shows the line-of-sight velocities of the spectra in the different
apertures along the ring as a function of their projected distance from the
galaxy center. The four different colors refer to measurements of the CO line,
[CII] line, and the two ways of measuring the redshift of the optical spectra:
EM for emission lines, and XC for cross-correlation. To better show the linear
fit of the different set of points we spaced them by 100 km/s intervals. The
data of the [CII], CO, and optical spectra give compatible values for slope
and systemic velocity inside the errors. In particular, the measurements with
the lowest errors (CO lines and optical emission lines) are almost identical.
The systemic velocity from the optical emission line is $(1089.1\pm 1.8)$
km/s, while the one based on CO data is $(1089.2\pm 1.1)$ km/s. These values
agree very well with the measurement from Lavaux & Hudson (2011) who reported
a systemic velocity of $(1090\pm 5)$ km/s. The four different methods also
provide very similar values for the slope of the line, which corresponds to
the angular velocity of the galaxy rotation $\Omega$. The absolute values of
the angular velocity for the CO data and the optical emission lines, which
have the smallest errors, are $(35.0\pm 0.1)$ km s-1kpc-1 and $(35.2\pm 0.2)$
km s-1kpc-1, respectively. Therefore, we have an almost perfect agreement
between the kinematic of the stars and that of the interstellar medium. This
is not always the case since in several galaxies these two components have
different rotational patterns (see, e.g. Williams et al., 2021; Su et al.,
2022).

Figure 7: Emission line diagnostic diagrams used to identify LIER and star-
forming regions. The regions are labelled as Seyfert (Sy), HII, Composite
(Comp), and LIER. Median errorbars are shown in the right bottom corner.

###  3.5 LIER and HII regions

The spectra extracted from the MUSE spectral cube for the apertures defined in
Fig. 4 have been also used to study the properties of the respective regions.
Many spectra, especially those inside the ring, show heavy absorption. The
Balmer lines (H$\alpha$ and H$\beta$) were always fit using a component in
absorption and one in emission. H$\alpha$, [NII], and [SII] lines are visible
in all the spectra. In contrast, due to attenuation, the [OIII] and H$\beta$
lines are not always measurable in emission. Figure 7 shows several diagnostic
diagrams obtained using the measurements of the emission lines. The typical
diagnostic diagrams which make use of the H$\beta$ emission line are not
possible for many of the spectra. In the cases where this line is barely
visible, we show 3-$\sigma$ lower limits. To determine the classification for
all the defined apertures, we used two alternative diagnostic diagrams
developed for weak line galaxies as described in Cid Fernandes et al. (2010)
which are shown in the two bottom panels of Fig. 7. Following the example of
Belfiore et al. (2016), we named the region shaded in green as LIER (low-
ionization emission-line region). The ionizing photons in such regions were
originally attributed to central, low-luminosity active galactic nuclei and
called LINERs (low-ionization nuclear emission-line regions). However, in the
case of passively-evolving galaxies with old stellar populations, hot post-
asymptotic giant branch stars are now considered to be the main source of
ionizing photons, especially when outside of the nuclear region.

Figure 8:  Two examples of the spectral energy distribution fits produced by
CIGALE: nucleus (top) and the S1 region on the ring (bottom). Data are marked
by blue points and the total model flux is plotted in gray. The unattenuated
light from the old and young stellar populations is shown in magenta and cyan,
respectively. The dust component is displayed in red, while the AGN emission
in plotted in orange. In the nucleus, the young stellar population is
negligible and the AGN produces a large percentage of the near- to mid-
infrared flux. On the contrary, in the ring there is a substantial population
of young stars and the IR emission is well–fit without any AGN component.

Regardless of the diagnostic used, the majority of the spectra lie in the LIER
region. In particular, the apertures defined inside the ring have the highest
[NII]/H$\alpha$ and [OIII]/H$\alpha$ ratios. In this inner region al least
part of the ionizing photons could be due to the central AGN (see, e.g., Bendo
et al., 2006). The few apertures with spectra in the star-forming region
(shaded in light orange) have been marked with orange circles in Fig. 4. These
apertures correspond to regions with knots of star formation visible in the
H$\alpha$ image. In the following figures, apertures in the HII/Comp and LIER
regions as determined used the bottom panel of Figure 7 are marked with orange
and green symbols, respectively.

###  3.6 SED Modeling

Spectral energy distribution (SED) fitting was performed using the Code for
Investigating Galaxy Emission, or CIGALE (Boquien et al., 2019). This code
assumes energy balance between light emitted in the infrared and absorbed in
the UV to produce each model SED. The main properties of bands used to build
the SED is detailed in Table 4. All of the available photometry described in
Section 2.4 was first smoothed to a common resolution of 10$\farcs$7, the
native resolution of the PACS spectroscopy at 158 $\mu$m. Smoothing was
completed using a Gaussian for the FUV–Ks band images and the kernels
developed in Aniano et al. (2011) for the IRAC–PACS images. Fluxes were
extracted for each individual region across the disk of M 104. Additional Far-
IR photometery is available from the SPIRE instrument on Herschel was not
included in the SED analysis due to the larger beam of even the
shortest–wavelength SPIRE band. The SPIRE 250 $\mu$m data has a PSF of $\sim
18$”, much larger than the 10$\farcs$7 PSF of the PACS 158 $\mu$m data. Using
this larger beam would make it impossible to extract fluxes for the individual
HII regions seen in the MUSE data. Since the SEDs of the regions across the
ring of M 104 peak shortwards of 160 $\mu$m, temperatures and masses of the
colder dust should be relatively well constrained without the 250 $\mu$m
measurements. With this in mind, we choose not to include the 250 $\mu$m data
and retain the highest possible spatial resolution, even if by using the 250
$\mu$m data we could have obtained more accurate estimates of the total far-IR
flux.

Due to the presence of an active galactic nucleus (AGN) in the center of M
104, we used two separate parameter ranges to complete the SED fits. Regions
interior to the ring were modeled adding a component of AGN emission, while
the regions along the ring were modeled assuming no AGN component. For both
region sets, we use the Bruzual & Charlot (2003) stellar population model with
a Chabrier (2003) IMF and the Draine et al. (2014) dust models. We set the
metallicity at $Z=Z_{\odot}$. The SFH delayed model, which we use for all
regions, models the star–formation history (SFH) as beginning at time $t_{0}$
and peaking at a later time $\tau$, followed by a smooth, exponential decay in
the star–formation rate. We do not include an additional burst in star
formation at a later point, nor do we include any quenching. tau_main and
age_main set the e-folding time and the age of the main stellar population in
this model, respectively. The dust attenuation is modeled using the Calzetti
et al. (2000) attenuation curve. The dust emission is modeled using Draine et
al. (2014) as this model contains detailed information about the PAH emission.
In this model, qpah is the mass fraction of PAHs, umin sets the minimum
interstellar radiation field heating the dust, and gamma is the fraction of
dust heated by a radiation field greater than umin. Finally, the AGN component
in the inner regions is fit using the Fritz et al. (2006) model where f_AGN is
the AGN fraction and psy is the angle between the equatorial axis of the AGN
and the line of sight. The complete set of model parameters for the two
regions is listed in Table 5. Two examples of SED fits, one in an inner region
(the nucleus) and one along the southern part of the ring (S1) are shown in
Figure 8. All the ETGs were fit using a similar method as the interior
regions, with some adjustments to accommodate the limited availability of
archival photometry for some of the sources.

###  3.7 [CII] and UV attenuation

Figure 9: Surface brightness of the [CII] line plotted as a function of the
attenuated UV light from the CIGALE SED fits. M104 data are color–coded based
on BPT diagram diagnostic, with orange being star–forming, and green being
LIERs–dominated. The LIERs are further divided into regions interior to the
ring (dark green) and along the ring (light green). Comparison data from the
nearby galaxy NGC 7331, our ETG sample, and M 31 are shown as grey, magenta,
and purple symbols, respectively. The global M104 measurement is shown as a
magenta star. Median errorbars, scaled to be the correct size on this plot at
the locus of the data from M 104, are shown in the right bottom corner.

If [CII] emission is the primary cooling channel for the ISM, it would follow
that the strength of the [CII] emission would be directly related to tracers
of heating under the assumption of thermal stability. This relationship is
especially relevant to the application of [CII] emission as a SFR indicator.
One particularly reliable tracer of gas heating is the amount of attenuated UV
light (E $=6-13.6$ eV), as this high energy light is a major heating source in
HII regions and PDRs (Kapala et al., 2017). The amount of attenuated UV light
can be estimated with the CIGALE SED fits, which predict the attenuated light
from the modeled populations of young and old stars. For the regions in our
sample, we use the Calzetti et al. (2000) dust attenuation model. The modeled
attenuated light is then integrated from $\lambda=91.2-206.6$nm to determine
the total amount of attenuated UV light. The results of this analysis are
shown in Figure 9, where the attenuated UV light is plotted against the [CII]
surface brightness ($\Sigma$[CII]). For comparison, the data from resolved
regions in NGC 7331 (Sutter & Fadda, 2022) and M 31 (Kapala et al., 2017)
along with our sample of ETGs are shown as gray, purple, and magenta points,
respectively. The global measurement for M 104 is shown as a magenta star, for
a direct comparison with the ETG global values.

Comparing these three samples with M 104, we see clear differences. While the
resolved measurements from NGC 7331 and M 31, two star–forming spiral
galaxies, fall along a linear relationship with a slope of 0.013, the majority
of the regions within M 104 and a subset of the ETGs fall well above this
relationship. The two ETGs that lie in a similar space to NGC 7331 are NGC
1266 and NGC 3032, which have both been suggested to host an AGN (Alatalo et
al., 2011; Capetti & Balmaverde, 2005). In addition, NGC 1266 shows signs of
an outflow, which could be producing shock heated gas, increasing the [CII]
emission above that of the other ETGs (Alatalo et al., 2011). The three ETGs
in the right corner of this plot are NGC 4636, 5322, and 5576. It is less
clear why this subsample of ETGs fall in this corner, but this could be due to
differences in modeling when considering resolved and global galaxy
measurements. The differences between M 104 and the remaining ETGs and the
resolved measurements from NGC 7331 and M 31 suggests that the primary heating
source differs between M 104 and other early–type galaxies and star–forming
galaxies. While young O and B stars provide the main heat source in NGC 7331
and M 31, M 104 has very little ongoing star formation leading to the dominant
source of heat being evolved stars. This would explain the lower values of
attenuated UV light across M 104, as there is little UV light to be attenuated
to begin with.

###  3.8 [CII] and total infrared luminosity

Figure 10: The [CII]/FIR ratio plotted as a function of far-IR surface
brightness ($\Sigma_{FIR}$). The regions within M 104 are color–coded based on
their position in the BPT diagram as in previous figures. The comparison data
from NGC 7331 (Sutter & Fadda, 2022), KINGFISH (star–forming regions in local
galaxies from Sutter et al. (2019)), $z\sim 0.02-0.2$ galaxies from Ibar et
al. (2015), and local U/LIRGS (Díaz-Santos et al., 2017) are shown in gray,
light gray, brown, and light brown, respectively. We also include global
measurements from local early type galaxies (ETGs) in magenta, and the global
measurement of M104 as a magenta star.

In order to explore the relationship between [CII] emission and dust heating,
we show the [CII]/FIR plotted against the FIR surface density in Figure 10.
The FIR fluxes were computed by integrating the modelled SEDs from
$\lambda=8-1000\mu$m. The FIR surface brightness was then determined by
dividing the FIR luminosity by the deprojected area of one region. To compare
the regions within the M 104 to previous studies of the [CII]/FIR
relationship, we also plot the data from the resolved regions across the disk
of nearby star–forming galaxy NGC 7331 (dark gray points, Sutter & Fadda,
2022), resolved star–forming regions from the “Key Insights in Nearby
Galaxies: a Far-Infrared Survey with Herschel” (KINGFISH, light gray points,
Sutter et al., 2019), global measurements of $z\sim 0.02-0.2$ galaxies (brown
diamonds, Ibar et al., 2015), and global measurements from local luminous
infrared galaxies (LIRGS) from the Great Observatory All–Sky LIRG Survey
(GOALS, tan diamonds Díaz-Santos et al., 2017). In order to perform a uniform
analysis of these diverse data sets, we deprojected the infrared surface
brightness measurements reported in Ibar et al. (2015) and Díaz-Santos et al.
(2017) by multiplying by a factor of $1/\cos{i}$, where $i$ is the galaxy’s
inclination. For the sources included in Ibar et al. (2015), the inclinations
were determined by fitting ellipses to the PANSTARRs $r$ band images of each
galaxy and assuming $\cos{i}=b/a$. For the galaxies in the GOALS sample, the
inclinations were taken from Kim et al. (2013). With these updated
$\Sigma_{FIR}$ measurements, we see a linear trend between [CII]/FIR and
$\Sigma_{FIR}$ across three orders of magnitude in $\Sigma_{FIR}$ for our
comparison samples.

Figure 11:  The [CII]/PAH values plotted as a function of $(\nu
F_{\nu})_{70\mu m}/(\nu F_{\nu})_{100\mu m}$. The points from M 104 follow the
color scheme of previous plots. Resolved measurements from three nearby
star–forming galaxies, NGC 7331, NGC 4559, and NGC 1097 (Sutter & Fadda, 2022;
Croxall et al., 2012) are shown as gray points. Median errorbars for M104 are
shown on the left.

By comparing our measurements of [CII]/FIR across M 104 to the trends measured
in other nearby galaxies, it becomes clear that M 104 is an outlier with
significantly lower values of [CII]/FIR for a given $\Sigma_{FIR}$. In order
to determine what unique properties of M 104 might be causing it to fill this
otherwise empty area of this plot, we consider similar behavior observed in
our ETG sample (see Section 2.5 for more information about this sample). The
global [CII]/FIR and $\Sigma_{FIR}$ points from this sample are displayed as
magenta diamonds in Figure 10, while the global measurement for M 104 is shown
as a magenta star for a consistent comparison. A subset of the ETG sample does
fall in a similar space as the data from M 104, suggesting that the cause of
the observed low values of [CII]/FIR in M 104 is shared in other ETGs. The two
ETGs that fall among the gray points indicating star–forming galaxies are NGC
1266 which has an outflow and hosts an AGN (Alatalo et al., 2011), NGC 3032
which has some observable spiral structure as well as an AGN (Capetti &
Balmaverde, 2005), and NGC 4710, a nearly edge on galaxy which makes
measurements of $\Sigma_{FIR}$ more uncertain. This could suggest that other
mechanisms are exciting the [CII] emission in these three galaxies, making
them outliers from the rest of the ETG sample.

With the additional information from the MUSE data, we can also subdivide the
regions in M 104 based on what the dominant source of ionizing radiation is
(see Section 3.5 for details). In this figure, the regions in M 104 classified
as HII or composite are orange and regions that fell in the LIER category are
green. We further subdivide the LIER category into regions along the ring
(light green diamonds) and regions interior to the ring (dark green diamonds),
with the nucleus marked with a dark green star. Using these diagnostics, we
see that the regions dominated by star formation have on average the highest
[CII]/FIR values, while those classified as LIERs have the lowest. Studies of
resolved BPT diagnostics have shown that regions classified as LIERs are
dominated by emission from an older stellar population, predominantly AGB
stars (Belfiore et al., 2016; Zhang et al., 2017). This could drive the
[CII]/FIR measurements lower as AGB stars will heat the dust, producing FIR
emission, while emitting very little radiation with energy high enough to
ionize carbon, limiting the production of the [CII] line. Within the LIER
sample, the regions in the interior show slightly higher [CII]/FIR values than
those in the ring, which could suggest some additional [CII] emission excited
by the central AGN.

Figure 12: The [CII]/PAH values, now plotted against the ratio of the 7.7
$\mu$m and 11.3$\mu$m PAH features, an indicator of PAH charge. Same color
scheme as previous plot. Histograms above and to the right show the
distribution of the different types of regions in M 104 with respect to the
star–forming galaxy sample. Median errorbars for the data from M104 are shown
in the lower-right corner.

###  3.9 [CII] and PAH emission

Studies have suggested that comparing [CII] emission to the emission from
polycyclic aromatic hydrocarbons (PAHs) might provide an improved indicator of
the photoelectric heating efficiency in PDRs (Croxall et al., 2012). As PAHs
provide the bulk of free electrons in PDRs, the emission from these small dust
grains provide a key indicator of the conditions within PDRs where much of the
[CII] emission is produced (Sutter et al., 2019; Tarantino et al., 2021). By
comparing the [CII] and PAH observations across M 104 we can therefore
determine how the PDR conditions might be affecting the strength of the
observed [CII] emission.

As the 7.7 $\mu$m and 11.3 $\mu$m PAH features are nicely covered by the IRAC4
and WISE3 bands, respectively, we use the fluxes from these bands along with
the results of the SED fits to estimate the PAH fluxes. To remove
contributions from stars, large dust grains, and AGN emission from these
bands, the modelled flux from each of these components is summed, convolved
with the transmission function for the specified band, and then subtracted
from the observed flux. The remaining emission is then assumed to be only the
emission from the 7.7 and 11.3 $\mu$m PAH emission features, which are added
together to estimate the total PAH emission. The results of this analysis are
used to compare the [CII] and PAH emission across M 104.

Figure 11 shows the [CII]/PAH values plotted as a function of $(\nu
F_{\nu})_{70\mu m}/(\nu F_{\nu})_{100\mu m}$, an indicator of dust
temperature. For comparison, resolved regions from star–forming galaxies NGC
1097 and NGC 4559 (Croxall et al., 2012) as well as NGC 7331 (Sutter & Fadda,
2022) are shown as gray points. The ETG sample is not included in these
measurements due to uncertainties in our PAH estimation when considering
global measurements. Specifically, the majority of the ETGs have sparse
coverage in the mid– to far–infrared photometric bands, making the precise
determination of the fraction of the flux from PAHs in the available IRAC4 and
WISE3 fluxes prone to significant errors.

Unlike the [CII]/FIR measurements shown in Figure 10, we see that there is
some overlap between the regions in M 104 and regions in the star–forming
galaxies. This overlap includes all of interior regions classified as LIERs
and the majority of the regions classified as HII–dominated using the BPT
classification mechanism. The similarity between M 104 and star–forming
galaxies suggests that changes to the PAHs are not the driving mechanism for
the observed differences in [CII]/FIR, and that the ISM conditions that
suppress [CII] emission are likely also limiting the PAH emission; either
through the destruction of small grains near an AGN (Langer & Pineda, 2015) or
a lack of photons with energies high enough to excite the PAHs (Malhotra et
al., 2001; Smith et al., 2017).

In addition to comparing the [CII]/PAH emission to the dust temperature, we
also compare to the ratio of the 7.7$\mu$m and 11.3$\mu$m PAH features, an
indicator of average PAH charge (Draine et al., 2021). This is shown in Figure
12. Again, we see overlap between the regions from M 104 and the comparison
sample of resolved star–forming galaxies. This is especially true for regions
classified as LIERS inside the ring. One major difference between the data
from M 104 and the star–forming sample is the range of 7.7/11.3 we measure.
While the regions from the three star–forming galaxies are fairly evenly
distributed from $\sim 0-4$, regions from M 104 all fall between 0.5 and 2.2,
implying a much more uniform population of PAHs across the disk. The range in
charges is even more constrained when we consider only regions along the ring
(light green and orange points) or only regions interior to the ring (dark
green points), suggesting that the population of PAHs is remarkably consistent
within these two environments. The lack of 7.7/11.3 values above 2.5 shows
that the PAHs within M 104 have a lower charge on average, and therefore PAH
grain charging is likely not the cause of the low [CII]/FIR values observed in
Figure 10.

###  3.10 Measuring the $H_{2}$ Mass

We can estimate the total mass of molecular hydrogen in the ring by
integrating the total CO emission. We assume a factor 2 correction to account
for the likelihood that the 12CO1→0 line will become optically thick in dense
star–forming regions (Hughes et al., 2017). By applying the conversion from
Eq. 3 from Bolatto et al. (2013), we find out that the total molecular
hydrogen mass of the ring of M 104 is $0.9\times 10^{9}$ M⊙. This places M 104
on the high end of molecular hydrogen mass when compared to the early–type
galaxies from the ATLAS3D catalog (Lagos et al., 2014). On the other hand, the
mass of molecular hydrogen in the 10 kpc ring of M 104 is approximately half
of the total mass of molecular hydrogen found in the 5 kpc ring of our own
galaxy ($\approx 2\times 10^{9}$ M⊙, Clemens et al., 1988). So, although M 104
cannot be classified as a star-forming galaxy, there is a substantial amount
of molecular hydrogen contained in the ring of M 104.

Figure 13: CO luminosities plotted against the [CII] luminosities, both
normalized by the FIR luminosity. Median errorbars for the data from M104 are
shown in the lower left corner.

###  3.11 [CII] and CO emission

As [CII] emission can originate in a variety of environments including
molecular gas, we compare the [CII] and 12COJ=1→0 (CO, hereafter) in regions
where CO was detected. These regions primarily consist of regions along the
ring as well as one region near the nucleus with a weak CO detection (region
R1, see Figures 2 and 4). As the CO flux in region R1 is much lower than in
the ring and approaching the detection limit of ALMA, we do not include it in
our analysis. This leaves only regions along the ring with significant [CII]
and CO detections, so the following analysis will not include the interior
regions discussed in previous sections. It is apparent by considering the
[CII] and CO maps that the distribution of [CII] and CO are very different in
M 104, suggesting that the majority of the [CII] emission is not tracing the
molecular gas phase of the ISM in this galaxy.

In order to further compare the [CII] and CO emission, we plot the the [CII]
against the CO emission, both normalized by FIR luminosity, in Figure 13. We
choose to plot the normalized fluxes instead of comparing the [CII] and CO
luminosities because the comparison between [CII]/FIR and CO/FIR is often used
as an input in PDR models, making this plot a good comparison for other
studies (see e.g. Madden et al., 2020). In addition, as CO is only observed
around the ring and has a relatively constant flux around ring, the direct
comparison of the two lines is dominated by scatter and there is little
observed relation between the two line luminosities. As in previous figures,
data from NGC 7331 is shown as a comparison sample. By examining the
distribution of the points from NGC 7331 and M 104, it is clear M 104 is
proportionally much lower in both [CII] and CO emission. It is also notable
that while the CO/FIR values from NGC 7331 are distributed over a range of
$3.9\times 10^{-6}-6.7\times 10^{-5}$, M 104 only covers a range of $1.4\times
10^{-6}-5.6\times 10^{-6}$, which is both lower and much more constrained than
NGC 7331. This is also apparent in the histogram plotted above Figure 13,
where we can see the small range of the data from M 104, and that there is
little overlap with the data from NGC 7331. This is primarily due to the
relatively constant CO fluxes across the ring (see the top panel of Figure 2).

Although the [CII]/FIR values in M 104 are also lower than those in NGC 7331,
there is some overlap between the two galaxies, especially in regions in M 104
that are classified as star–forming using the emission line diagnostics. This
difference between the [CII] and CO behavior suggests that while the [CII]
emission is tracing the small amount of star–formation still occurring in M
104, the molecular gas as traced by CO emission is not. For this reason, we
choose to not include PDR models on this plot, as it seems the CO emission may
not be tracing this phase of the ISM.

Figure 14: A Kennicutt-Schmidt plot with star–formation rate surface density
plotted against the molecular gas surface density. The relationship for sub-
Kpc regions in starforming galaxies from Bigiel et al. (2008) is shown as a
blue line, with blue shading representing the 3$\sigma$ error on the slope.
Data for NGC 7331 (Sutter & Fadda, 2022) are marked with gray dots. Median
errorbars for the data from M104 (orange and green diamonds) are shown as a
black cross in the lower part of the plot.

To further test the disconnect between CO and star formation in M 104, we plot
the surface density of star formation vs the surface density of molecular gas
in Figure 14. This plot is commonly referred to as a Kennicutt–Schmidt plot,
and the proportional trend between $\Sigma_{\rm{SFR}}$ and $\Sigma_{H_{2}}$
demonstrates how gas in the ISM is the fuel for ongoing star formation
(Kennicutt & Evans, 2012).

For SFR values we used the CIGALE estimates which take into account the entire
SED from the far-IR to the far-UV. The H2 gas mass is determined by measuring
the molecular gas mass for each region using the method described in Section
3.10. Both the H2 gas mass and the SFR are converted to surface densities by
dividing by the deprojected area of the aperture used in the measurement. For
comparison, we plot the relationship from Bigiel et al. (2008) which
investigated the Kennicutt-Schmidt relationship at sub-Kpc scale for several
star-forming galaxies as a blue line, with the dispersion represented using
blue shading, as well as the relationship for regions of the Milky Way analog
NGC 7331 (Sutter & Fadda, 2022). Figure 14 clearly shows that there is no
correlation between $\Sigma_{H_{2}}$ and $\Sigma_{\rm{SFR}}$ in the regions
within M 104. This supports the conclusion that the majority of the CO
emission is not tracing the ongoing star formation, and therefore is not a
useful indicator of PDR conditions.

##  4 Summary and Conclusions

We presented the analysis of unpublished archival observations of the galaxy
Messier 104, also known as the Sombrero galaxy, obtained with ALMA, Herschel,
and MUSE. These observations have been compared to a wealth of archival
photometric observations from the UV to the far-IR. The measurements used in
the Figures are available in Appendix B (see Tables 6). The main results of
our study can be summarized as follows:

  * •

The emission of dust and molecular gas is very uniform all along the ring. In
particular, the ring is clearly defined from 8 $\mu$m to the far-IR. The CO
emission from molecular gas is mainly confined to the ring with the exception
of a weak emission from a circumnuclear region, while dust emission is also
visible in the nucleus and in the region inside the ring. The [CII] and
H$\alpha$ emission are visible all around the ring but they appear less
uniform, with intense spots linked to knots of star formation.

  * •

The kinematics of stars and gas along the ring is extremely regular. The
ionized gas traced by the H$\alpha$ emission as well as the gas traced by CO
and [CII] have the same rotational velocity inside the measurement errors. The
velocity dispersion is constant along the ring, while the inner part of the
disk has a larger velocity dispersion.

  * •

Through comparisons with a set of early–type galaxies observed with Herschel
and SOFIA, we find that both M 104 and a sub–sample of the early–type galaxies
populate a region of the [CII]/FIR vs $\Sigma_{FIR}$ under the locus of star-
forming galaxies. This is likely due to the fact that although the old stellar
population heats the dust which emits continuum far-IR radiation, it is not
able to excite the [CII] line, leading to the lack of correlation between
[CII] and FIR emission and therefore to low [CII]/FIR values.

  * •

The study of the [CII] emission to dust emission and gas heating indicators
such as UV attenuation, far-IR total emission, and PAH emission, show that M
104 behaves like early-type galaxies. However, the inner region and the parts
of the ring with visible star formation in H$\alpha$ have higher [CII]/FIR and
[CII]/PAH ratios, closer to those of star-forming galaxies.

  * •

The total mass of molecular hydrogen in the ring of M 104 is $0.9\times
10^{9}$ M⊙, a value intermediate between typical early-type galaxies and the
molecular hydrogen content of the ring of our own galaxy.

  * •

While the [CII] emission is comparable to those of faint star-forming regions
in other galaxies, the CO emission is much lower. The mass of H2 derived from
the CO emission does not correlate with the star formation along the ring. It
is therefore clear that the molecular hydrogen of the ring is not converted
efficiently into stars and that most of the [CII] emission is probably not
related to molecular gas, but rather to ionized and neutral atomic gas.

The study of this iconic galaxy shows how a direct interpretation of CO and
[CII] emission should be used with caution in the case of galaxies with low
star formation. The lack of correlation between CO emission and star formation
as well as the fact that the [CII] emission is probably not linked to the
reservoir of molecular hydrogen should be taken into account when studying the
evolution of early-type galaxies in high redshift surveys.

The authors are grateful to Dr. Yuguang Chen for his help in interpreting the
MUSE data and to the anonymous referee for the numerous and detailed
suggestions which greatly improved the quality of the paper. This research is
based on data and software from: the SOFIA Observatory, jointly operated by
USRA (under NASA contract NNA17BF53C) and DSI (under DLR contract 50 OK 0901
to the Stuttgart University); Herschel, an ESA space observatory with
instruments provided by European-led P.I. consortia and important NASA
participation; the Spitzer Space Telescope, operated by JPL/Caltech under a
contract with NASA; WISE, a joint project of UCLA and JPL/Caltech, funded by
NASA; the SDSS survey, funded by the Sloan Foundation, participating
institutions, NSF, DOE, NASA, Monbukagakusho (Japan), Max Planck Soc.
(Germany), and HEFCE (UK); 2MASS, a joint project of the Univ. of
Massachusetts and IPAC/Caltech, funded by NASA and NSF; GALEX, a NASA small
explorer, whose archive is hosted by HEASARC; MUSE observations collected at
the ESO observatories under program 60.A-9303(A); data ADS/JAO.ALMA#
2018.1.00034.S from ALMA, a partnership of ESO, NSF (USA), NINS (Japan), NRC
(Canada), MOST and ASIAA (Taiwan), and KASI (Rep. of Korea), in cooperation
with the Rep. of Chile. The Joint ALMA Observatory is operated by ESO,
AUI/NRAO and NAOJ. NRAO is a NSF facility operated under cooperative agreement
by Associated Universities, Inc. Partial financial support for this project
was provided by NASA through the award # SOF-06-0032 issued by USRA.

##  Appendix A Transient correction of PACS data

Figure 15: Scan technique used to observe M 104 with PACS. Each square is a
position of the array on the sky with respect the center of the galaxy. The
scan has been repeated twice in opposite directions (blue and red squares).
The numbers refer to the number of the slice used in the bottom panel figure
which shows the signal normalized to the median signal for all the 16 spexels
in spaxel 2. The two different tonalities of green and blue indicate the two
wavelength ranges observed in each position of the scan. In particular, the
green slices are on-target positions while the blue ones are off-target
positions (scan blocks 1, 13, and 25). The red line shows the fit of the
transient behavior of the response. Note that the same position observed at
the beginning (2) and end (33) of the observation has a variation of 15% in
the response of the detectors, while the flux in the off-target positions
varies by 20%.

In this appendix we describe in detail the process used to reduce the [CII]
data obtained with PACS on Herschel. The data have been obtained by scanning
the rectangular region containing the ring twice. At the second scan, the
center was moved along the perpendicular direction to add a minimum spatial
dithering (see Figure 15). At each position, two spectral regions were
observed. During the observation the primary wavelength were 157.74 $\mu$m
([CII] line) and 88 $\mu$m ([OIII] line). Since PACS had a dual array, When
observing the [OIII] line in the blue array, the parallel observation in the
red array was centered at 177.4$\mu$m. In the following we refer to
observations in one wavelength range and in one raster position as science
blocks. In Figure 15 each science block relative to the 158$\mu$m observation
is colored in light green, while the parallel observation is colored in dark
green. The off-target positions for the two wavelength regions are drawn in
light and dark blue, respectively.

During the observation, the response of the detectors varies because of sudden
variations in the incident flux. This mainly happens in three situations.

The first reason is linked to the change of the observed field and wavelength
range at the beginning of the observation. During the slewing from the
previous target, calibration observations of the internal black-bodies are
taken. Then, an initial off-target position is observed before targeting the
source. In this specific observation, the telescope was pointed to an off-
target position two other times. A long-term transient is visible along the
entire observation and it is due to the sudden variation of flux when the
detector moved from the previous observation (see bottom panel of Fig. 15).

The second reason is due to the alternate observation of two different
wavelength ranges. When observing the region centered at 157.7$\mu$m, for each
raster position the grating is moved to also cover the wavelength region
centered at 177.4$\mu$m. Since the two regions have quite different telescope
backgrounds, the simple fact of alternating between the two bands introduced a
transient behavior in the response of the detector. As visible in Fig. 16, the
signal at the beginning of each science block can have a 10% different
response with respect to that at the end of the block.

Finally, cosmic rays hit the detector randomly throughout the observations,
creating a sudden surcharge which dissipates slowly (typically in less than an
hour, see middle panel of Fig. 17). Such transients can be fitted with a
combination of exponential functions as explained in Fadda et al. (2016).

We will therefore differentiate between a long-term transient affecting the
entire observation, science-block transients affecting the beginning of each
science block, and cosmic ray transients produced by the random impact of
cosmic rays on the detector. To disentangle these different effects one can
use the statistics of repeated observations. Moreover, since the flux of the
observed target is very weak and the background of the telescope dominates
total flux, the total flux does not differ too much from the off-target
positions for the majority of the observation. This fact can be exploited to
better model the transient behavior of the detector response and subtract it
from the data.

Before entering into the details of the algorithm used, it is useful to
establish some technical terms. The PACS array is composed by $5\times 5$
spatial pixels which are called spaxels. For each one of these spaxels, an
instantaneous spectrum is measured using 16 spectral pixels which are called
spexels. A large wavelength range is then obtained by moving the grating to
cover a different instantaneous spectrum for each grating position.

Figure 16: The transient at the beginning of each science block The color code
is as in Figure 15. On the top, the first estimates of the two science-block
transients are obtained by fitting the last science blocks of all the 16
spexels of spaxel 2. On the bottom, the model is refined for the single spexel
6 of spaxel 2 using most of the science blocks of the observation corrected
for the long-term transient.

The pipeline described in Fadda et al. (2016) is optimized for observations
with a single band. In cases like M 104 where two bands are observed
consecutively, the fit of the transient along the entire observation can be
done only after normalizing the science blocks to their respective telescope
background and correcting for the transients due to the change of spectral
range.

We therefore modified the sequence of the modules performed in the script
given with HIPE 15. After correcting all the science blocks for dark,
response, and flats, we output them and correct them externally using Python
scripts. We first compute the transient due to the change of band by
considering the last off-target position block of each spaxel. To improve the
statistics, we include a small selection of blocks from the end of the
observation where the signal appear stabilized (see left panel of Fig. 16)
since many blocks are damaged by cosmic ray transients. After normalizing each
science block, we compute a first estimate of the long-term transient
affecting the entire observation.

Figure 17: Effect of transient corrections on a single pixel: spaxel 2, spexel
6. The original signal normalized to the telescope background (top panel) is
fitted with a transient model (red line). The correction (middle panel) puts
in evidence the transients caused by cosmic rays hitting the detector. These
are corrected using the HIPE pipeline leaving only the flux variations along
the scan at the end of the process (bottom panel).

This first estimate is obtained for each spaxel by combining all the 16
spexels (see Fig. 15). We use it to correct the signal and obtain a second
estimate of the science block transient by coadding all the science blocks
(after rejecting the ones affected by cosmic-induced transients). This
produces models of science block transients for each spexel, as shown in the
right side of Fig. 16.

At this point, this correction is applied to each single spexel of the
original signal and the long-term transient is obtained for each individual
spexel (Fig. 17, top panel). By correcting the spexels for this transient
(middle panel of Fig. 17), the effects of cosmic rays on the response of the
detector become evident. If not corrected they can introduce a significant
amount of noise in the final spectral cube. Moreover, since they also affect
the signal in the off-target positions, the subtraction of the off-target
signal can lead to further inaccuracy in the final result.

The cosmic induced transients are corrected using the module specTransCorr in
the transient correction pipeline of HIPE 15 as explained in Fadda et al.
(2016). This module is very efficient in removing the transients (see bottom
panel of Fig. 17). Transients are identified by finding discontinuities in the
flux and fitting the transient behaviour of the response after the
discontinuity. The few readouts at the beginning of the transients are masked
by the pipeline.

The data are finally reprojected into a spectral cube with a spatial pixel of
3 arcseconds. During this last step, a further rejection of outliers is
performed by the pipeline using the redundancy of data in the same sky
position.

The described process is not only able to eliminate most of the gradient
visible in the archival data, but it also allows one to reconcile the two
scans over the observed region. The usage of the telescope background as
absolute flux calibrator is also very important. As visible in the ratio of
signal over telescope background, the signal calibrated with the calibration
blocks (the technique used in the archival product) grossly overestimates the
flux (by approximately 55%, in this case). We remind that the flux calibration
using the telescope background is the standard process used for the chop/nod
observations and it has been verified with sky flux calibrators. Also, as
shown in Sutter & Fadda (2022), the recalibration of unchopped data using the
telescope background as absolute reference agrees very well with measurements
done with SOFIA/FIFI-LS in NGC 7331 (SOFIA/FIFI-LS uses planets, moons, and
asteroids as absolute flux calibrators, see Fadda et al., 2019).

##  Appendix B Measurements

This appendix presents the measured fluxes in the [CII], CO, and optical
lines, as well as the quantities derived from the SED fitting used in the
figures of the paper (see Table 6). For measurements determined using the
CIGALE SED models (PAH 7.7$\mu$m and 11.3$\mu$m, FIR, and UVatt) we assume 10%
errors due to the uncertainties introduced during the modelling process.

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=4.7cm

Table 6: M104 aperture measurements Aper- | Coordinates | [CII]158μm |  12COJ=0→1 |  $\nu F_{\nu}$ ratio | PAH | FIR | H$\beta$ | [OIII]5008A | H$\alpha$ | [NII]6585A | [SII]6718,32A | EW(H$\alpha$) | UV att
---|---|---|---|---|---|---|---|---|---|---|---|---|---
ture |  | W/m2 | W/m2 | 70$\mu$m/100$\mu$m | 7.7$\mu$m | 11.3$\mu$m | 8-1000$\mu$m | erg/s/cm2 | erg/s/cm2 | erg/s/cm2 | erg/s/cm2 | erg/s/cm2 | Å | erg/s/kpc2
ID | J2000 | $\times 10^{-21}$ | $\times 10^{-18}$ |  | 10${}^{6}L_{\odot}$ | 10${}^{6}L_{\odot}$ | 10${}^{6}L_{\odot}$ | $\times 10^{-16}$ | $\times 10^{-16}$ | $\times 10^{-16}$ | $\times 10^{-16}$ | $\times 10^{-16}$ |  | $\times 10^{40}$
N1 | 12:40:09.04 -11:37:20.4 | 23.2$\pm$0.5 | 18.3$\pm$0.7 | 0.41$\pm$0.06 | 2.47 | 1.21 | 37.1 | 2.6$\pm$0.8 | 2.4$\pm$0.6 | 18.3$\pm$0.9 | 10.4$\pm$0.7 | 9.5$\pm$1.3 | 7.3$\pm$0.4 | 4.65
N2 | 12:40:08.04 -11:37:14.1 | 18.7$\pm$0.7 | 12.4$\pm$0.4 | 0.42$\pm$0.07 | 2.01 | 1.13 | 31.1 | 0.9$\pm$0.9 | 2.7$\pm$0.6 | 8.7$\pm$0.8 | 7.7$\pm$0.6 | 7.4$\pm$0.9 | 2.8$\pm$0.3 | 1.76
N3 | 12:40:07.04 -11:37:11.5 | 13.6$\pm$0.7 | 10.4$\pm$0.4 | 0.44$\pm$0.08 | 1.50 | 0.83 | 24.1 | 0.9$\pm$0.8 | 1.9$\pm$0.6 | 8.4$\pm$0.7 | 5.5$\pm$0.6 | 4.8$\pm$0.5 | 2.5$\pm$0.2 | 1.88
N4 | 12:40:06.26 -11:37:10.4 | 14.1$\pm$0.0 | 10.8$\pm$0.4 | 0.44$\pm$0.09 | 1.29 | 0.74 | 19.9 |  | 2.0$\pm$0.7 | 5.0$\pm$0.6 | 4.7$\pm$0.5 | 4.3$\pm$8.2 | 1.2$\pm$0.2 | 1.79
N5 | 12:40:05.42 -11:37:10.2 | 21.2$\pm$0.4 | 10.1$\pm$0.7 | 0.44$\pm$0.10 | 1.14 | 0.71 | 16.9 | 1.9$\pm$1.2 | 2.0$\pm$0.7 | 13.2$\pm$1.1 | 7.0$\pm$0.8 | 6.4$\pm$0.7 | 2.8$\pm$0.2 | 1.23
N6 | 12:40:04.73 -11:37:09.8 | 9.9$\pm$1.0 | 11.8$\pm$0.4 | 0.45$\pm$0.11 | 1.11 | 0.70 | 16.9 |  |  | 7.2$\pm$1.5 | 6.8$\pm$1.0 | 6.7$\pm$1.1 | 1.3$\pm$0.3 | 0.38
N7 | 12:40:03.96 -11:37:08.8 | 8.4$\pm$3.9 | 9.7$\pm$0.3 | 0.44$\pm$0.11 | 1.07 | 0.71 | 16.6 |  |  | 8.6$\pm$1.1 | 5.8$\pm$0.8 | 4.7$\pm$0.7 | 1.3$\pm$0.2 | 0.39
N8 | 12:40:03.13 -11:37:09.1 | 7.1$\pm$1.0 | 10.5$\pm$0.3 | 0.47$\pm$0.11 | 1.15 | 0.84 | 18.4 |  | 1.5$\pm$1.1 | 6.9$\pm$1.1 | 6.4$\pm$0.9 | 5.1$\pm$0.7 | 0.7$\pm$0.1 | 0.49
N9 | 12:40:02.27 -11:37:08.5 | 9.6$\pm$0.6 | 8.8$\pm$0.3 | 0.44$\pm$0.11 | 1.06 | 0.90 | 17.3 |  |  | 4.1$\pm$1.0 | 7.1$\pm$0.8 | 5.7$\pm$0.9 | 0.3$\pm$0.1 | 0.41
N10 | 12:40:01.04 -11:37:09.1 | 13.8$\pm$1.6 | 10.3$\pm$0.3 | 0.48$\pm$0.11 | 1.16 | 1.06 | 18.3 |  | 2.0$\pm$1.5 | 7.3$\pm$2.0 | 8.9$\pm$1.6 | 7.2$\pm$1.7 | 0.4$\pm$0.1 | 0.68
N11 | 12:40:00.17 -11:37:08.8 | 27.5$\pm$1.3 | 10.7$\pm$0.3 | 0.49$\pm$0.09 | 1.43 | 1.50 | 21.8 |  |  | 15.5$\pm$1.8 | 12.2$\pm$1.5 | 9.3$\pm$1.9 | 0.6$\pm$0.1 | 0.62
N12 | 12:39:58.79 -11:37:08.8 | 15.7$\pm$1.4 | 8.0$\pm$0.3 | 0.52$\pm$0.10 | 1.42 | 1.61 | 22.6 |  |  | 6.5$\pm$1.2 | 7.7$\pm$1.1 | 5.0$\pm$1.6 | 0.3$\pm$0.1 | 0.63
N13 | 12:39:57.74 -11:37:09.2 | 23.8$\pm$1.3 | 9.3$\pm$0.3 | 0.46$\pm$0.09 | 1.28 | 1.13 | 21.9 |  |  | 13.0$\pm$2.0 | 11.3$\pm$1.5 | 9.1$\pm$0.9 | 0.9$\pm$0.1 | 0.60
N14 | 12:39:56.81 -11:37:10.4 | 3.2$\pm$0.5 | 8.8$\pm$0.4 | 0.47$\pm$0.11 | 1.06 | 0.96 | 17.6 |  |  | 2.2$\pm$1.8 | 7.4$\pm$1.7 | 5.0$\pm$0.8 | 0.2$\pm$0.1 | 0.47
N15 | 12:39:55.94 -11:37:11.5 | 4.7$\pm$1.2 | 8.5$\pm$0.4 | 0.42$\pm$0.10 | 1.07 | 0.83 | 18.1 |  |  | 7.0$\pm$1.6 | 9.3$\pm$1.1 | 5.7$\pm$0.8 | 0.7$\pm$0.2 | 0.56
N16 | 12:39:55.01 -11:37:11.1 | 5.1$\pm$0.1 | 9.3$\pm$0.3 | 0.44$\pm$0.10 | 1.14 | 0.79 | 18.1 |  |  | 5.4$\pm$1.6 | 9.0$\pm$1.4 | 6.8$\pm$1.6 | 0.7$\pm$0.2 | 0.46
N17 | 12:39:54.07 -11:37:12.5 | 16.9$\pm$1.5 | 10.0$\pm$0.4 | 0.38$\pm$0.09 | 1.28 | 0.80 | 20.6 |  |  | 4.8$\pm$1.1 | 5.9$\pm$1.0 | 5.4$\pm$0.9 | 0.9$\pm$0.2 | 0.17
N18 | 12:39:53.27 -11:37:13.4 | 16.0$\pm$1.2 | 10.7$\pm$0.4 | 0.37$\pm$0.09 | 1.37 | 0.82 | 21.6 |  |  | 2.8$\pm$0.7 | 5.3$\pm$0.7 | 4.7$\pm$0.5 | 0.6$\pm$0.2 | 2.28
N19 | 12:39:52.41 -11:37:14.8 | 25.2$\pm$1.1 | 10.6$\pm$0.3 | 0.39$\pm$0.08 | 1.48 | 0.86 | 24.0 |  |  | 9.8$\pm$0.7 | 8.2$\pm$0.6 | 6.7$\pm$0.5 | 2.4$\pm$0.2 | 1.91
N20 | 12:39:51.38 -11:37:17.4 | 20.1$\pm$1.0 | 11.0$\pm$0.4 | 0.42$\pm$0.07 | 1.91 | 1.10 | 30.2 | 1.3$\pm$0.8 | 1.6$\pm$0.7 | 10.2$\pm$0.8 | 8.4$\pm$0.6 | 7.2$\pm$0.5 | 2.9$\pm$0.2 | 1.91
N21 | 12:39:50.62 -11:37:18.0 | 17.9$\pm$0.6 | 9.7$\pm$0.4 | 0.42$\pm$0.06 | 2.09 | 1.18 | 33.0 | 1.4$\pm$0.8 | 2.5$\pm$0.7 | 10.4$\pm$0.8 | 8.3$\pm$0.6 | 8.2$\pm$1.7 | 3.5$\pm$0.3 | 1.71
N22 | 12:39:50.10 -11:37:25.9 | 25.0$\pm$8.9 | 16.5$\pm$0.5 | 0.41$\pm$0.06 | 2.70 | 1.29 | 31.2 | 2.1$\pm$1.2 | 2.0$\pm$0.5 | 13.5$\pm$0.8 | 8.6$\pm$0.6 | 8.3$\pm$0.4 | 5.7$\pm$0.4 | 5.05
N23 | 12:39:49.28 -11:37:24.4 | 20.1$\pm$0.5 | 15.1$\pm$0.0 | 0.37$\pm$0.07 | 2.12 | 1.03 | 25.1 |  |  |  |  |  |  | 1.29
L1 | 12:40:00.82 -11:37:22.8 | 14.0$\pm$0.3 |  | 0.69$\pm$0.13 | 0.91 | 1.43 | 17.5 |  |  | 15.3$\pm$9.7 | 28.4$\pm$7.2 | 16.2$\pm$5.2 | 0.3$\pm$0.2 | 0.34
L2 | 12:40:02.01 -11:37:23.4 | 14.9$\pm$0.9 |  | 0.66$\pm$0.11 | 0.82 | 1.05 | 17.0 |  | 7.6$\pm$5.7 | 20.6$\pm$10.6 | 32.0$\pm$5.0 | 17.3$\pm$2.3 | 0.6$\pm$0.3 | 0.30
L3 | 12:40:03.03 -11:37:22.8 | 8.7$\pm$0.1 |  | 0.63$\pm$0.12 | 0.67 | 0.86 | 14.2 |  | 9.3$\pm$6.5 | 18.5$\pm$10.9 | 27.3$\pm$3.9 | 15.9$\pm$2.7 | 0.9$\pm$0.5 | 0.33
L4 | 12:40:04.08 -11:37:22.7 | 12.4$\pm$0.6 |  | 0.58$\pm$0.13 | 0.62 | 0.76 | 13.3 |  | 7.9$\pm$3.3 | 9.5$\pm$3.3 | 17.1$\pm$2.5 | 12.6$\pm$1.8 | 0.7$\pm$0.2 | 0.20
L5 | 12:40:05.15 -11:37:22.4 | 14.5$\pm$0.8 |  | 0.51$\pm$0.13 | 0.63 | 0.72 | 11.8 |  |  | 3.6$\pm$2.4 | 7.2$\pm$1.7 | 4.9$\pm$1.2 | 0.4$\pm$0.3 | 0.26
L6 | 12:40:06.08 -11:37:22.0 | 8.4$\pm$0.7 |  | 0.48$\pm$0.11 | 0.82 | 0.79 | 14.3 |  | 4.7$\pm$1.2 | 4.6$\pm$1.3 | 7.8$\pm$1.0 | 5.4$\pm$0.6 | 0.8$\pm$0.2 | 0.18
L7 | 12:40:06.95 -11:37:22.1 | 12.6$\pm$1.1 |  | 0.45$\pm$0.08 | 1.24 | 1.00 | 17.7 |  | 4.0$\pm$2.3 | 6.3$\pm$1.3 | 11.5$\pm$1.0 | 9.2$\pm$0.6 | 1.2$\pm$0.3 | 0.22

=5.2cm

Table B1: (continued) Aper- | Coordinates | [CII]158μm |  12COJ=0→1 |  $\nu F_{\nu}$ ratio | PAH | FIR | H$\beta$ | [OIII]5008A | H$\alpha$ | [NII]6585A | [SII]6718,32A | EW(H$\alpha$) | UV att
---|---|---|---|---|---|---|---|---|---|---|---|---|---
ture |  | W/m2 | W/m2 | 70$\mu$m/100$\mu$m | 7.7$\mu$m | 11.3$\mu$m | 8-1000$\mu$m | erg/s/cm2 | erg/s/cm2 | erg/s/cm2 | erg/s/cm2 | erg/s/cm2 | Å | erg/s/kpc2
ID | J2000 | $\times 10^{-21}$ | $\times 10^{-18}$ |  | 10${}^{6}L_{\odot}$ | 10${}^{6}L_{\odot}$ | 10${}^{6}L_{\odot}$ | $\times 10^{-16}$ | $\times 10^{-16}$ | $\times 10^{-16}$ | $\times 10^{-16}$ | $\times 10^{-16}$ |  | $\times 10^{40}$
S1 | 12:40:08.10 -11:37:26.4 | 20.0$\pm$0.2 | 10.3$\pm$0.4 | 0.41$\pm$0.07 | 2.16 | 1.11 | 26.4 |  | 2.0$\pm$0.4 | 7.5$\pm$0.6 | 7.3$\pm$0.5 | 6.3$\pm$0.5 | 3.5$\pm$0.3 | 4.50
S2 | 12:40:07.11 -11:37:31.0 | 10.7$\pm$0.0 | 7.5$\pm$0.4 | 0.43$\pm$0.09 | 1.42 | 0.79 | 17.9 | 1.7$\pm$0.4 | 1.3$\pm$0.4 | 12.6$\pm$0.5 | 7.2$\pm$0.4 | 6.4$\pm$0.3 | 8.2$\pm$0.4 | 0.36
S3 | 12:40:06.19 -11:37:33.0 | 9.6$\pm$1.2 | 9.4$\pm$0.3 | 0.44$\pm$0.10 | 1.25 | 0.67 | 16.5 |  | 0.9$\pm$0.4 | 3.6$\pm$0.4 | 4.1$\pm$0.4 | 4.2$\pm$0.3 | 2.7$\pm$0.3 | 0.25
S4 | 12:40:05.22 -11:37:34.6 | 12.9$\pm$0.5 | 8.6$\pm$0.3 | 0.42$\pm$0.11 | 1.22 | 0.64 | 15.5 | 1.1$\pm$0.4 | 1.0$\pm$0.2 | 8.5$\pm$0.8 | 5.6$\pm$0.9 | 5.1$\pm$0.6 | 35.4$\pm$5.1 | 0.27
S5 | 12:40:04.27 -11:37:35.0 | 8.4$\pm$0.7 | 8.1$\pm$0.3 | 0.45$\pm$0.11 | 1.19 | 0.69 | 15.7 |  | 2.0$\pm$0.8 | 4.1$\pm$0.9 | 5.7$\pm$1.1 | 5.1$\pm$0.6 | 4.1$\pm$1.0 | 0.28
S6 | 12:40:03.10 -11:37:35.3 | 3.6$\pm$0.8 | 10.0$\pm$0.3 | 0.48$\pm$0.10 | 1.29 | 0.78 | 17.3 |  | 1.4$\pm$0.7 | 2.3$\pm$1.0 | 5.1$\pm$0.9 | 4.1$\pm$0.6 | 1.0$\pm$0.5 | 0.36
S7 | 12:40:01.95 -11:37:36.3 | 5.5$\pm$0.8 | 9.5$\pm$0.3 | 0.48$\pm$0.11 | 1.43 | 0.91 | 17.9 |  | 1.5$\pm$0.6 | 4.8$\pm$0.6 | 6.9$\pm$0.6 | 5.4$\pm$0.6 | 1.3$\pm$0.2 | 0.27
S8 | 12:40:00.89 -11:37:36.6 | 13.0$\pm$1.0 | 8.3$\pm$0.5 | 0.46$\pm$0.10 | 1.76 | 1.14 | 20.1 |  | 1.3$\pm$0.8 | 6.1$\pm$1.1 | 6.8$\pm$0.9 | 6.1$\pm$0.8 | 2.3$\pm$0.4 | 0.39
S9 | 12:39:59.70 -11:37:37.3 | 6.9$\pm$0.5 | 6.6$\pm$0.3 | 0.53$\pm$0.11 | 2.21 | 1.72 | 22.6 |  | 1.9$\pm$0.7 | 4.7$\pm$0.8 | 5.5$\pm$0.6 | 4.7$\pm$0.6 | 0.7$\pm$0.1 | 0.61
S10 | 12:39:58.78 -11:37:37.3 | 11.6$\pm$0.3 | 8.6$\pm$0.5 | 0.52$\pm$0.11 | 2.00 | 1.52 | 20.3 |  | 3.0$\pm$1.4 | 4.7$\pm$1.1 | 5.5$\pm$0.8 | 4.5$\pm$0.6 | 0.8$\pm$0.2 | 0.55
S11 | 12:39:57.88 -11:37:38.3 | 6.6$\pm$1.1 | 8.1$\pm$0.3 | 0.39$\pm$0.12 | 1.55 | 1.06 | 17.7 |  | 1.2$\pm$0.4 | 2.6$\pm$0.4 | 4.8$\pm$1.0 | 3.7$\pm$0.7 | 2.8$\pm$0.5 | 0.34
S12 | 12:39:57.09 -11:37:37.3 | 6.7$\pm$0.4 | 8.6$\pm$0.3 | 0.42$\pm$0.11 | 1.41 | 0.93 | 17.0 | 1.5$\pm$0.7 | 1.4$\pm$0.4 | 8.8$\pm$0.7 | 6.8$\pm$0.6 | 6.1$\pm$0.6 | 2.3$\pm$0.2 | 0.29
S13 | 12:39:56.21 -11:37:36.6 | 6.1$\pm$0.5 | 11.6$\pm$0.3 | 0.41$\pm$0.11 | 1.28 | 0.81 | 16.3 |  | 1.9$\pm$0.4 | 3.9$\pm$0.6 | 5.6$\pm$0.5 | 4.8$\pm$0.6 | 1.3$\pm$0.2 | 0.24
S14 | 12:39:55.31 -11:37:36.0 | 15.6$\pm$1.2 | 12.7$\pm$0.8 | 0.41$\pm$0.11 | 1.23 | 0.74 | 16.8 | 0.8$\pm$0.7 | 1.8$\pm$0.6 | 5.9$\pm$0.7 | 7.0$\pm$0.6 | 6.2$\pm$0.4 | 2.1$\pm$0.2 | 0.35
S15 | 12:39:54.36 -11:37:36.3 | 8.7$\pm$0.5 | 11.5$\pm$0.3 | 0.39$\pm$0.11 | 1.25 | 0.69 | 15.9 | 1.1$\pm$0.8 | 1.4$\pm$0.5 | 5.7$\pm$0.5 | 6.2$\pm$0.5 | 5.8$\pm$0.6 | 6.1$\pm$0.6 | 0.29
S16 | 12:39:53.35 -11:37:35.3 | 14.2$\pm$1.1 | 16.2$\pm$0.5 | 0.34$\pm$0.10 | 1.30 | 0.74 | 16.9 |  | 0.9$\pm$0.6 | 2.6$\pm$0.5 | 4.1$\pm$0.4 | 3.5$\pm$0.2 | 1.5$\pm$0.3 | 0.24
S17 | 12:39:52.36 -11:37:34.6 | 20.5$\pm$1.0 | 14.4$\pm$0.4 | 0.41$\pm$0.09 | 1.53 | 0.77 | 20.8 | 1.4$\pm$0.5 | 0.7$\pm$0.3 | 10.8$\pm$0.5 | 6.1$\pm$0.5 | 5.3$\pm$0.3 | 7.6$\pm$0.4 | 0.25
S18 | 12:39:51.55 -11:37:32.0 | 12.4$\pm$0.4 | 12.2$\pm$0.4 | 0.40$\pm$0.07 | 1.89 | 0.99 | 22.4 |  | 1.1$\pm$0.4 | 5.9$\pm$0.6 | 5.5$\pm$0.5 | 5.3$\pm$0.4 | 3.4$\pm$0.4 | 0.47
S19 | 12:39:50.76 -11:37:29.3 | 21.1$\pm$0.9 | 12.0$\pm$0.4 | 0.42$\pm$0.06 | 2.54 | 1.22 | 30.6 | 1.2$\pm$0.7 | 1.8$\pm$0.5 | 9.8$\pm$0.7 | 6.4$\pm$0.5 | 6.4$\pm$0.5 | 4.8$\pm$0.4 | 5.06
S20 | 12:39:47.78 -11:37:25.6 | 4.5$\pm$0.5 | 5.0$\pm$0.4 | 0.30$\pm$0.15 | 0.84 | 0.51 | 13.3 |  |  |  |  |  |  | 3.14
S21 | 12:39:46.82 -11:37:25.0 | 5.5$\pm$0.8 | 4.3$\pm$0.3 | 0.27$\pm$0.21 | 0.62 | 0.35 | 9.5 |  |  |  |  |  |  | 2.10
S22 | 12:40:10.73 -11:37:20.5 | 18.9$\pm$1.6 | 7.4$\pm$0.2 | 0.34$\pm$0.11 | 1.24 | 0.66 | 18.5 |  |  |  |  |  |  | 4.21
Nuc | 12:39:59.41 -11:37:22.0 | 31.4$\pm$2.4 | 2.1$\pm$1.5 | 1.10$\pm$0.10 | 3.11 | 2.85 | 53.6 |  |  | 110.6$\pm$17.5 | 695.0$\pm$48.0 | 302.6$\pm$38.5 | 0.4$\pm$0.1 | 0.65
R1 | 12:39:58.61 -11:37:21.8 | 14.9$\pm$1.4 | 1.4$\pm$0.2 | 0.83$\pm$0.11 | 1.35 | 2.25 | 25.8 |  | 31.8$\pm$6.8 | 38.6$\pm$15.3 | 78.1$\pm$10.7 | 36.8$\pm$5.6 | 0.5$\pm$0.2 | 0.31
R2 | 12:39:57.34 -11:37:23.7 | 8.9$\pm$0.9 |  | 0.65$\pm$0.11 | 0.85 | 1.16 | 18.1 |  |  | 17.6$\pm$7.8 | 45.9$\pm$7.8 | 22.0$\pm$3.5 | 0.5$\pm$0.2 | 0.36
R3 | 12:39:56.29 -11:37:24.1 | 11.4$\pm$0.8 |  | 0.58$\pm$0.15 | 0.65 | 0.90 | 13.0 |  | 11.3$\pm$3.8 | 4.8$\pm$4.8 | 17.4$\pm$4.2 | 8.5$\pm$2.2 | 0.2$\pm$0.2 | 0.26
R4 | 12:39:55.20 -11:37:24.0 | 8.9$\pm$0.8 |  | 0.56$\pm$0.13 | 0.61 | 0.81 | 12.6 |  | 10.6$\pm$6.1 | 14.8$\pm$3.2 | 22.6$\pm$2.7 | 15.1$\pm$2.6 | 1.0$\pm$0.2 | 0.26
R5 | 12:39:54.36 -11:37:24.4 | 9.2$\pm$1.1 |  | 0.47$\pm$0.14 | 0.62 | 0.78 | 11.4 |  | 6.9$\pm$4.3 | 5.4$\pm$2.8 | 10.9$\pm$1.9 | 6.4$\pm$1.2 | 0.5$\pm$0.3 | 0.18
R6 | 12:39:53.44 -11:37:24.4 | 18.6$\pm$1.4 |  | 0.41$\pm$0.13 | 0.77 | 0.85 | 12.4 |  |  | 1.3$\pm$2.0 | 5.9$\pm$1.3 | 3.7$\pm$2.2 | 0.2$\pm$0.3 | 0.24
R7 | 12:39:52.58 -11:37:24.8 | 11.8$\pm$0.7 |  | 0.43$\pm$0.10 | 1.05 | 0.94 | 16.9 |  | 3.2$\pm$2.1 | 5.8$\pm$1.2 | 10.5$\pm$1.0 | 7.6$\pm$0.8 | 1.1$\pm$0.2 | 0.31