Issue |
A&A
Volume 518, July-August 2010
Herschel: the first science highlights
|
|
---|---|---|
Article Number | L76 | |
Number of page(s) | 5 | |
Section | Letters | |
DOI | https://doi.org/10.1051/0004-6361/201014628 | |
Published online | 16 July 2010 |
Herschel: the first science highlights
LETTER TO THE EDITOR
The Herschel revolution: Unveiling the morphology of the
high-mass star-formation sites N44 and N63 in the
LMC![[*]](/icons/foot_motif.png)
S. Hony1 - F. Galliano1 - S. C. Madden1 - P. Panuzzo1 - M. Meixner2 - C. Engelbracht3 - K. Misselt3 - M. Galametz1 - M. Sauvage1 - J. Roman-Duval2 - K. Gordon2 - B. Lawton2 - J.-P. Bernard4 - A. Bolatto5 - K. Okumura1 - C.-H. R. Chen6 - R. Indebetouw6 - F. P. Israel7 - E. Kwon8 - A. Li9 - F. Kemper10 - M. S. Oey11 - M. Rubio12 - H. E. Triou1
1 - Service d'Astrophysique, CEA, Saclay, 91191 Gif-Sur-Yvette Cedex, France
2 -
Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA
3 -
Steward Observatory, University of Arizona, 933 North Cherry Ave., Tucson, AZ 85721, USA
4 -
Centre d'Étude Spatiale des Rayonnements, CNRS, 9 av. du Colonel Roche, BP 4346, 31028 Toulouse, France
5 -
Department of Astronomy, Lab for Millimeter-wave Astronomy, University of Maryland. College Park, MD 20742-2421, USA
6 -
Department of Astronomy, University of Virginia, PO Box 3818, Charlottesville, VA 22903, USA
7 -
Sterrewacht Leiden, Leiden University, PO Box 9513, 2300 RA Leiden, The Netherlands
8 -
Astronomy & Space Science, Sejong University, 143-747 Seoul, South Korea
9 -
Department of Physics and Astronomy, University of Missouri, 314 Physics Building, Columbia, MO 65211, USA
10
- Jodrell Bank Centre for Astrophysics, Alan Turing Building, School of
Physics and Astronomy, The University of Manchester, Oxford Road,
Manchester M13 9PL, UK
11 -
Department of Astronomy, University of Michigan, 830 Dennison Building, Ann Arbor, MI 48109-1042, USA
12 - Departamento de Astronomia, Universidad de Chile, Casilla 36-D, Santiago, Chile
Received 31 March 2010 / Accepted 15 April 2010
Abstract
Aims. We study the structure of the medium surrounding sites
of high-mass star formation to determine the interrelation between the
H II regions and the environment from which they
were formed. The density distribution of the surroundings is key in
determining how the radiation of the newly formed stars interacts with
the surroundings in a way that allows it to be used as a star-formation
tracer.
Methods. We present new Herschel/SPIRE 250 m, 350
m and 500
m
data of LHA 120-N44 and LHA 120-N63 in the LMC. We construct average
spectral energy distributions (SEDs) for annuli centered on the IR
bright part of the star-formation sites. The annuli cover
10-
100 pc.
We use a phenomenological dust model to fit these SEDs to derive the
dust column-densities, characterize the incident radiation field and
the abundance of polycyclic aromatic hydrocarbon molecules. We see a
decrease of a factor 5 in the radiation field energy-density as a
function of radial distance around N63. The source N44 does not show a
systematic trend. We construct a simple geometrical model to derive the
3D density profile of the surroundings of these two regions.
Results. Herschel/SPIRE data have proven very efficient
in deriving the dust-mass distribution. We find that the radiation
field in the two sources behaves very differently. N63 is more or less
spherically symmetric and the average radiation field drops with
distance. N44 shows no systematic decrease of the radiation intensity,
which is probably due to the inhomogeneity of the surrounding molecular
material and to the complex distribution of several star-forming
clusters in the region.
Key words: Magellanic Clouds - galaxies: star formation - infrared: ISM - submillimeter: ISM - ISM: structure
1 Introduction
![]() |
Figure 1:
False color images of the surroundings of N44 and N63. IRAC 4 (8.0 |
Open with DEXTER |
High-mass star-formation (SF) sites (hereafter HMSFSs) are the beacons
by which we probe a large part of the physics of external galaxies.
They generally represent the most important tracers of the properties
of their host galaxies in terms of star-formation rate (SFR) and
general activity. The most frequent tracers of the star-formation
activity generally use the fact that the abundant UV light coming from
the hot, young stars is absorbed in the vicinity and reradiated in the
form of line or continuum emission. This is true, for example, for
H
(e.g. Kennicutt 1998), the aromatic emission
bands in the mid-IR (e.g. Calzetti et al. 2007) or the IR
continuum due to solid-state materials (dust,
e.g. Soifer et al. 1986). These tracers work relatively well and
are used to characterize nearby star-forming regions and star-forming
galaxies out to large redshifts, although interesting discrepancies
have been noted for dwarf galaxies at low SFR
(see Lee et al. 2009). One of the main assumptions that
enters into the quantitative interpretation of these data is the
geometry of the material surrounding the newly formed stars, in
particular, where the UV light is being reprocessed. For example, if
the UV photons escape from the ionized medium this may boost the
aromatic feature strengths and strongly influence the lines
originating from the surrounding photo-dissociation regions (PDRs).
There are indications that this geometry in external galaxies may
qualitatively and quantitatively differ from that observed in the
Milky Way (MW)
(e.g. Madden et al. 2006; Galametz et al. 2009). One simple
effect may be that at different metallicities the surrounding medium
is more or less opaque and therefore the UV photons have a different
mean free path. More complex scenarios are also discussed in the
literature. For example, clumpiness of the molecular cloud may lead to
small molecular cores surrounded by large PDRs. Herschel with
its unprecedented wavelength coverage and angular resolution at
submillimeter (submm) wavelengths provides a unique opportunity to
probe the cold interstellar medium (ISM) and sample the effects of the
environment on the resulting SF tracers. In particular, it is well
suited to trace the distribution of matter around HMSFSs and to map
the way the UV radiation permeates and heats the surroundings. Here we
present a study of two HMSFSs in the Large Magellanic Cloud (LMC)
based on data taken in the HERITAGE program (PI. Meixner,
see Meixner et al. 2010).
2 Data treatment and modeling
We constructed spectral energy distributions (SEDs) of the environment
of two distinct HMSFSs (LHA 120-N 44 and LHA 120-N 44 (Henize 1956), hereafter N44 and N63,
respectively) in the strip of the LMC that was mapped during the
science demonstration phase. The two regions were chosen because they
are the brightest and most isolated regions observed. N44 is the
brightest H II complex in the observed strip. Massive star
formation has occurred in this region; it contains three the OB
associations LH47, 48, and 49 with ages 10 Myr at the
central super-bubble and
5 Myr at the super-bubble rims and
surrounding dense H II regions, as well as a large number of
massive young stellar objects (YSOs) with ages
1 Myr
(Lucke & Hodge 1970; Chen et al. 2009; Oey & Massey 1995).
The site N44 is also the brightest source of all a the SPIRE
wavelengths (250
m, 350
m, and 500
m) in the strip
(Meixner et al. 2010). By contrast, N63 is a simple, roughly
round H II region. It contains one OB association LH83 with an
age <5 Myr and a number of massive YSOs
(Bica et al. 1996; Caulet et al. 2008). At SPIRE wavelengths,
N63 is in a relatively isolated environment. Thus, we use N44 as an
example of a prominent H II region as seen in more distant
galaxies and N63 as a comparison, whose simple structure makes it more
straightforward to relate dust properties with physical conditions of
the ISM.
The data we use are: 2MASS J, H, (Skrutskie et al. 2006), Spitzer IRAC 1, 2, 3, 4
(Fazio et al. 2004), MIPS 24
m, 70
m and 160
m
(Rieke et al. 2004) and Herschel (Pilbratt et al. 2010) SPIRE 250
m, 350
m and 500
m (Griffin et al. 2010). See
Meixner et al. (2010) for a description of the SPIRE data
treatment. We do not use the PACS information because the data we have
until now do not allow us to extract extended source fluxes with
sufficient accuracy. We extracted maps of
40
centered on each H II region.
We convolved these data to a spatial resolution of 38
set by the MIPS 160
m/SPIRE 500
m data. The 2MASS data were
convolved with the beam of MIPS 160
m, the IRAC1-4, MIPS
24
m and 70
m were convolved with custom-made kernels
(Gordon et al. 2008). The SPIRE data were all convolved to the
SPIRE 500
m resolution assuming Gaussian beam profiles with FWHM
of 18.1
,
25.2
and 36.9
for SPIRE 250
m, 35
m and 500
m, respectively. We have the convolved images to the pixel scheme of the MIPS 160
m image with the IDL/astrolib routine hastrom.
The center of the HMSFS was determined by fitting a 2D Gaussian
profile as the brightest source in the total IR (TIR) image. The TIR
image was obtained by simple integration from 8 m to 500
m.
The reasoning for this definition of the center is that this location
(on a size scale of tens of parsecs) probably hosts the most active
site of embedded star formation. We extracted flux densities (in Jy)
for annuli around the given center (see Fig. 1). We used
the following radii for the sizes of the annuli: 35, 47, 78, 125, 200,
330 and 530
,
corresponding to linear sizes of 8, 12,
19, 30, 48, 80 and 128 pc assuming a distance to the LMC of 50 kpc
(e.g. Schaefer 2008). The annuli were chosen to be
larger than the apparent size of the HMSFS to enable us to also study
the regime in which the emission becomes dominated by the general LMC.
Examples of the extracted SEDs for each region in different annuli are
shown in Fig. 2a,b. There is a clear and systematic
trend for the far-IR to peak at a longer wavelength for the outer
annuli. For N44 this trend is to a large part offset by the broadness
of the far-IR peak. This is an indication that the emission arises
from a broad temperature distribution. We also note that we detect
polycyclic aromatic hydrocarbon (PAH) emission (at 8
m) in all
SEDs. Because we are mainly interested in the ``shape'' of the IR SED
as a function of distance, we created relative flux-density maps by
dividing the maps at each wavelength by the TIR map to measure the
scatter. The scatter inside each annulus of the relative intensity map
was used to estimate the uncertainty (1
)
on the flux
densities. Note that this method for determining the variance causes a
large scatter in the near-IR pixels which are dominated by stellar
light. This is the reason for the large error-bars at these
wavelengths in Fig. 2a, b.
We used a phenomenological dust model, which is described in detail in
Galametz et al. (2009), to interpret the observed SEDs. This
model consists of a quantity of dust, with a realistic composition
(PAHs, silicate and graphite) and grain-size distribution (complex
molecules, very small (VSG) and big grains) illuminated by a radiation
field with a range of intensities. The main parameters that we aim to
constrain are: 1) total dust mass; 2) the range of
illumination intensities; and 3) the relative composition, in
particular the mass fraction of PAHs. The radiation field distribution
is represented by a power-law function that describes which fraction
of the matter is exposed to what radiation field
(Dale & Helou 2002):
where U is the intensity of the incident radiation field the dust is subjected to (U =1 for the diffuse MW environment),



![]() |
Figure 2: Summary of main results. We show the SEDs of the two SF regions on the left. The black symbols show the integrated photometry of three different annuli, lines are the best-fit models and the colored trianglesrepresent the synthetic photometry in the corresponding filters. The derived dust column density (panel c)), mean radiation field energy-density (panel d)), and the PAH mass fraction (panel e)) as a function of annulus size are shown on the right. The error-bars on the parameters in Panels c), d), e) were derived by propagating the variance on the photometry with a Monte-Carlo method (see Sect. 2). |
Open with DEXTER |
The starting point for the modeling is to adopt dust properties that
fit the MW IR emission well (Zubko et al. 2004, distribution
BARE-GR-S). The observed 24 m fluxes in the
diffuse ISM forced us to use a dust-size distribution that is
different from the MW values. The best fits are obtained by reducing
the mass fraction of VSGs to total dust by 50 per cent. We used the MW
interstellar radiation field as the shape of the radiation field and
did not vary this. The derived dust masses are robust against the
choice of interstellar radiation field and the mass fraction of VSGs.
However, the relative mass fractions of the various dust constituents
may depend on these choices.
In comparing the dust-mass tracers with the gas tracers (Roman-Duval et al. 2010; Meixner et al. 2010; Gordon et al. 2010) some issues have been raised about the applicability of this composition to the LMC, in particular the graphitic component. We verified that the derived mass and radiation field profiles (the shape as a function of annulus) are not sensitive to the choice of the carbon-bearing grains. However, the absolute values of the derived parameters depend on this choice. Uncertainties on the derived parameters were estimated with a Monte-Carlo evaluation. The fitting routine was repeated 300 times with the observational constraints varied randomly, according to their standard deviations, and new best-fit parameters were determined. The ensemble of best-fit parameters was used to calculate the error-bars on each parameter (see Fig. 2).
3 Results
Figure 2a, b show representative SEDs and the
best-fit models. The models fit the data very well over the entire
wavelength range, for all annuli. Most parameters are well constrained
with a distribution of best-fit parameters which is roughly symmetric
around the central value. One exception to this is the
in the two outer annuli of N44. We find a distribution around the mean which
is heavily skewed to low values of
.
We do not detect a
systematic submm excess, i.e. the whole wavelength range up to
500
m is well fitted by the standard model. The model and the
500
m surface brightness agree on average within 3% with a very
small dispersion. The model is in accordance with the findings of
Gordon et al. (2010), who show that the evidence in the LMC
for a submm excess is weak, and if present it is confined to the more
diffuse and fainter environments.
The SED fits allow us to study the derived properties as a function of
annulus (projected distance). We show as a function of radius in
Fig. 2c-e the dust column density
(
), average radiation field intensity (
)
and the mass fraction of PAHs normalized to the MW value. Both sources
show a column density profile that decreases outwards, although the
column density in the central region of N63 is not much higher than in
the outer annuli. The source N63 causes an increase of a
factor 2-3
of column density. The column density towards the central regions
of N44 is
10 times higher than its environment.
The width of the IR SED, which is well determined through the
SPIRE data, requires a significant dust mass at lower temperatures.
This is reflected in the low values of
in panel d.
exhibits only a small range for the entire sample of SEDs.
decreases as a function of distance for N63. The source N44
does not exhibit any significant trend and the data are consistent
with a constant
over a distance scale from 10-100 pc. Note
that
is weighted by dust mass and so it readily traces the
radiation field as seen by the coldest dust along the line of sight.
We calculated the second moment of the radiation field distribution
(), again weighted by dust mass to quantify the range of
radiation fields that the matter is exposed to. All SEDs require
a wide range of U. For N44
is roughly constant at the
value of 30 meaning that the entire region is typified by a radiation
field intensity ranging from 1 to 30. The site N63 shows an outward
decreasing
from
50 in the inner annulus to 2 in the
outer. Thus the radiation field in N63 spans 5-55
(
-
+
)
on the inside and 1-3 in the outer annuli. This implies that the outer annuli in N63 closely resemble a diffuse environment.
The fraction of mass contained in PAHs increases with increasing
radius out to about 50 per cent of the MW value. We find a significant
depletion of the PAHs towards the central regions over 20 and
40 pc for N44 and N63, respectively. Note that the smaller size of the
depleted region is consistent with the observation that N63 is less
prominent compared to its surroundings (see below). Interestingly, the
radius of the depleted environment corresponds well to the area
occupied by the ionizing stars in Fig. 1. The fraction of
the ionized PAHs is not well constrained, but we checked that there is
no systematic effect of the fitting procedure that causes the observed
trend in Fig. 2e.
![]() |
Figure 3: Derived geometrical parameters of the two regions. We show the dust column density and the fitted profile of a thick shell, with a power-law density profile (blue line) and a slab (red). The dashed model corresponds to the case when we fix the exponent of the power-law to 2 (see text). |
Open with DEXTER |
We constructed a simple geometrical model to try to constrain the size
and density of the matter in the HMSFSs, i.e. to deproject the
observed column densities. We represent the molecular cloud around the
H II region as a geometrically thick shell. To this we add a
slab that represents the disk of the LMC, i.e. the diffuse extended
emission. We assume a constant dust column density for the slab and a
power-law profile for the shell
(
).
The dust-mass profile and the best-fit decomposition into these two
components and the corresponding parameters are shown in
Fig. 3. We propagated the uncertainties on the dust
column density in each annulus (see Fig. 3). The
uncertainties are significant. We find for N63, for which the
over-density is weak compared to the slab (i.e. the disk of the LMC),
that the geometrical parameters are not very well constrained. In
particular, it is hard to constrain the
parameter. The
best-fit model has
,
which seems flat. If we fix
at 2, the value expected for a cloud in hydrostatic equilibrium, we
find that the distance where the slab component starts to dominate,
i.e. the intersection of the blue and red lines in
Fig. 3, is reduced from
80 to
30 pc.
4 Discussion and conclusion
Figures 2 and 3 show the power of Herschel to determine the matter distribution around HMSFSs. We investigated the effect of the new SPIRE constraints on the derived parameters and their uncertainties by also fitting the SEDs without these SPIRE data. We find that the column density of dust is often very discrepant (by more than an order of magnitude) from the values derived with the SPIRE data. The derived





The sites N44 and N63 exhibit a strikingly different behavior in the
radiation intensity profile (Fig. 2d.) The lack
of a systematic decrease of
around N44 indicates that we are
observing dust with a wide range of temperatures along each
line-of-sight. The inner annuli in N44 are affected by the superbubble
to the NE of the OB association, where high values of
are
expected. The low values of
for such a luminous SF region may
reflect clumpiness. The profile is clearly incompatible with a
centrally illuminated optically thin irradiation profile. It is clear
from Fig. 1 that the studied regions are not very
spherically symmetric (azimuthally smooth). In particular, N44
harbours several clusters and the peak of the X-ray emission is
located in a cavity,
20-30 pc away from the TIR peak (see
Fig. 1). Measuring the azimuthally averaged properties
smears out some of the characteristics. This smearing could have been
the cause for the lack of trend seen in the average U as seen by the
dust (Fig. 2). We verified that this small range of
is not simply an artifact of this averaging or a wrong choice
of center of the annuli by studying the parameters we derived pixel by
pixel in the maps, which makes no assumptions about the geometry.
Indeed, the highest
in N44 is found close to the center we
chose. Except for the very center all other values with their scatter
are within the range as depicted in Fig. 2. We conclude
that the choice of center does not dominate the lack of trend of N44
in the average radiation field. Thus this lack of trend reflects the
true broad range of irradiation conditions along all lines of sight in
N44, which is an indication of the inhomogeneity of the ISM around
N44. A simple dust model shows a deficit in PAHs toward the centers of
these two regions. We find no evidence for a submm excess. We have the
observed dust column densities surrounding N44 and N63 to derive a 3D model for these regions for the first time.
We acknowledge financial support from the NASA Herschel Science Center, JPL contracts # 1381522 & 1381650. We thank the contributions and support from the European Space Agency (ESA), the PACS and SPIRE teams, the Herschel Science Center and the NASA Herschel Science Center (esp. A. Barbar and K. Xu) and the PACS and SPIRE instrument control centers, without which none of this work would be possible. We thank the referee, Glenn White, for comments that improved the paper.
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Footnotes
- ... LMC
- Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.
All Figures
![]() |
Figure 1:
False color images of the surroundings of N44 and N63. IRAC 4 (8.0 |
Open with DEXTER | |
In the text |
![]() |
Figure 2: Summary of main results. We show the SEDs of the two SF regions on the left. The black symbols show the integrated photometry of three different annuli, lines are the best-fit models and the colored trianglesrepresent the synthetic photometry in the corresponding filters. The derived dust column density (panel c)), mean radiation field energy-density (panel d)), and the PAH mass fraction (panel e)) as a function of annulus size are shown on the right. The error-bars on the parameters in Panels c), d), e) were derived by propagating the variance on the photometry with a Monte-Carlo method (see Sect. 2). |
Open with DEXTER | |
In the text |
![]() |
Figure 3: Derived geometrical parameters of the two regions. We show the dust column density and the fitted profile of a thick shell, with a power-law density profile (blue line) and a slab (red). The dashed model corresponds to the case when we fix the exponent of the power-law to 2 (see text). |
Open with DEXTER | |
In the text |
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