Issue |
A&A
Volume 508, Number 2, December III 2009
|
|
---|---|---|
Page(s) | 645 - 664 | |
Section | Extragalactic astronomy | |
DOI | https://doi.org/10.1051/0004-6361/200912963 | |
Published online | 08 October 2009 |
A&A 508, 645-664 (2009)
Probing the dust properties of galaxies up to submillimetre wavelengths
I. The spectral energy distribution of dwarf galaxies using LABOCA
M. Galametz1 - S. Madden1 - F. Galliano1 - S. Hony1 - F. Schuller2 - A. Beelen3 - G. Bendo4 - M. Sauvage1 - A. Lundgren5 - N. Billot6
1 - Laboratoire AIM, CEA, Université Paris Diderot, IRFU/Service
d'Astrophysique, Bât. 709, 91191 Gif-sur-Yvette, France,
2 - Max-Planck-Institut für Radioastronomie, Bonn, Germany
3 - Institut d'Astrophysique Spatiale, Orsay, France
4 - Imperial College, London, UK
5 - ESO, Santiago, Chili
6 - Caltech, Pasadena, USA
Received 23 July 2009 / Accepted 28 September 2009
Abstract
Aims. We study the dust properties of four low
metallicity galaxies by modelling their spectral energy distributions.
This modelling enables us to constrain the dust properties such as the
mass, the temperature or the composition to characterise the global ISM
properties in dwarf galaxies.
Methods. We present 870 m images of four low metallicity galaxies
(NGC 1705, Haro 11, Mrk 1089 and
UM 311) observed with the Large APEX
BOlometer CAmera (LABOCA) on the Atacama Pathfinder EXperiment (APEX)
telescope. We modeled their spectral energy distributions combining the
submm observations of LABOCA, 2MASS,
IRAS, Spitzer photometric data,
and the IRS data for Haro 11.
Results. We found that the PAH mass abundance is
very low in these galaxies, 5 to 50 times lower than the
PAH mass fraction of our Galaxy. We also found that a
significant mass of dust is revealed when using submm constraints
compared to that measured with only mid-IR to far-IR observations
extending only to 160 m. For NGC 1705 and Haro 11, an
excess in submillimeter wavelengths was detected when we used our
standard dust SED model. We rerun our SED procedure adding a
cold dust component (10 K) to better describe the high
870
m
flux derived from LABOCA observations, which significantly improves the
fit. We found that at least 70
of the dust mass of these two galaxies can reside in a cold dust
component. We also showed that the subsequent dust-to-gas mass ratios,
considering HI and CO observations, can be strikingly high for
Haro 11 in comparison with what is usually expected for these
low-metallicity environments. Furthermore, we derived the star
formation rate of our galaxies and compared them to the Schmidt law.
Haro 11 falls anomalously far from the Schmidt relation. These
results may suggest that a reservoir of hidden gas could be present in
molecular form not traced by the current CO observations.
While there can be a significant cold dust mass found in
Haro 11, the SED peaks at exceptionally short wavelengths
(36
m),
also highlighting the importance of the much warmer dust component
heated by the massive star clusters in Haro 11. We also
derived the total IR luminosities derived from our models and
compared them with relations that derive this luminosity from Spitzer
bands. We found that the Draine & Li (2007) formula compares
well to our direct IR determinations.
Key words: galaxies: ISM - galaxies: dwarf - infrared: ISM - dust, extinction
1 Introduction
The understanding of the evolution of a galaxy requires knowledge of
the roles of the different actors controlling the evolution of the
interstellar medium (ISM) and the subsequent feedback on star formation
activity. Despite its low fraction of the total mass of a galaxy (less
than 1),
dust plays a prominent role in the heating and cooling of the ISM and
thus tightly influences the overall physics of a galaxy. Since dust
absorbs the stellar radiation and reemits it in a wide range of
wavelengths, the star formation rate (SFR) as well as other fundamental
parameters of a galaxy, such as its age, can be indirectly studied
through the dust emission itself. The spectral energy distribution
(SED) of a galaxy is its spectral footprint from which we can study the
physical processes taking place in the galaxy since it synthesises the
contribution of all its components to the emission of the galaxy. Using
this tool, we can peer into the window of the integrated history of the
galaxy and disentangle the various physical actors (stars, HII regions,
molecular clouds) and processes (stellar radiation, dust emission)
involved (Draine
et al. 2007; Galliano et al.
2008, see also Sect. 5 of this paper).
Table 1: General properties of the sample.
While dust hinders the interpretation of ultraviolet (UV) and optical wavelengths, in the mid infrared (MIR), far infrared (FIR) and submillimetre (submm) wavelengths, dust emission and absorption properties expose different physical environments, from the most vigorous star formation and AGN activity (e.g. Wu et al. 2007; Gordon 1995) to the more quiescent diffuse media (Bernard et al. 1996; Arendt et al. 1998). Many processes linked to star formation such as stellar winds (Hoefner 2009), supernovae shocks, photodestruction by high-mass stars etc. can also affect the spatial distribution and the local properties and abundance of the different dust components of a galaxy such as polycyclic aromatic hydrocarbons (PAHs, O'Halloran et al. 2006), amorphous carbon grains, silicates or composite grains, manifesting themselves in the MIR to submm wavelengths.
Studying the interplay between galaxy properties and metal
enrichment is crucial to understand galaxy evolution. The metallicity
of a galaxy is deeply linked with the dust properties of the ISM and
its substructures such as HII regions and molecular clouds,
but just how it affects the ISM is currently poorly known. Dwarf
galaxies in the Local Universe, are metal-poor galaxies, and are thus
convenient laboratories to study the effects of metallicity (Z)
on the gas and dust. They exhibit a wide variety of physical
conditions, and their star formation properties and ISM represent the
closest analogs to proto-galaxies of the early universe. Indeed, dwarf
galaxies are small and may compared to high redshift galaxies which
also present lower metallicities (Lara-López
et al. 2009). They are also considered to be the
building blocks of much larger and more metal-rich galaxies
(Review by Tosi 2003).
They also show analogies with Gamma Ray Bursts (GRB) hosts
whose ISM usually exhibit moderate chemical enrichment with a median
metallicity of 1/10
(Chen et al. 2009).
They finally show evidence for older stellar populations than their metallicity suggests (e.g. Aloisi et al. 1998), posing enigmatic issues for galaxy evolution models. Many studies have been carried out to grasp this apparent paradox. Lisenfeld & Ferrara (1998) confirmed that the dependence of the dust-to-gas mass ratio (D/G) in low metallicity galaxies was a function of metallicity using IRAS observations. James et al. (2002), Walter et al. (2007) and Hirashita et al. (2008) concluded likewise using JCMT/SCUBA submm, Spitzer MIR/FIR and AKARI (FIR) observations. Finally, Galliano et al. (2008) observed some systematic deviations between dust abundances of very low metallicity systems and what is expected for supernova-condensed dust. At MIR wavelengths, low metallicity systems also show prominent differences in the dust properties compared to the more metal-rich systems. For example, PAH features are strikingly diminished as metallicities drop (e.g. Engelbracht et al. 2005; Wu et al. 2007; Engelbracht et al. 2008; Madden 2005) compared to metal-rich galaxies, in spite of the role the smallest grains play in the energy balance of galaxies (Rubin et al. 2009). Some studies suggest that PAH emission depends on the hardness or strengh of the illuminating radiation field (Bendo et al. 2008; Engelbracht et al. 2008; Madden et al. 2006; Gordon et al. 2008). The consequence of lowering the metallicity of a galaxy is the decrease in dust opacity resulting in harder and stronger radiation fields. The dearth of PAHs in low metallicity galaxies has also been explained by the destructive effects of supernovae (O'Halloran et al. 2006,2008) or by the delayed injection of PAHs by AGB stars (Galliano et al. 2008).
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Figure 1:
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Broad wavelength coverage of the MIR to submm regime is imperative to
constrain the modelling of the observed SEDs, leading to a better
comprehension of the dust properties of galaxies. Since Spitzer
only observes dust emission at wavelengths shorter than 160 m, submm
data are necessary not only to enlarge the wavelength coverage at
longer wavelengths to verify the dust models but also because the
potential reservoir of cold grains (
15 K), which contribute to this submm
flux, may account for a significant amount of mass. Only a handful of
galaxies of the Local Universe have been studied using submm
ground-based instruments (e.g. JCMT/SCUBA).
When submm observations of dwarf or late-type galaxies are studied, an
excess in the dust SEDs is often found in the mm/submm domain (Bendo
et al. 2006; Dumke et al. 2004; Böttner
et al. 2003; Galliano et al. 2005,2003;
Marleau
et al. 2006; Lisenfeld et al. 2001).
This excess can be interpreted as very cold dust (
10 K),
in which case more than 50
of the total dust mass of these galaxies should reside in a very cold
component. Cold dust is also needed to explain the break in the gas to
dust mas ratio as a function of metallicity relaion for low-metallicity
galaxies (Muñoz-Mateos
et al. 2009; Galliano et al.
2008). The presence of this cold dust component is still a
contentious issue in the ISM community and will have important
consequences on our comprehension of ISM properties of low
metallicity environments. Lisenfeld
et al. (2001), Reach
et al. (1995), Dumke
et al. (2004), Bendo
et al. (2006) or Meny
et al. (2007) suggested that changes in dust
emission properties (changes in dust emissivity or resonances related
to dust impurities) should be responsible for boosting submm emission
above the 15-20 K thermal emission expected at these
wavelengths. However, not all low metallicity galaxies show submm
excess, as shown recently by the observations of the nearby Local Group
Galaxy IC 10 (Parkin et al. 2009, in prep.),
where the main two star forming regions were isolated with ISO, Spitzer
and 850
m
observations, the SEDs were modeled without invoking a very cold dust
component. Moreover, Draine
et al. (2007) showed that their observations of
mostly metal-rich galaxies can largely be reproduced by dust models
which do not account for a very cold dust component, even in their
limited number of cases where submm observations are present. Studies
using submm observations for a wider range of metallicity values are
necessary to check the relevance of these conclusions for low
metallicity environments.
In this paper, we present the first APEX/ LABOCA
870 m
observations of dwarf galaxies: 1 extended galaxy
(NGC 1705) and 3 compact sources (Haro 11,
UM 311, Mrk 1089) (see Table 1). We
have combined these data with Spitzer and/or IRAS
observations to produce global SEDs that we use to model the dust
properties. The sample is small but covers a wide range of
metallicities, from
1/9
for Haro 11 to
1/3
for NGC 1705. It also presents varied morphologies,
size scales and characteristics: resolved or compact galaxies,
disturbed and even merging environments.
We describe the sample in Sect. 2 and the observations and data reduction in Sect. 3 and the images and photometry in Sect. 4. In Sect. 5, we present the SED modelling and discuss the results in Sect. 6.
2 The sample
The four galaxies studied in this paper were chosen because of their diversity in morphology, distance, metallicity and star formation activity:
NGC 1705 - this is a well
studied Local Group galaxy which is in the Spitzer
infrared nearby galaxies survey (SINGS; Kennicutt
et al. 2003). Heckman
& Leitherer (1997) found the luminosity of the galaxy
in the UV to be dominated by a central bright 105
super star cluster (SSC) also at the origin of a galactic outflow. This
SSC shows similar properties to the distant gamma ray burst hosts (Chen et al. 2007). The H
emission
extends over the entire optical emission of the galaxy (Gil de Paz et al. 2003)
while the HI emission is exceptionally extended beyond the
optical emission (Meurer
et al. 1998) and lie on either side of the SSC. Two
off-nuclear regions called D1 and D2 (Fig. 1) can be
seen to dominate the MIR and FIR dust emission (Cannon et al. 2006).
Spitzer IRS spectroscopy reveals the
PAH emission originating toward region D1 but not
toward the SSC or region D2 (Cannon
et al. 2006).
Haro 11 - also known as ESO
350-IG038, this is the most distant galaxy of the sample (92Mpc; Bergvall et al. 2000).
It possesses characteristics of an extreme starburst with
10
(Sanders
et al. 2003),
making it a luminous infrared galaxy (LIRG) with a high star formation
rate of
25
yr-1
as determined from H
,
radio continuum, FIR and hard X-ray observations (Grimes et al. 2007).
Broadband images of H
show three bright star-forming condensations with unrelaxed kinematic
structure and faint extended shell structures in the outer regions of
the galaxy, all suggesting an ongoing merger (Östlin et al. 1999; Bergvall
& Östlin 2002). Haro 11 is a moderately
strong radio source (essentially free-free continuum) with extended
continuum emission at 6 and 20 cm (Heisler & Vader 1995).
It is a very metal poor galaxy (Z
1/7
that seems to have a very
little neutral hydrogen, an unusually high
ratio between blue luminosity and HI mass and little observed
molecular gas (Bergvall
et al. 2000).
Mrk 1089 - Mrk 1089 is
a Wolf-Rayet (WR) galaxy (Kunth
& Schild 1986) and is the most luminous of the eight
members of the Hickson Group 31 (Hickson
1982). The morphology of the group is very disturbed with
tidal interactions between Mrk 1089 (HCG31 C) and the
galaxy NGC 1741 (HCG31 A) (Fig. 2c). The two
galaxies present similar kinematics suggesting a single entity (Richer et al. 2003).
At the location of their interaction is a very strong
24 m
source and high levels of infrared emission can be found throughout the
whole group (Johnson
et al. 2007). Mrk 1089 and
NGC 1741 are referred to collectively as NGC 1741 in
the catalog of WR galaxies of Conti
(1991). Nevertherless, many surveys (Iglesias-Paramo
& Vilchez 1997; Johnson & Conti 2000; Conti
et al. 1996; Rubin et al. 1990)
showed that the interacting system was undergoing a starburst which was
attributed to HCG31 C. We thus decide, in this paper, to
designate the interacting system compounded of HCG31 A and
HCG31 C together as Mrk 1089.
UM 311 - This compact HII galaxy
(Terlevich et al. 1991)
is located between the pair of spiral galaxies NGC 450 and
UGC 807, 2 galaxies which were once thought to be
interacting but have now been demonstrated to be physically separated (Rubin & Ford 1983).
There are three very bright sources of compact HII emission
between the two galaxies, UM 311 being the brightest
(Fig. 2d).
The galaxy has been misidentified as a projected galactic star due to
its quasi-stellar and compact morphology. Its H luminosity and
equivalent width are remarkably high for an HII galaxy (Guseva et al. 1998).
3 Observations and data reduction
3.1 LABOCA
LABOCA is a multi-channel bolometer array for
continuum observations at 870 m, built by MPIfR (Max-Planck-Institut fur
Radioastronomie, Bonn, Germany) and mounted on APEX
(Atacama Pathfinder EXperiment), a 12-m radio telescope of
ESO, Onsala and MPIfR. The array consists of 295 channels. LABOCA
on APEX has a total field of view of 11
4
11
4 and a full width half maximum
(FWHM) of its point spread function (PSF)
18.2''.
About 30 h of observations were taken from November 9th 2007 to November 20th 2007 (Program ID: 080.B-3003(A)). The four galaxies are smaller than the FOV of LABOCA. Basic spiral patterns with 4 pointings were combined with a raster mapping mode (raster-spiral) to completely fill the array (homogenous sampling of each map), to obtain enough off-source position for background substraction and to effectively execute long integration times (8.7 h, 8.3 h, 4 h and 7.6 h for Haro 11, UM 311, Mrk 1089 and NGC 1705 respectively). Flux calibration was performed through the observations of the planets Uranus and Mars and the sources HLTAU, J0423-013, J0050-095, J0006-064, V883-ORI, PMNJ0403-3605, PMNJ0106-4034, PKS0537-441, N2071IR. We used the BOA package (BOlometer Array Analysis Software; Schuller et al., in prep.) to reduce the data. The sotware was developed through a collaboration of scientists from the MPIfR, AIfA (Argelander-Institut für Astronomie, Bonn, Germany), AIRUB (Astronomisches Institut der Ruhr-Universität, Bochum, Germany), and IAS (Institut d'Astrophysique Spatiale, Orsay, France).
The atmospheric attenuation was determined via skydips every
hour. Opacities at 638 m range from 0.103 to 0.353
throughout the observing run. Flat-fielding normalisation is applied by
dividing the signals by the bolometre gains supplied by the observatory
and thus removing the bolometre gain variations. From the 18th of
October up to the 15th of November, 33 LABOCA
pixels were shadowed by a plate in the beam. These pixels are removed.
We also masked out stationary points and data taken outside reasonable
telescope scanning velocity and acceleration limits as well as dead or
noisy channels. During the commissioning period of LABOCA,
correlated noise was found between groups of channels sharing some
parts of the electronics (amplifier boxes or cables). As our
data are not all point sources, it is necessary to carefully
differentiate correlated noise from extended emission. This correlated
noise is subtracted from each map. Moreover, we performed a correction
to suppress spikes and flatten the 1/f noise of the FFT to
remove the noise caused by thermal variations. Finally, each reduced
scan was gridded into a weighting map. These weights were built by
calculating the rms of each time series which contributes to a given
region of the map.
The major sources of uncertainty are the calibration
uncertainty and uncertainty resulting from the background variation. We
estimate the average uncertainty levels to be of 15
.
All of the galaxies were detected with a root mean square (rms)
estimated to be lower than 10 mJy/beam for three of our
galaxies but as high as 15 mJy/beam for Mrk 1089.
Some anomalous pixels at the edges of the final maps are the results of
poor coverage at the edges of the map. The anomalous pixels are ignored
in the analysis. The 870
m LABOCA images are presented
in Fig. 2.
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Figure 2:
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Figure 2: continued. |
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3.2 Spitzer data
3.2.1 IRAC
The IRAC bands cover 3.6, 4.5, 5.8, and 8 m with a FWHM
of the PSFs of 1.8, 1.8, 2.0 and 2.2 arcsec respectively
(http://ssc.spitzer.caltech.edu/documents/SOM/). Two bands are imaged
in pairs (3.6 and 5.8 microns; 4.5 and 8.0 microns).
IRAC provides 5.2'
5.2' images (pixel size of 1.2''
1.2''). Our sources were observed with IRAC in dithering imaging mode
and Mrk 1089, UM 311 and Haro 11 were
obtained through the Spitzer data archive
(post-basic calibrated data). For NGC 1705, the IRAC data were
obtained throught the SINGS data delivery page
.
Table 2
summarizes the Astronomical Observation Request (AOR) keys of each
observation. IRAC fluxes are uncertain at the
10
level due to systematic effects. The
data we obtained were compared and verified with those published in Johnson et al. (2007)
for Mrk 1089 and Cannon
et al. (2006) for NCG 1705. Images are
presented in Fig. 2.
3.2.2 MIPS
The MIPS bands cover 24, 70 and 160 m with a FWHM of the PSFs of
6, 18 and 40'' respectively
(http://ssc.spitzer.caltech.edu/documents/SOM/). The galaxies were
observed in MIPS scan mapping mode for NGC 1705 and MIPS
Photometry/Super-Res mode for Haro 11, Mrk 1089
and UM 311.
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Figure 3:
a) The positions of the short-high (green)
and low-high (red) slits of the IRS observations superimposed on the
Spitzer/3.6 |
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All of the MIPS images (see Table 2 for AOR keys) were obtained through the Spitzer data archive (raw data) and reduced using the MIPS Data Analysis Tools (Gordon et al. 2005), version 3.10 along with additional processing steps.
The individual 24 m frames were first processed through a droop
correction (to remove an excess signal in each pixel) and were
corrected for non-linearity in the ramps. The dark current was then
subtracted. Scan-mirror-position dependent and independent flats were
created in each AOR and applied to the data. Detector pixels that had
measured signals superior to 2500 DNs-1
(data numbers per second) in any frame were masked out in the following
three frames to avoid latent images in the data. Planes were fit to the
zodiacal light emission in the background regions, and third order
polynomials were fit to the background in each leg of each scan map. We
also measured scan-mirror-position dependent residual offsets in the
backgrounds. They were subtracted from the data. For NGC 1705,
we created preliminary mosaics of the data to identify transient
objects (e.g. asteroids). We also performed a robust
statistical analysis in which the values of cospatial pixels from
different frames were compared to each other and statistical outliers
to remove cosmic rays. We masked out these objects. A final
mosaic was made with data calibrated into astronomical units. The
calibration factor for the 24
m data was given in Engelbracht
et al. (2007) as 4.54
0.18
10-2 MJy sr-1
[MIPS instrumental unit]-1.
Table 2: AOR keys of the Spitzer/IRAC and Spitzer/MIPS observations.
In the 70 and 160 m
data processing, we first fit ramps to the readouts to derive slopes.
Readout jumps, cosmic ray hits and dark current were removed. The stim
flash frames taken by the instrument were used as responsivity
corrections. An electronic nonlinearity correction and an illumination
correction were applied. Short term variations in the signals
(``drifts'') were removed from all 70
m and 160
m data. To combine the photometry and
scan map data for NGC 1705 without dealing with problems of
background offsets, we subtracted the background from the photometry
map at this stage. We corrected all pixels affected by cosmic rays
(see 24
m
data treatment for details). Then, final mosaics were built, residual
backgrounds were subtracted and the data calibrated. The 70
m
calibration factors given in Gordon
et al. (2007) are 702
35 MJy sr-1 [MIPS instrumental
unit]-1 for coarse-scale imaging and
2894
294 MJy sr-1 [MIPS
instrumental unit]-1 for fine-scale imaging. The
160
m
calibration factor is given by Stansberry
et al. (2007) as 41.7
5 MJy sr-1 [MIPS instrumental
unit]-1. An additional 70
m
nonlinearity correction given as f70(true) =
0.581
f70(measured)1.13 (Dale et al. 2007) was
applied where the surface brightness exceeded
66 MJy sr-1. MIPS flux
uncertainties were estimated to be 10
in the MIPS 24
m
band and 20
in the MIPS 70 and 160
m bands. The fluxes calculated compared to those
published in Johnson
et al. (2007) for Mrk 1089 and Cannon et al. (2006)
for NCG 1705.
3.2.3 IRS
For the galaxy Haro 11, we supplemented our dataset with the
mid-IR spectrum from the Spitzer Infrared
Spectrograph (IRS) in order to better constrain the 5 m to
40
m
range of the SED. We used public released data (Spitzer
AOR key: 9007104) performed in staring mode. We used the Basic
Calibrated Data products available in the Spitzer
archive for the short-low resolution channel (SL, 5.2-14.5
m;
/
60-120) and the two high resolution channels: short-high (SH,
9.9-19.6
m;
/
600) and long-high (LH, 18.7-37.2
m;
/
600). IRSClean was applied to the individual files to mask out hot
pixels, and the frames were coaddd together. We then used the Spitzer
IRS Custom Extraction software (Spice -
2.0.1 version) to extract the spectrum. We subtracted
background contributions estimated from zodiacal models using the
software SPOT (18.0.1 version -
http://ssc.spitzer.caltech.edu/propkit/spot/). We finally subtracted a
background estimated using zodiacal models in SPOT. The final error on
the photometry derived from peak-up acquisition windows is about 15
,
the value recommended by the IRS data handbook. Finally, the
spectrum is shifted from a redshift of z=0.021 (Bergvall et al. 2000)
to rest wavelengths. The position of the slits of the IRS high
resolution observations is shown in the panel on the left in
Fig. 3.
The spectrum with labels identifying the main emission features is
shown in the panel on the right in Fig. 3. The 6.3,
7.6, 8.2 and 11.3
m
PAH features are clearly detected as well as significant
emission lines. Note that
NeIII/NeII ratio = 3.2 (calculated on the
IRS spectrum), which is an indication of the hard radiation
field dominated by a young population
5 Myr (Madden
et al. 2006).
3.3 Supplemental data
We supplement the Spitzer and LABOCA
observations with 2MASS J, H, K flux
density estimates available on the NASA/IPAC Infrared Science Archive
to describe the stellar contribution of the SEDs of the galaxies
Mrk 1089, Haro 11 and NGC 1705. We assume
that these 2MASS flux densities are global
measurements for the galaxies. For the UM 311 system, we
perform the photometry and estimate the 2MASS flux
densities from the images also obtained from the NASA/IPAC Infrared
Science Archive. The IRAS broadband flux densities at 12, 25, 60 and
100 m
are finally obtained through the NASA/IPAC Infrared Science Archive,
the IRAS Faint Source catalogue, |b| > 10,
Version 2.0 (Moshir
et al. 1990), the IRAS catalogue of Point Sources,
Version 2.0 (IPAC 1986) and Dultzin-Hacyan et al.
(1990). They are added to supplement the existing data on
dust emission. For Haro 11, the IRAS fluxes are consistent
with the values of the IRS spectrum. For UM 311, IRAC
data should probably encompass emission from both of the nearby
galaxies and are thus not used in the analysis.
4 Images
4.1 Discussion on the morphology
The 870 m
LABOCA maps are presented in Fig. 2. The
contours of the IRAC observations - 4.6
m for
Haro 11 and 8
m for UM 311, Mrk 1089 and
NGC 1705 - are superimposed on the LABOCA images.
NGC 1705 - there is significant
change in the galaxy morphology from NIR to FIR wavelengths.
The bright 3.6 m
source is observed toward the location of the SSC while two strong MIR
and FIR emission peaks appear at 5.8
m and longer
wavelengths, offset from the SSC and coincident with the H
maximum
(Figs. 1
and 2a).
These two off-SSC emitting regions do not have bright stellar
counterparts. The Spitzer 8
m image
shows the SSC in the middle of these two off-nuclear
HII regions. The eastern region is the brightest source at
24
m,
with a flux density which is two times higher than the
SSC flux density at this wavelength (Cannon et al. 2006).
The three regions are also barely resolved in the 870
m images.
An offset peak is detected toward the west of the centre of
the galaxy. Two faint 24
m sources are possible counterparts of the
emission.
Haro 11 - this galaxy is not resolved by Spitzer
at wavelengths greater than 4.5 m. It is clearly detected but barely
resolved with LABOCA (Fig. 2b). The
final images present extended structures but this extension is not
observed in the MIR images and was removed while calculating the submm
flux to be conservative.
Mrk 1089 - the 8 m image
(Fig. 2c)
clearly shows the interaction between the galaxies NGC 1741
(East) and Mrk 1089 (West). A Spitzer
color composition image of the complete Hickson group observed with Spitzer
is described in Johnson
et al. (2007). The merging center of
Mrk 1089 dominates the emission at MIR, FIR and 870
m. Diffuse
emission probably linked with intergalactic dust, presumably from
galaxy interactions, is detected through out the whole region and was
removed while performing the photometric measurements.
UM 311 - the 4.5 m image of
the interacting field (Fig. 2d) shows the
spiral structure and arms of NGC 450 as well as the spiral
companion UGC 807 and the three bright HII regions
between these two spirals, one of which is the UM 311. We
adopt the same numbering as Moles
et al. (1994) to describe these
3 HII sources and will call them
``the UM 311 system''. UM 311 is the region
called 3 on the 4.5
m image. This compact HII galaxy is the
brightest source of emission at 24
m. In the LABOCA image,
the emission peaks toward the location of UM 311. The galaxy
should dominate the SED of the UM 311 system.
4.2 Photometry
Table 3: Integrated flux densities measured with 2MASS, IRAS, Spitzer and LABOCA.
We use the function aper of the library IDL astro of the NASA Goddard Space Flight Center to perform the aperture photometry. For the Spitzer photometric data, the background is estimated using annuli just outside the boundaries of our galaxies. For the LABOCA images, the background significantly varies in intensity throughout the entire map. We calculated the flux densities in small circles in the immediate surroundings of the galaxy and averaged them to determine a local background for each source which was removed during the photometric calculation.
To determine the flux densities at IRAC and MIPS bands of our
sources and compare data between different wavelengths, the
observations are convolved and regridded to a common resolution. For
NGC 1705 and Haro 11, the lowest spatial resolution
is the resolution of MIPS 160 m (40''). We use convolution kernels (Gordon et al. 2008)
which convert a higher resolution IRAC/MIPS point-spread function (PSF)
to lower resolution IRAC/MIPS PSF using Fourier transforms. For the LABOCA data,
we convolved the observations with a Gaussian kernel and
regridded the images to the resolution of MIPS 160
m. The
photometric aperture chosen has a diameter of 144'' for these two
galaxies to encompass the entire emission of the galaxy.
As Mrk 1089 was not observed at 160 m, the four
IRAC bands and the MIPS 24 and 70
m observations were regridded to the resolution
of LABOCA (18.2''). We choose an aperture of 72''
avoiding the flux arising from the other nearby companions. However,
Mrk 1089 clearly dominates the whole system at
MIR-FIR wavelengths.
For UM 311, the resolution of the MIPS bands and the
proximity of the 2 nearby HII regions makes it
difficult to study UM 311 alone. We decide to perform the
photometry of the UM311 system (encompassing
sources 1-3 in Fig. 2d). The
2MASS, IRAC and MIPS 24 and 70 m images were regridded to the LABOCA resolution
of 18.2'' for the UM 311 system. In the 160
m image, the
broad PSF may cause emission from other sources outside the region
around UM 311 to bleed into that region (Fig. 2d).
To be conservative, we choose
a 54'' aperture which encompasses the
UM311 system and use the 160
m observation as an upper limit when modelling
the SED of this system. The procedure we use to model this system gives
us solutions for the limits on the parameter space for UM 311
as if this interacting system were more distant causing these
3 sources to blend together.
The IRAC measurements require aperture corrections to account
for the scattering of incident light in the focal plane arrays (Reach et al. 2005).
These scaling factors of 91, 94, 71, 74
are respectively applied to the final integrated flux density estimates
at 3.6, 4.5, 5.8 and 8
m. Table 3 presents the
IRAC flux densities corrected for the scaling factors.
Finally, we compare the fluxes obtained from Spitzer
observations with the IRAS broadband fluxes. MIPS
24 m
and IRAS 25
m as well as IRAS 60
m and MIPS
70
m
are consistent for the galaxies where both are available except for
Haro 11 for which IRAS fluxes are
systematically higher than MIPS fluxes due to the fact that IRAS
fluxes were estimated using bigger aperture. The IRAS
25
m
flux is not used since we use the IRS spectrum as a constraint
for that part of the SED. The IRAS 100
m flux
values seem to be high for Mrk 1089 and NGC 1705,
perhaps encompassing more extended emission. We will see in
Sect. 5 what this implies for the SED modelling.
4.3
Contamination of the 870
m
emission from non-dust origins
Since we are interested here in the dust emission arising in the
870 m
band, we must consider and quantify possible contamination from
non-dust sources and take these corrections into account when modelling
the dust SEDs. The CO(3-2) line can, in principle fall within
the 870
m
band. While CO(1-0) has been a great challenge to detect in low
metallicity galaxies (cf. Leroy
et al. 2005), we can not be sure that the smaller
beam, higher excitation CO(3-2) could not be present here.
CO observations were attempted in NGC 1705 without
positive detections (Greve
et al. 1996). In the same way, CO seems to
be very faint in the Hickson Group to which Mrk 1089 belongs (Yun et al. 1997).
Finally, for Haro 11, Bergvall
et al. (2000) found an upper limit for
of 1029 W. We can derive an upper limit
to
from the
estimation using the Meier
et al. (2001) relations for dwarf starburst
galaxies:
/
is usually lower
than 1. For the four galaxies, we
conservatively estimate the CO(3-2) contribution to the
870
m
band to be
5
.
Additionally, we can expect contributions to the 870 m fluxes
from radio continuum emission (synchrotron emission and/or
bremsstrahlung). Three radio fluxes were estimated for Haro 11
with the NRAO VLA Sky Survey (8.46 and 1.4 GHz - Condon et al. 1998)
and the Sydney University Molonglo Sky Survey
(843 MHz - Mauch
et al. 2003). We derive the 870
m radio
continuum contribution by extrapolation of the radio data
tendancy (
).
We find a radio contribution of 3
of the LABOCA flux for Haro 11.
The radio observations in the literature are not sufficient to
constrain the expected 870
m radio contamination for NCG 1705,
UM 311 and Mrk 1089. We thus consider that the radio
continuum contamination is of the same order for these other galaxies.
Finally, we conservatively estimate the global non-dust contamination
from potential CO(3-2) emission and radio continuum emission
(synchrotron/bremsstrahlung) in the 870
m band to be 10
for our four galaxies, similar to the submm contributions that Galliano et al. (2005),
for example, determine for their dwarf submm observations.
5 The SED modelling
The SED is a complex tool to interprete. For a macroscopic region of the ISM (HII region, cirrus), the SED summarises a wide range of physical conditions linked with the non-uniformity of its illumination and the variations of the dust composition. For an entire galaxy such as the dwarf galaxies we are studying here, the SED synthesises, on the contrary, the different components that constitute its global shape and emission: HII regions, molecular clouds, nebulae, diffuse ISM etc., that can not be studied independantly due to the lack of observational constraints.
We want to construct the SEDs of our galaxy sample using the
fluxes presented in Table 3 and the
IRS spectrum for the galaxy Haro 11 as constraints in
order to quantify elementary quantities of these galaxies such as their
mass of PAHs or their total mass of dust. The stellar contribution to
the SED is constrained by the 2MASS bands and IRAC 3.6 m. The NIR
to submm wavelengths of the SEDs, signatures of the dust and physical
conditions of the galaxies, are constrained by IRAS,
Spitzer and our new LABOCA data
(Table 3).
No radio component is taken into account as a model constraint
but the radio contribution is removed from the 870
m flux
(see Sect. 4.3).
The model we use to fit the SEDs is a simplified version (due to the smaller number of observational constraints) of the Galliano et al. (2008) model. We would first like to note that a SED depends on the intensity and the hardness of the Interstellar Radiation Field (ISRF) that the ISM experiences, on the mass fraction of the dust species (silicate and carbon grains, PAHs etc.) and on the distribution of grain sizes. Thus, modelling a SED requires making a priori assumptions on the ISRF and on the global properties of the dust, assumptions that we will describe in the following paragraphs.
We assume that the source of excitation of the dust is the
ISRF which we choose to have the spectral shape of the ISRF found in
the Galactic diffuse ISM (Mathis
et al. 1983), although we test the influence of this
spectral shape by trying a variety of forms
(see Sect. 6.4). The ISRF intensity will be scaled
using a factor U (defined in Draine & Li 2007),
with U = 1 corresponding to a
normalization to the local solar neighbourhood value of 2.2 10-5 W m-2.
We assume that the sources of IR emission are dust and old
stars. We suppose that the dust composition is homogeneous throughout
the galaxy. For silicates, graphites and PAHs, we adopt the composition
and size distribution of Zubko
et al. (2004) (Table 4). Zubko et al. (2004)
assume that the dust particules are PAHs, graphite and silicate grains
and that the ISM has a solar abundance. The assumed optical properties
of these grains are taken from Draine
& Li (2007, PAHs), Laor
& Draine (1993, graphites) and Weingartner & Draine (2001,
silicates). The total mass of dust (
)
represents the first parameter of our model while the
PAH component requires the introduction of two other
parameters, the ionised PAHs-to-neutral PAH ratio (
)
and the PAH-to-total dust mass ratio (
)
normalised to the Galactic value of 0.046, to be described.
Table 4: Size range and mass densities of the three dust grain components from Zubko et al. (2004).
We adopt the prescription of Dale
et al. (2001) to relate the dust mass exposed to a
given intensity d
(U) to the
different heating environment intensities (U)
to which dust is exposed.
This prescription is flexible enough to describe dense and diffuse media. The simple power law relation leads to the definition of the index




Since the stellar component contributes to the NIR part of the
SED, we finally add it from the dust SED by fitting a stellar spectrum.
This spectrum is synthesised using the stellar evolution code PEGASE (Fioc & Rocca-Volmerange 1997)
assuming a Salpeter Initial Mass Function (IMF). The stellar population
is considered to have undergone an instantaneous burst
(5 Gyr ago) and the initial metallicity is assumed to
be solar ().
The mass of stars (
)
is introduced as a parameter of our modelling.
In summary, the free parameters used in the modelling are:
![\begin{eqnarray*}\begin{array}{lp{0.8\linewidth}}
M_{\rm dust} & total mass of d...
...sity\\ [2pt]
M_{\rm oldstar} & mass of old stars. \\
\end{array}\end{eqnarray*}](/articles/aa/full_html/2009/47/aa12963-09/img36.png)
The modelling is an iterative process in which we assume an initial dust grain distribution (size and composition). Optical and near-IR data are first used to constrain the stellar radiation of the model. We then compute the temperature distribution of the dust grains heated by the absorption of this stellar radiation using the method of Guhathakurta & Draine (1989). Synthesised spectra are finally computed for each of the silicates, graphites, neutral and ionized PAHs, considering that grains are stochastically heated. The sum of these discrete contributions leads to a global SED model of the galaxy.
The interactive fitting stops when deviations from the
observational constraints are minimized. The 2 minimisation
algorithm is based on the Levenberg-Marquardt methods.
To prevent
from being influenced by the density of points or dominated by the
highly sampled MIR spectrum in the case of Haro 11,
we weight each data point depending on the density of points around its
wavelength.
(
i)
represents the error on the luminosity at a given wavelength.
![]() |
(2) |
We will call this first model the ``fiducial'' model.
Our model presents some limits mainly linked to the assumptions we made to simplify the model. Indeed, we choose the radiation field shape of the Galaxy (Mathis et al. 1983), a profile which could be different in low-metallicity environments. The choice of a radiation field profile usually affects the PAH and small grains mass derived from the modelling. The influence of this parameter is discussed in Sect. 6.4. Another strong assumption was in the use of the Dale et al. (2001) prescription (Eq. (1)). This formula directly relates the cold and the hot regions of the galaxy, an assumption which is not valid if cold dust is physically residing in different regions than star forming regions. The fact that a separate cold dust component is required for some of our galaxies (see Sect. 6.2) may be a sign of the limit of the Dale et al. (2001) prescription. Nevertherless, our simple model has the sufficient level of complexity (e.g. detailed dust properties) to accurately derive the global properties we want to study, especially as regards to our small number of observational constraints for each galaxy. Adding other components such as different phases, clumps or more complex geometries would have lead to an overinterpretation of the observations.
An international conference was held (2005) to discuss other SED models. We refer the readers to the reviews of this conference in Popescu & Tuffs (2005).
![]() |
Figure 4:
SED models of Mrk 1089, the UM 311 system,
NGC 1705 and Haro 11 using the fiducial model. The
SEDs are plotted in black. Observational constraints (listed in
Table 3)
are superimposed (filled circles). The green and red lines respectively
distinguish the stellar and the dust contributions. The dashed black
lines present the SED models of our galaxies obtained when the
LABOCA constraint is not used in the modelling. The open circles
represent the expected modeled fluxes integrated over the instrumental
bands. When the error bars are not shown, the errors are smaller than
symbols. Note that the IRS MIR spectrum used in the modelling
is overlaid in orange for Haro 11. For the UM 311
system of 3 compact sources, the 160 |
Open with DEXTER |
6 Analysis
6.1 Results of the fiducial SED modelling
Table 5: Parameters of our SED models using or not submm constraints and Dust-to-Gas mass ratios of our galaxies.
Table 6:
Parameters of our SED models for the UM311 system using
different values for the 160 m constraint.
The SED models are presented in Fig. 4, along with the
observations. Haro 11 observations are displayed corrected to
rest wavelengths taking into account its redshift. The Haro 11
IRS spectrum, from 5.1 m to 37.2
m, provides additional constraints to better
describe the PAH properties as well as the slope of the rising
MIR continuum. We perform SED models using the 870
m
observational constraint, and then compare to the resulting parameters
when we remove the 870
m data to study the influence of the submm data
on the parameters of the modelling, especially the dust mass of the
galaxy (Table 5).
To quantify the errors on our dust mass determinations, we produced a
grid of 500 randomly modified observational constraints,
allowing the observational fluxes to vary within their error bars,
following a Gaussian distribution around their reference
value. Before entering into the details of each galaxy, we can already
notice that the
,
which is normalized to the Galactic value, is always inferior
to 1, which is consistent with the fact that low-metallicity
galaxies usually show a PAH deficit compared to
dustier galaxies (Engelbracht
et al. 2005; Wu et al. 2007; Engelbracht
et al. 2008; Madden 2005). For
NGC 1705, 11.3
m PAH emission was nevertherless
detected with IRS spectroscopy in the most luminous of the two
dust emission peaks (D1) but not in the second off-nuclear
region nor in the SSC (Cannon
et al. 2006), so most of the PAHs should reside
in D1. Finally,
is
quite similar for the three galaxies, with Haro 11 having the
smaller
.
Dale
et al. (2005,2007) found that
was typically 2.4 for SINGS galaxies while Draine et al. (2007)
fixed it at 2 in their SED modelling. Our values are smaller
than 2 for NGC 1705 and Haro 11. Note that
for a given
,
galaxies with smaller
usually contain more strongly heated regions and therefore are more
likely to be associated with intense star formation activity.
Mrk 1089 - in spite of the lack of
160 m
observations, we are able to fit the observations accurately both with
and without the LABOCA observations.
Notice how flat the peak of the SED is in the FIR (Fig. 4). The slope of
SINGS galaxies is positive between 60 and 100
m whereas
the slopes of the dwarf galaxies here (Mrk 1089 but also in
NGC 1705 and Haro 11) are flat or descending in that
wavelength range. This rather flat form of the SED is not
characteristic of our Galaxy nor is it common in other more metal rich
galaxies, but is often seen in the SEDs of active low metallicity
galaxies, such as IIZw40 and He2-10 (Galliano et al. 2005,2003),
in the Large Magellanic Cloud (Bernard
et al. 2008) or in the SEDs of Dale et al. (2007).
There are two possible explanations for this: the lower metal abundance
and the decrease in dust attenuation result in a higher overall
interstellar radiation field and/or the increased abundance of very
small stochastically-heated grains can inflate the continuum on the
Wien side of the SED. We find a total dust mass of 5.12
107
(
20
). This mass
is a factor of 1.7 larger than that we would calculate without
submm constraints. This galaxy is the least affected by the submm
constraint. Nevertherless, this increase is superior to the error bars
estimated for this galaxy.
The UM 311 system - the 160 m beam is
too large to isolate the UM 311 system alone and,
without this data, we lack sufficient observational constraints at
FIR wavelengths to accurately determine the shape of the
SED peak for the system. Instead we measure the 160
m flux in a
bigger aperture (80'') than the one chosen to measure the
fluxes in the other bands (54'') and use the 160
m flux as an
upper limit. To explore the range of parameter space constrained by the
160
m
upper limit, we decrease the 160
m flux in steps of 10
down to 50
and find the range of shapes with associated parameters that could fit
our observational constraints (see Fig. 4 and Table 6).
We also produced a grid of 200 randomly modified observational
constraints to study the spread of the SED models induced by these
uncertainties. These tests enable us to establish a range of possible
dust masses for this galaxy system. We conclude that the dust mass of
the system should reside between 5.2
106 and 1.1
107
,
and
should reside between 1.79 and 2.13 (Table 6).
The various SED models obtained include both solutions that
maximise the contribution from the hot dust with
a FIR peak at about 50
m and solutions that, on the contrary, favor a
large dust mass, peaking at longer wavelengths.
We convolve the 8 m
IRAC images of the UM 311 system to the resolution of MIPS
24
m
and calculate the luminosities of the 3 different
substructures at these wavelengths. The luminosities in
of region 1 and 2 are respectively 1.5 and
2.9 times lower than that of UM 311
(region 3) at 8
m and respectively 2.6 and
8.4 times lower at 24
m. Thus, we obtain different
8/24 luminosity ratios for the 3 different regions,
respectively 0.36 and 0.61 for region 1
and 2, and 0.21 for UM 311 which compares
with the value of 0.24 obtained for the whole
UM 311 system. These ratios imply that
region 2, which has the lowest 24
m flux, may
be relatively less active than the others, if we use the 24
m flux as a
good indicator of the star formation activity of the region (Relaño
et al. 2007; Helou et al. 2004). On
the contrary, UM 311, having the highest 24
m continuum
should present the strongest star formation activity of the system.
Moreover, even if the system is not clearly resolved at 70
m, its
emission clearly peaks at the location of UM 311. This leads
to the conclusion that the galaxy UM 311 should dominate the
system at MIR and FIR wavelengths and the global dust SED of
the UM 311 system. The galaxy should account for the
major part of the hot dust mass of the system. If more distant, the
3 objects would blend, like the 3 distinct nuclei of
Haro 11 which can be resolved by HST but not resolved
with Spitzer.
Table 7: Parameters of the SED models introducing a cold dust component at 10 K.
NGC 1705 - Fig. 4 presents the fit
which gives the lowest 2
for this galaxy. The model fails to fit the IRAS
100
m
data when we introduce the LABOCA constraint but does fit this
constraint when the SED is modeled with constraints up to 160
m. We test
the influence of the IRAS 100
m flux on
the fit performing SED models with and without this data point but with
the submm constraint. The global shape of the SED does not change and
the dust masses derived in these 2 cases vary by less
than 5%. Cannon
et al. (2006) estimated the dust mass of
NGC 1705 using the models of Dale
& Helou (2002) and Li
& Draine (2001), obtaining respectively (3.8
1.9)
105
and 7
104
(
50
). The model
of Li & Draine (2001)
combines laboratory studies and astronomical observations and fits the
MIPS fluxes very well. The dust mass deduced from the Li & Draine (2001)
model, accounting for its 50
uncertainty
and the different distance they used (5.1 Mpc), compares well
with our results obtained without the submm constraint: 3
104
(Table 5).
Including the submm LABOCA constraint, we obtain a
dust mass of 1.3
106
,
which is 50 times higher than our results without the submm
data. In any event, our fiducial model, even using the 870
m
observations, is not satisfactory and gives a poor
2 value.
For this galaxy, the uncertainty in the mass estimate obtained using
the submm constraint is mostly due to the flattening FIR peak
and to the elevated 870
m emission, for which the model has difficulty to
find a consistent solution. Considering that the error in the dust mass
reaches more than 50
,
we consider this first dust mass estimate obtained with our fiducial
model uncertain and not satisfactory for this galaxy.
Haro 11 - the SED of Haro 11 is
very striking in that it peaks at very short wavelengths -
36 m,
highlighting the extreme nature of the young starburst. This is also
evidenced by the high global value of the Ne[III]/[NeII] ratio
(ratio > 1), already seen in other low
metallicity dwarf galaxies (Madden
et al. 2006), which is normally an indication of the
hard interstellar radiation field dominated by a young
(<5 Myr) stellar population. The peak of the IR SED
compares to that of the 1/40
galaxy SBS0335-052 (Houck
et al. 2004) or IC 10 NW (Parkin
et al. 2009, in prep.). The IRS spectroscopy
provides a tight constraint on the slope of the hot MIR dust continuum
emission as well as for the
.
The model does not clearly fit all the details of the
IRS spectrum due to the lack of sophistication and flexibility
in the dust properties. More complex modelling would be required to
perfectly model the different features of the spectrum but this does
not affect the following conclusions on the dust mass parameter. Engelbracht et al. (2008)
previously estimated the total dust mass of the galaxy to be
6.2
106
using Spitzer observations and a distance of
87 Mpc. This value is consistent with the dust mass we obtain
without submm constraints for a distance of 92 Mpc:
7.2
106
.
Note that when the IRS spectrum is not used for the modelling
but only IRAC broabands, the dust mass is estimated to be 2
108
with a poor-fit (
2 = 24).
Thus the IRS spectrum greatly influences and constrains the
global shape around the peak of the SED.
The large uncertainty in the dust mass estimated from the
modeled SED (the error reaches 40
for this galaxy) is due to the excess emission at submm wavelengths
that the model does not fit (Fig. 4). Such submm excess
was already observed in other galaxies using submm instruments such as
SCUBA on the James Clerk Maxwell Telescope (JCMT) (Bendo
et al. 2006; Galliano et al. 2005,2003;
Marleau
et al. 2006) and usually leads to different
interpretations. Galliano
et al. (2005,2003) proposed that the
submillimeter excess in the dwarf galaxies that they observed could
originate from 10 K dust. We decide to explore this hypotesis.
Our fiducial model does not seem to be sufficient to explain the fluxes
we obtained at submm wavelengths for the two galaxies NGC 1705
and Haro 11. Two separate thermal dust models may be more
successful to describe the 60-160
m and the 870
m emission separately for these two galaxies.
6.2 Refinement: adding a cold dust component
In an attempt to improve the model results, we refine our fiducial SED
model for the two galaxies Haro 11 and NGC 1705 by
adding a thermal cold dust component with a flux, ,
characterised by a modified blackbody:
![]() |
(3) |
where











Indeed, there is a bend in the SED near 450 m. Due to
the physical parameters of the grains behaving like a modified black
body in the submm, having a natural bend on the Rayleigh-Jeans slope
seems complicated unless you suddenly change the emissivity of the
grains at 450
m.
In Sect. 6.2, we discuss other possible explanations beyond
the cold dust hypothesis.
Since the supplemental black body component is only
constrained by the 870 m flux, we cannot solve for the temperature
and
independently. For this exercise, we fix the temperature to
10 K and fit the SED using a
= 1
or 2 to test the hypothesis of a submm excess of cold dust (Galliano
et al. 2003,2005; Marleau et al. 2006).
The new SED produced is obtained by adding the fiducial SED model and
the cold blackbody. Chi-square values are estimated from the deviations
of the new SED model to the observational constraints. In this revised
model, the warm dust component is described by the observational
constraints covering the FIR wavelengths to 160
m while the
cold component is constrained by the 870
m observations.
![]() |
Figure 5:
SED models of NGC 1705 and Haro 11, adding a cold
dust component of 10 K with an emissivity coefficient |
Open with DEXTER |
The dust masses derived from each SED model for Haro 11 and
NGC 1705 using = 1
and 2, as well as the dust masses derived from the
fiducial models, are given in Table 7.
Including a 10 K dust component, we find dust masses
constrained by
= 2
to be 6 and 8 times greater than those with
= 1
(Table 7)
for Haro 11 and NGC 1705 respectively. Indeed, since
a 10 K blackbody modified with a
-1 emissivity
is flatter on the millimetre tail, the model fits the data with less
mass than when a steeper emissivity coefficient of 2 is used.
For Haro 11, the best-fit model prefers
= 1, giving
a total mass of dust (warm and cold) of 2
107
,
although the success in using
= 1
or 2 is not very different in terms of the reduced
chi-square (
2). For
both galaxies, the
2 values
for the models including a cold component indicate better fits than the
fiducial models. The SED models including a cold dust component are
presented in Fig. 5.
Comparison by eye with the models presented in Fig. 4 show obvious
improvements in the model fits to the observations. The value
of
significantly influences the dust masses derived from the SEDs and thus
the dust-to-gas mass ratio (D/G) estimate of the galaxies
(see Sect. 5.3). We also note that the abundance of
PAHs relative to the total dust mass of these galaxies is much lower
than the Galactic value of 4.6
10-2: a factor of 15 lower for
Haro 11 and a factor of 50 times lower for
NGC 1705 (Table 7).
For Haro 11, increasing the temperature of the cold
dust with = 1
does not significantly influence the
2 value until the
temperature of the cold dust reaches
20 K. For
NGC 1705, when we try to increase the temperature of the cold
dust component, the 160
m observations becomes difficult to fit and
2 values
increase. Thus, at least for NGC 1705, the very cold dust
10 K dust provides a better fit, while for Haro 11,
somewhat higher temperatures could also work. However, we need more
observational constraints to pin down the precise temperature of the
cold dust component.
As mentionned previously, Galliano et al. (2005,2003)
proposed that the submillimeter excess in the dwarf galaxies that they
observed could originate from 10 K dust with a dust emissivity
index = 1
and found that dust would account for 40-80
of the total dust mass in each of these galaxies. We choose to follow
the same assumption but other explanations can be proposed. Lisenfeld et al. (2001)
proposed that the submillimeter excess would originate from hot (
100 K)
dust with a dust emissivity index
= 1 and the
temperature fluctuations of very small grains. Bendo
et al. (2006) studied NGC 4631
at 450 and 850
m with SCUBA and found that the 850-1230
m emission
exceeds what would be expected from thermal emission but the scenario
of a very cold dust component which might explain this excess was
rejected due to the high dust-to-gas mass ratio it would imply. In
fact, submm excess is not always detected in low-metallicity galaxies.
Parkin et al. 2009 (in prep.) investigate the very
well sampled SED of the low-metallicity galaxy of the Local
Group IC 10, using Spitzer and
ISOCAM observations combined with JCMT/SCUBA observations. They model
the SED of the 2 main SF regions only and found no
submm excess. The observations, however, do not cover the entire
galaxy, preventing analysis on the global scale. Draine et al. (2007)
present SED models of a large sample of 65 galaxies. For
17 galaxies for which they have SCUBA data at 850
m, they fit
SED models with and without this submm constraint. Five of their
17 galaxies show an increase in the dust mass when calculated
using SCUBA constraints whereas 5 other galaxies show a
decrease of this dust mass. In fact, their dust masses obtained with
and without SCUBA data agree to within a factor of 1.5
for 11/17 cases and to within a factor of 2.2 for all
cases. They concluded that their dust models do not require cold (
10 K)
dust to account for their submm fluxes. However, they caution that some
of the SCUBA galaxies are not completely mapped or are not
taken in scan map mode. The difficult data processing might have
oversubstracted diffuse, extended emission for these galaxies. Thus
assumptions they make for complet submm flux values may require caution
in using these data. Their sample studied with submm observations
contains only metal-rich galaxies that may show different dust
properties and dust temperature distributions than the low-metallicity
galaxies we present here. Further studies would be necessary to study
the presence of submm excess and the influence of submm constraints on
the SED model with respect to the metallicity of the galaxy.
Instead of a cold dust component fitting the submm excess, we
also test the formalism presented in Draine
et al. (2007) and try to fit the excess with an
extra ISM component heated at
for our two galaxies. This addition, in both cases, leads to a very
cold component with
<
10-2 due to the fact that the extra component
tends to fit the submm excess. The masses of dust derived from the SED
models in this case are 3.3
106
for NGC 1705 and 1.2
108
for Haro 11, thus 19 and 6 times higher,
respectively, than the mass of dust derived from a SED model using a
cold blackbody of 10 K with
= 1,
unrealistic values due to the D/G mass ratios they imply.
Additionally, a =
1.5, which is closer to amorphous carbons (Rouleau & Martin 1991),
might give a better fit and reduce the cold dust mass but it would also
imply that the FIR-mm dust mass was dominated by carbons and not
silicates, which is contrary to our usual relative dust mass concepts.
Other assumptions can be invoked to account for the submm
excess. For example, underestimating the contributions to the
870 m
flux values could have important consequences on the values of the
deduced dust mass. Direct measurements of the CO(3-2) line and
more mm radio observations would place greater confidence in the dust
mass determinations. The submm excess could also be explained as a
change in dust emissivity in lieu of the cold dust hypothesis. Models
of Meny et al. (2007)
modify the dust optical properties to find an effective decrease in the
submm emissivity index as the dust temperature increases as suggested
by the observations of Dupac
et al. (2003). However, Shetty
et al. (2009) express caution in the inverse
temperature -
interpretation,
showing that flux uncertainties, especially in the Rayleigh-Jeans
regime, can affect the results for the SED fits as far as temperature
and emissivity are concerned. Although we do not reject the possibility
of a modification of the properties of dust with temperature, here we
explore the cold dust hypothesis, since it enables us to investigate
its consequences on the global properties of the galaxies.
6.3 Dust-to-gas mass ratios
We calculate the D/G of our galaxies and compare them to estimates from the chemical evolution model of Galliano et al. (2008). Values are presented in Table 5 for Mrk 1089, in Table 7 for Haro 11 and NGC 1705. Since our SED for UM 311 contains 3 individual targets, we do not consider it here in the discussion of the D/G.
NGC 1705 - this galaxy is surrounded by a
very large HI envelope up to 10 times larger than the
optical extension (see Fig. 1), which
is more often the case for dwarf galaxies in comparison with spiral
galaxies. From the HI image of NGC 1705, we estimate
that only 80
of the total HI flux is contained in the aperture we choose to
derive our dust mass. We then consider that only 80
of the HI mass, i.e. 4.1
107
,
should be used for the D/G estimate. The D/G of
NGC 1705 estimated with submm observations is
4.1
10-3 with our required very cold dust component
using a
emissivity
factor of 1 (Table 7). This
value compares to that expected by the chemical evolution model used in
Galliano
et al. (2008) (2
10-3 < D/G <
5
10-3). The solution for
= 2,
obtained with a slightly higher
2,
leads to a D/G of 2.8
10-2, which is a factor of 8 higher
than that of
= 1.
This high D/G value would be difficult to reconcile with
chemical models. We prefer the model with a cold component using
= 1
for NGC 1705.
Haro 11 - the D/G estimated with our SED
model is 0.2
when a very cold dust component of
= 1 is used
(Table 7).
If we were to use an emissivity index of 2 for the very cold
grains, the D/G derived is even higher and not physical
considering the lack of metals in the galaxy. For this reason, in spite
of the similar
2 values
for the two different fits, we prefer the fit for
= 1
for the cold dust component. The HI mass used for our
calculation is an upper limit of 108
given in Bergvall et al.
(2000). Bergvall
& Östlin (2002) already note from their VLA
observations that Haro 11 is dramatically deficient in neutral
hydrogen. For such a low metallicity (
= 7.9),
a D/G of
10-3
should be more likely considering chemical evolution models. Our high
values for the D/G, constrained by the new submm data, are not easily
explained with current models. For the same galaxy, Galliano et al.
(2008) estimated the D/G
1.6
10-2 (without submm constraints) but this ratio
was qualified as uncertain due to the poor HI measurement for
this galaxy which could be linked to the difficulty of accurately
measuring HI at such distances. Indeed, in Gordon & Gottesman
(1981), the mean HI mass for BCGs of the size of
Haro 11 should be
8.1
108
.
If we consider that the existing HI observations provide a
reliable upper limit on the mass of atomic hydrogen (Bergvall et al. 2000),
the large estimated dust mass may suggest that a significant fraction
of the total gas mass is in forms other than atomic. A major
fraction of its gas should be in molecular or ionised form.
An upper limit of only
109
was estimated from CO observations for the mass of molecular gas in
this galaxy (Bergvall
et al. 2000). The total amount of observed molecular
+ atomic gas (all upper limits) still can not lead to a D/G
of 10-3 for Haro 11. In fact,
CO can be a poor tracer of molecular gas in low metallicity galaxies
due to the high excitation and the density of these environments and
the small filling factor of the molecular clouds. Self-shielding can be
extremely efficient for H2 in regions where CO
is photodissociated. Thus, there could be a non negligeable amount of
molecular gas not traced by CO (e.g. Madden et al. 1997; Poglitsch
et al. 1995). In order to reach the
D/G value expected by chemical models, a large molecular gas
mass on the order of 1010
would be required to account for the ``missing'' gas mass, that is to
say an order of magnitude more molecular gas than that deduced from
current CO upper limits. Molecular hydrogen could be embedded
in [CII] emiting envelopes as described in Madden et al. (1997)
for the low-metallicity galaxy IC 10. The high
/
value (
4
105)
deduced by Bergvall
et al. (2000) and also seen in other low metallicity
galaxies (Madden 2000) is
coherent with this theory.
Mrk 1089 - Our SED model estimate of the
D/G leads to a value of 1.9
10-3. For a galaxy with the metallicity of
Mrk 1089 (
),
the chemical evolution model used in Galliano et al.
(2008) which links the D/G with metallicity, leads to an
estimated D/G of
10-3,
consistent with the value we obtain to within a factor of 2.
To summarize, the SED results we will discuss in the following
sections are those obtained with our fiducial model for
Mrk 1089 (i.e., no additional modified black body)
and the SED models which include a cold dust component of 10 K
with = 1
for NGC 1705 and Haro 11.
6.4 Robustness of the results with the assumed radiation field
The modelling scheme already presented in this paper, does not
constrain the form of the global ISRF of the galaxies and the results
should be dependent on the shape of the average radiation field to
which the dust grains are exposed. The SED results presented here are
obtained using the Galactic shape of the ISRF (Mathis
et al. 1983), but this may not be accurate in our
case for metal-poor galaxies. Modeled ISRFs of dwarf galaxies show that
dwarf galaxies can certainly have harder global average ISRFs than that
of the Galaxy (Madden
et al. 2006) - an effect attributed to the
lower dust attenuation in the low metallicity ISM and, as a
consequence, the larger mean free path length of the ionising photons.
As we are modelling galaxies on the global scale here, we test several
ISRFs which have been determined for low metallicity galaxies to
quantify this dependence. We use synthesised radiation fields of four
dwarf galaxies as a reference: He2-10, IIZw40, NGC 1140 and
NGC 1569. The process to synthesized the ISRFs uses the
stellar evolution synthesis code PEGASE (Fioc
& Rocca-Volmerange 1997) and the photoionisation
model CLOUDY (Ferland 1996).
We refer to Galliano
et al. (2005,2003) for more explanations
of this process and a description of the synthesized ISRFs of He2-10,
IIZw40, NGC 1140 and NGC 1569. We furthermore produce
a grid of dust models for the ISRF of a young and non-ionising cluster,
created just after an instantaneous burst, with a
Salpeter IMF. Even if the shapes of the resulting SEDs for our
galaxies are somewhat modified using different forms of harder
radiation fields, we find that the masses of dust derived from these
different models and those determined using the Galactic ISRF, differ
by less than 10,
which is within the error bars of the dust masses we estimate
(Table 8).
Indeed, the shape of the radiation field essentially controls the
emission of out-of-equilibrium grains. Increasing the hardness of the
radiation field increases the maximum temperature that small grains
reach when they fluctutate. Consequently, it produces a short
wavelength excess of the grain spectrum as reflected in the resulting
modified SEDs. However, this excess is compensated in the global model
of Sect. 5, by lowering the weight of the high intensity
regions. Since these hot regions do not contribute significantly to the
total dust mass, the latter does not strongly depend on the shape of
the ISRF.
Table 8: Dust masses derived from SED models using different shapes of ISRFs.
6.5 Distribution of the dust temperatures
To get an idea of how the dust mass is distributed as a function of the temperature, we calculate the fraction of the dust mass in several ranges of temperatures: above 50 K (hot), between 25 and 50 K, between 15 and 25 K and a cold 10 K component for the two galaxies NGC 1705 and Haro 11. We estimate the fraction of dust between two temperatures as the mass of dust exposed to a radiation field such that the large silicates, which are at thermal equilibrium, have temperatures between these two temperatures.
The energy absorbed by a dust grain is given by:
![]() |
(4) |
where

The energy emitted by a dust grain is given by:
![]() |
(5) |
where


As
=
,
we can equalize these two expressions. We thus obtain a relation of
proportionnality between the radiation intensity U
and the equilibrium temperature
.
Grains are assumed to possess an emissivity
= 2:
![]() |
(6) |
Note that in this equation, the equilibrium temperature is normalised to the equilibrium dust temperature of the Galaxy of 17.5 K (Boulanger et al. 1996).
Finally, from the prescription of Dale
et al. (2001) (Eq. (1)), we can derive the
heated dust mass associated to each radiation intensity U
and thus to each equilibrium temperature. The fraction of the total
mass exposed to radiation between temperatures T1 and T2 is given by:
![]() |
(7) |
where


For Haro 11 and NGC 1705, the fraction of
dust at 10 K is given by the ratio between the dust mass of
the cold dust component and the total dust mass of the galaxy. The
results are summarized in Table 9. The cool phase (25 K)
constitues the major part of the dust in our galaxies, at
least 70% for Haro 11 and up to 90% for
Mrk 1089 and NGC 1705. The SED of Haro 11
peaks at usually short wavelengths (36
m), with a significant fraction (
30
)
of the dust mass at a temperature >25 K while this same
dust mass fraction does not exceed 10
for NGC 1705 and Mrk 1089. Thus their global SEDs
reflect the different levels of SF activity (and/or
morphologies) and the consequences on the dust heating.
Table 9: Minimum and maximum equilibrium temperature and distribution of the dust mass with dust temperature ranges.
Table 10: Luminosities, size and SFR of our galaxies.
![]() |
Figure 6:
a) Ratio between the total infrared luminosty
(
|
Open with DEXTER |
6.6 Total infrared luminosity
We calculate the total IR luminosity (
)
for our galaxies by integrating our modeled SEDs from 3
m to
1100
m
and compare our
values
with prescriptions in the literature using IR broadbands. For
example, Dale & Helou
(2002) have made phenomenological SED models to derive
based on IRAS ISO and
some 850
m
data and provide a recipe to estimate the 3
m to
1100
m
luminosity using the Spitzer MIPS bands:
![]() |
(8) |
In the same fashion, Draine & Li (2007) expand this


![]() |
(9) |
We estimate the











The values given by the Dale
& Helou (2002) formula for the
seem to be lower for our galaxies than the
derived directly from our SED models while the Draine & Li (2007)
formula leads to closer results. To know if our overestimation of
compared to the Dale &
Helou (2002) formula is a systematic effect observed in other
galaxies, we derive the
of the galaxies of Galliano
et al. (2008) by integrating their SEDs from
3
m
to 1100
m
and compare the results to the
obtained by both Dale
& Helou (2002) and Draine
& Li (2007) relations. Engelbracht
et al. (2008) also calculate the
of their galaxies from their SED modelling. We calculated the
derived from the Dale
& Helou (2002) and the Draine
& Li (2007) relations for their galaxies (from the
fluxes available in the paper) and add these galaxies to the sample.
The ratio between these different estimates are plotted in
Fig. 6
as a function of metallicity. We clearly observe a systematic
underestimation of the
when using the Dale &
Helou (2002) relation, with a shift of about 20
and a scatter of
20
.
The Draine & Li (2007)
formula seems to better estimate the
of the galaxies to within
20
.
For the lowest metallicity galaxies used in this comparison (
< 7.5),
we note a potentially systematic underestimation but larger samples
would be required to investigate this point.
Table 10
also presents the distribution of the IR luminosity according
to wavelength windows: from 3 to 50 m,
from 50 to 100
m and from 100 to 1100
m. For
Mrk 1089 and NGC 1705, the luminosity is roughly
evenly distributed over the wavelength windows while for
Haro 11, 70
of the
comes out at wavelengths shorter than 50
m. While the longer wavelengths account for the
major fraction of the dust mass, not more than 6
of the
comes out from wavelength superior to 100
m.
![]() |
Figure 7:
Positions of Haro 11, NGC 1705 and Mrk 1089
in the Schmidt-Kennicutt diagram. The triangles represent normal
spirals and squares represent starburst galaxies (see Kennicutt 1998, for details
on the galaxies represented by triangles). Red stars indicate our
sources. The position of Haro 11 in this diagram accounts for
the HI+H2 upper limit of total gas mass ( |
Open with DEXTER |
6.7 Star formation rates
To investigate how these galaxies behave with respect to the Schmidt
law, which describes the tight relationship between global SFR and gas
density, originally formulated for normal spirals, we derive the star
formation rates (SFRs) for our galaxies using the relation of Kennicutt (1998):
![]() |
(10) |
where


We compare these values with the SFRs obtained by Zhu et al. (2008) for
star forming galaxies, formula which is only valid when
<
1011
and thus can not be used for the LIRG Haro 11:
![]() |
(11) |
We finally use the relations of Calzetti (2007) to derive SFR estimates from the 24



![]() |
(12) |
![]() |
(13) |
The SFR estimates are presented on Table 10. The values given by the Kennicutt (1998) relation are higher than the one obtained with the Calzetti (2007) formula but compare to the ones of Zhu et al. (2008).
We investigate the behaviour of our galaxies with respect to
the Schmidt law (Kennicutt
1998). We plot the SFR estimated with the relation of Kennicutt (1998) as a
function of the gas density for our three galaxies. We overplot a large
sample of spirals and starburst galaxies presented in (Kennicutt 1998);
(Fig. 7).
The two galaxies Mrk 1089 and NGC 1705 seem to follow
the Schmidt law. For Haro 11, we take the large upper
limit of the HI + H2 mass (109
- Bergvall et al. 2000)
into account in the gas mass estimate. This galaxy does not fall close
to the Schmidt law. Its location in Fig. 7 might
be due to the fact that it is a dwarf galaxy, which can explain why the
gas seems to be consumed at a much higher rate than in normal spiral
galaxies. Undergoing a merger, Haro 11 should also have a high
star-formation rate with a lower gas consumption time than less
luminous galaxies (see Tacconi et al. 2006; Kennicutt
et al. 1994, for studies on normal nearby and
submillimiter galaxies respectively). Nevertherless, Kennicutt (1998) suggests
that the SFR in LIRGs do follow the Schmidt Law dependance on
gas surface density, which means that the relation linking the SFR and
of starburst systems should not differ significantly from normal disk
galaxies. In conclusion, the location of Haro 11 as an outlier
confirms that some gas is missing and that the current HI and CO
observations do not lead to an amount of gas coherent with what is
usually expected. The fact that Haro 11 falls far from the
relation favors the cold dust explanation over the change in the
emissivity of the grains for this galaxy. To follow the
Schmidt law, Haro 11 would require 1010
of gas, which would imply an order of magnitude more than that
suggested by CO and HI measurements and which is coherent with
the ``missing'' gas mass required to obtain a D/G expected by
the chemical evolution models (see Sect. 6.3).
7 Conclusion and summary
The quantification of the dust mass of a galaxy aids our understanding of its evolution and star formation history. Larger dust masses are sometimes found in low metallicity galaxies when using submm constraints in the SED modelling. In this context, submm observations are clearly necessary to lead a more complete description of the distribution and properties of dust.
We focused our paper on the dust modelling of four low metallicity galaxies observed with APEX/LABOCA.
In this paper:
- 1.
- We present the first images of four dwarf galaxies carried
out with the APEX/LABOCA
instrument observing at 870
m.
- 2.
- We construct the SEDs with Spitzer IRAC and MIPS bands as well as the IRS spectra for Haro 11. We apply our SED model and determine the dust properties of these galaxies.
- 3.
- We find that the mass of PAHs accounts for 0.08 to 0.8
of the total dust mass of the galaxies, which is a factor of 5 to 50 lower than that of the Galaxy.
- 4.
- To investigate the influence of the submm constraints on
the interpretation, we test the effect on the SED model results when
submm 870
m observations are taken into account and compare with SED models not taking into account the 870
m flux, but with observational constraints at wavelengths only as long as 160
m. We find that the use of submm observational constraints always leads to an increase of the total dust mass derived for our low metallicity galaxies.
- 5.
- We choose to include an additional component to account for
the excess submm emission of NGC 1705 and Haro 11.
A cold dust component (
10 K) with a
emissivity index of 1 substantially improves the fit. We find at least 70
of the total dust mass residing in a cold (
10 K) dust component for these two galaxies. We note that describing a cold component of
= 2 does not give very different
2 values, but would give unrealistically larger D/G. Our results however do not rule out the hypothesis of a change in dust emissivity as a function of wavelength proposed in recent studies (e.g. Dupac et al. 2003; Meny et al. 2007).
- 6.
- While Haro 11 has a substantial (
70
) cold dust component, it also harbours a significant fraction of dust mass (30
) in a warmer dust component (>25 K). The SED peaks at unusually short wavelengts (36
m), highlighting the importance of the warm dust.
- 7.
- We determine the D/G for Mrk 1089,
NGC 1705 and Haro 11 to be 1.9
10-3, 4.1
10-3 and 0.2, respectively. For Mrk 1089 and NGC 1705, these D/G are consistent with current chemical evolution models. On the contrary, Haro 11 has an excessively high D/G considering the upper limits detected in HI and CO. Haro 11 also falls far from the Schmidt law, perhaps due to the observed deficit of gas in this galaxy. This could suggest the presence of a large amount of molecular gas. 10 times more molecular gas, compared to that deduced from CO measurements, may be present but not necessarily traced by CO observations.
- 8.
- From our SED models, we determine the total infrared
luminosity of our galaxy sample to range from 5.8
107 for NGC 1705 to 1.7
1011 for the LIRG Haro 11. These values of
are systematically higher than those obtained using the Dale & Helou (2002) formula but compare better to the Draine & Li (2007) formula. While
90
of the dust mass is residing in the FIR to submm regime, not more than 6
of the total IR luminosity in Haro 11 emerges from the FIR to submm (100 to 1100
m), while most of the luminosity (70
) emerges in the NIR to MIR (3
m to 50
m) window. This is in contrast to Mrk 1089 and NGC 1705 which distribute their luminosities more equally in these two wavelength windows.


We first thank the referee for his/her detail suggestions and comments that help to improve the understanding of the paper. We thank Xander Tielens, Ant Jones and Eli Dwek for very stimulating discussion which improved the content of this paper. We would also like to thank Gerhardt R. Meurer for his high quality HI map of NGC 1705. This publication is based on data acquired with the Atacama Pathfinder Experiment (APEX). APEX is a collaboration between the Max-Planck-Institut fur Radioastronomie, the European Southern Observatory, and the Onsala Space Observatory.
References
- Aloisi, A., Origlia, L., Tosi, M., et al. 1998, in European Southern Observatory Astrophysics Symposia, ed. W. Freudling, & R. N. Hook, 55, 154
- Arendt, R. G., Odegard, N., Weiland, J. L., et al. 1998, ApJ, 508, 74 [NASA ADS] [CrossRef]
- Bendo, G. J., Dale, D. A., Draine, B. T., et al. 2006, ApJ, 652, 283 [NASA ADS] [CrossRef]
- Bendo, G. J., Draine, B. T., Engelbracht, C. W., et al. 2008, MNRAS, 389, 629 [NASA ADS] [CrossRef]
- Bergvall, N., & Östlin, G. 2002, A&A, 390, 891 [NASA ADS] [EDP Sciences] [CrossRef]
- Bergvall, N., Masegosa, J., Östlin, G., & Cernicharo, J. 2000, A&A, 359, 41 [NASA ADS]
- Bernard, J. P., Boulanger, F., Désert, F. X., et al. 1996, in AIP Conf. Ser. 348, ed. E. Dwek, 105
- Bernard, J.-P., Reach, W. T., Paradis, D., et al. 2008, AJ, 136, 919 [NASA ADS] [CrossRef]
- Böttner, C., Klein, U., & Heithausen, A. 2003, A&A, 408, 493 [NASA ADS] [EDP Sciences] [CrossRef]
- Boulanger, F., Abergel, A., Bernard, J.-P., et al. 1996, A&A, 312, 256 [NASA ADS]
- Calzetti, D. 2007, Nuovo Cimento B Serie, 122, 971 [NASA ADS]
- Cannon, J. M., Smith, J.-D. T., Walter, F., et al. 2006, ApJ, 647, 293 [NASA ADS] [CrossRef]
- Chen, H.-W., Prochaska, J. X., & Bloom, J. S. 2007, ApJ, 668, 384 [NASA ADS] [CrossRef]
- Chen, H.-W., Perley, D. A., Pollack, L. K., et al. 2009, ApJ, 691, 152 [NASA ADS] [CrossRef]
- Condon, J. J., Cotton, W. D., Greisen, E. W., et al. 1998, AJ, 115, 1693 [NASA ADS] [CrossRef]
- Conti, P. S. 1991, ApJ, 377, 115 [NASA ADS] [CrossRef]
- Conti, P. S., Leitherer, C., & Vacca, W. D. 1996, ApJ, 461, L87 [NASA ADS] [CrossRef]
- Dale, D. A., & Helou, G. 2002, ApJ, 576, 159 [NASA ADS] [CrossRef]
- Dale, D. A., Helou, G., Contursi, A., Silbermann, N. A., & Kolhatkar, S. 2001, ApJ, 549, 215 [NASA ADS] [CrossRef]
- Dale, D. A., Bendo, G. J., Engelbracht, C. W., et al. 2005, ApJ, 633, 857 [NASA ADS] [CrossRef]
- Dale, D. A., Gil de Paz, A., Gordon, K. D., et al. 2007, ApJ, 655, 863 [NASA ADS] [CrossRef]
- Draine, B. T., & Li, A. 2007, ApJ, 657, 810 [NASA ADS] [CrossRef]
- Draine, B. T., Dale, D. A., Bendo, G., et al. 2007, ApJ, 663, 866 [NASA ADS] [CrossRef]
- Dultzin-Hacyan, D., Masegosa, J., & Moles, M. 1990, A&A, 238, 28 [NASA ADS]
- Dumke, M., Krause, M., & Wielebinski, R. 2004, A&A, 414, 475 [NASA ADS] [EDP Sciences] [CrossRef]
- Dupac, X., Bernard, J.-P., Boudet, N., et al. 2003, A&A, 404, L11 [NASA ADS] [EDP Sciences] [CrossRef]
- Engelbracht, C. W., Gordon, K. D., Rieke, G. H., et al. 2005, ApJ, 628, L29 [NASA ADS] [CrossRef]
- Engelbracht, C. W., Blaylock, M., Su, K. Y. L., et al. 2007, PASP, 119, 994 [NASA ADS] [CrossRef]
- Engelbracht, C. W., Rieke, G. H., Gordon, K. D., et al. 2008, ApJ, 678, 804 [NASA ADS] [CrossRef]
- Ferland, G. J. 1996, Hazy, A Brief Introduction to Cloudy 90, ed. G. J. Ferland
- Fioc, M., & Rocca-Volmerange, B. 1997, A&A, 326, 950 [NASA ADS]
- Galliano, F., Madden, S. C., Jones, A. P., et al. 2003, A&A, 407, 159 [NASA ADS] [EDP Sciences] [CrossRef]
- Galliano, F., Madden, S. C., Jones, A. P., Wilson, C. D., & Bernard, J.-P. 2005, A&A, 434, 867 [NASA ADS] [EDP Sciences] [CrossRef]
- Galliano, F., Dwek, E., & Chanial, P. 2008, ApJ, 672, 214 [NASA ADS] [CrossRef]
- Gil de Paz, A., Madore, B. F., & Pevunova, O. 2003, ApJS, 147, 29 [NASA ADS] [CrossRef]
- Gordon, M. A. 1995, A&A, 301, 853 [NASA ADS]
- Gordon, D., & Gottesman, S. T. 1981, AJ, 86, 161 [NASA ADS] [CrossRef]
- Gordon, K. D., Rieke, G. H., Engelbracht, C. W., et al. 2005, PASP, 117, 503 [NASA ADS] [CrossRef]
- Gordon, K. D., Engelbracht, C. W., Fadda, D., et al. 2007, PASP, 119, 1019 [NASA ADS] [CrossRef]
- Gordon, K. D., Engelbracht, C. W., Rieke, G. H., et al. 2008, ApJ, 682, 336 [NASA ADS] [CrossRef]
- Greve, A., Becker, R., Johansson, L. E. B., & McKeith, C. D. 1996, A&A, 312, 391 [NASA ADS]
- Grimes, J. P., Heckman, T., Strickland, D., et al. 2007, ApJ, 668, 891 [NASA ADS] [CrossRef]
- Guhathakurta, P., & Draine, B. T. 1989, ApJ, 345, 230 [NASA ADS] [CrossRef]
- Guseva, N. G., Izotov, Y. I., & Thuan, T. X. 1998, Kinematics and Physics of Celestial Bodies, 14, 41 [NASA ADS]
- Heckman, T. M., & Leitherer, C. 1997, AJ, 114, 69 [NASA ADS] [CrossRef]
- Heisler, C. A., & Vader, J. P. 1995, AJ, 110, 87 [NASA ADS] [CrossRef]
- Helou, G., NGC300 ERO Team 2004, in BAAS, 36, 701
- Hickson, P. 1982, ApJ, 255, 382 [NASA ADS] [CrossRef]
- Hirashita, H., Kaneda, H., Onaka, T., & Suzuki, T. 2008, PASJ, 60, 477
- Hoefner, S. 2009, Cosmic Dust - Near and far, ed. Th. Henning, E. Grün, & J. Steinacker, ASP Conf Ser., in press [arXiv:0903.5280]
- Hopkins, A. M., Schulte-Ladbeck, R. E., & Drozdovsky, I. O. 2002, AJ, 124, 862 [NASA ADS] [CrossRef]
- Houck, J. R., Charmandaris, V., Brandl, B. R., et al. 2004, ApJS, 154, 211 [NASA ADS] [CrossRef]
- Iglesias-Paramo, J., & Vilchez, J. M. 1997, ApJ, 479, 190 [NASA ADS] [CrossRef]
- James, A., Dunne, L., Eales, S., & Edmunds, M. G. 2002, MNRAS, 335, 753 [NASA ADS] [CrossRef]
- Johnson, K. E., & Conti, P. S. 2000, AJ, 119, 2146 [NASA ADS] [CrossRef]
- Johnson, K. E., Hibbard, J. E., Gallagher, S. C., et al. 2007, AJ, 134, 1522 [NASA ADS] [CrossRef]
- Kennicutt, Jr., R. C. 1998, ARA&A, 36, 189 [NASA ADS] [CrossRef]
- Kennicutt, Jr., R. C., Tamblyn, P., & Congdon, C. E. 1994, ApJ, 435, 22 [NASA ADS] [CrossRef]
- Kennicutt, Jr., R. C., Armus, L., Bendo, G., et al. 2003, PASP, 115, 928 [NASA ADS] [CrossRef]
- Kunth, D., & Schild, H. 1986, A&A, 169, 71 [NASA ADS]
- Laor, A., & Draine, B. T. 1993, ApJ, 402, 441 [NASA ADS] [CrossRef]
- Lara-López, M. A., Cepa, J., Bongiovanni, A., et al. 2009, A&A, 493, L5 [NASA ADS] [EDP Sciences] [CrossRef]
- Leroy, A., Bolatto, A. D., Simon, J. D., & Blitz, L. 2005, ApJ, 625, 763 [NASA ADS] [CrossRef]
- Li, A., & Draine, B. T. 2001, ApJ, 554, 778 [NASA ADS] [CrossRef]
- Lisenfeld, U., & Ferrara, A. 1998, ApJ, 496, 145 [NASA ADS] [CrossRef]
- Lisenfeld, U., Sievers, A., Israel, F., & Stil, J. 2001, Astrophys. Space Sci. Suppl., 277, 105 [NASA ADS] [CrossRef]
- Madden, S. C. 2000, New Astron. Rev., 44, 249 [NASA ADS] [CrossRef]
- Madden, S. C. 2005, in The Spectral Energy Distributions of Gas-Rich Galaxies: Confronting Models with Data, ed. C. C. Popescu, & R. J. Tuffs, AIP Conf. Ser., 761, 223
- Madden, S. C., Poglitsch, A., Geis, N., Stacey, G. J., & Townes, C. H. 1997, ApJ, 483, 200 [NASA ADS] [CrossRef]
- Madden, S. C., Galliano, F., Jones, A. P., & Sauvage, M. 2006, A&A, 446, 877 [NASA ADS] [EDP Sciences] [CrossRef]
- Marleau, F. R., Noriega-Crespo, A., Misselt, K. A., et al. 2006, ApJ, 646, 929 [NASA ADS] [CrossRef]
- Mathis, J. S., Mezger, P. G., & Panagia, N. 1983, A&A, 128, 212 [NASA ADS]
- Mauch, T., Murphy, T., Buttery, H. J., et al. 2003, MNRAS, 342, 1117 [NASA ADS] [CrossRef]
- Meier, D. S., Turner, J. L., Crosthwaite, L. P., & Beck, S. C. 2001, AJ, 121, 740 [NASA ADS] [CrossRef]
- Meny, C., Gromov, V., Boudet, N., et al. 2007, A&A, 468, 171 [NASA ADS] [EDP Sciences] [CrossRef]
- Meurer, G. R., Freeman, K. C., Dopita, M. A., & Cacciari, C. 1992, AJ, 103, 60 [NASA ADS] [CrossRef]
- Meurer, G. R., Staveley-Smith, L., & Killeen, N. E. B. 1998, MNRAS, 300, 705 [NASA ADS] [CrossRef]
- Moles, M., Marquez, I., Masegosa, J., et al. 1994, ApJ, 432, 135 [NASA ADS] [CrossRef]
- Moshir, M., et al. 1990, in IRAS Faint Source Catalogue, version 2.0, 0
- Muñoz-Mateos, J. C., Gil de Paz, A., Zamorano, J., et al. 2009, ApJ, 703, 1569 [NASA ADS] [CrossRef]
- O'Halloran, B., Satyapal, S., & Dudik, R. P. 2006, ApJ, 641, 795 [NASA ADS] [CrossRef]
- O'Halloran, B., Madden, S. C., & Abel, N. P. 2008, ApJ, 681, 1205 [NASA ADS] [CrossRef]
- Östlin, G., Amram, P., Masegosa, J., Bergvall, N., & Boulesteix, J. 1999, A&AS, 137, 419 [NASA ADS] [EDP Sciences] [CrossRef]
- Poglitsch, A., Krabbe, A., Madden, S. C., et al. 1995, ApJ, 454, 293 [NASA ADS] [CrossRef]
- Popescu, C. C., & Tuffs, R. J. 2005, The Spectral Energy Distributions of Gas-Rich Galaxies: Confronting Models with Data, AIP Conf. Ser., 761
- Reach, W. T., Dwek, E., Fixsen, D. J., et al. 1995, ApJ, 451, 188 [NASA ADS] [CrossRef]
- Reach, W. T., Megeath, S. T., Cohen, M., et al. 2005, PASP, 117, 978 [NASA ADS] [CrossRef]
- Relaño, M., Lisenfeld, U., Pérez-González, P. G., Vílchez, J. M., & Battaner, E. 2007, ApJ, 667, L141 [NASA ADS] [CrossRef]
- Richer, M. G., Georgiev, L., Rosado, M., et al. 2003, A&A, 397, 99 [EDP Sciences] [CrossRef]
- Rouleau, F., & Martin, P. G. 1991, ApJ, 377, 526 [NASA ADS] [CrossRef]
- Rubin, V. C., & Ford, Jr., W. K. 1983, ApJ, 271, 556 [NASA ADS] [CrossRef]
- Rubin, V. C., Hunter, D. A., & Ford, W. K. J. 1990, ApJ, 365, 86 [NASA ADS] [CrossRef]
- Rubin, D., Hony, S., Madden, S. C., et al. 2009, A&A, 494, 647 [NASA ADS] [EDP Sciences] [CrossRef]
- Sanders, D. B., Mazzarella, J. M., Kim, D.-C., Surace, J. A., & Soifer, B. T. 2003, AJ, 126, 1607 [NASA ADS] [CrossRef]
- Shetty, R., Kauffmann, J., Schnee, S., Goodman, A. A., & Ercolano, B. 2009, ApJ, 696, 2234 [NASA ADS] [CrossRef]
- Smoker, J. V., Davies, R. D., Axon, D. J., & Hummel, E. 2000, A&A, 361, 19 [NASA ADS]
- Stansberry, J. A., Gordon, K. D., Bhattacharya, B., et al. 2007, PASP, 119, 1038 [NASA ADS] [CrossRef]
- Tacconi, L. J., Neri, R., Chapman, S. C., et al. 2006, ApJ, 640, 228 [NASA ADS] [CrossRef]
- Terlevich, R., Melnick, J., Masegosa, J., Moles, M., & Copetti, M. V. F. 1991, A&AS, 91, 285 [NASA ADS]
- Tosi, M. 2003, Ap&SS, 284, 651 [NASA ADS] [CrossRef]
- Walter, F., Cannon, J. M., Roussel, H., et al. 2007, ApJ, 661, 102 [NASA ADS] [CrossRef]
- Weingartner, J. C., & Draine, B. T. 2001, ApJ, 548, 296 [NASA ADS] [CrossRef]
- Williams, B. A., McMahon, P. M., & van Gorkom, J. H. 1991, AJ, 101, 1957 [NASA ADS] [CrossRef]
- Wu, H., Zhu, Y.-N., Cao, C., & Qin, B. 2007, ApJ, 668, 87 [NASA ADS] [CrossRef]
- Yun, M. S., Verdes-Montenegro, L., del Olmo, A., & Perea, J. 1997, ApJ, 475, L21 [NASA ADS] [CrossRef]
- Zhu, Y.-N., Wu, H., Cao, C., & Li, H.-N. 2008, ApJ, 686, 155 [NASA ADS] [CrossRef]
- Zubko, V., Dwek, E., & Arendt, R. G. 2004, ApJS, 152, 211 [NASA ADS] [CrossRef]
Footnotes
- ... page
- Details on the data reduction of the SINGS Fifth Enhanced Data Release can be found at http://data.spitzer.caltech.edu/popular/sings/
All Tables
Table 1: General properties of the sample.
Table 2: AOR keys of the Spitzer/IRAC and Spitzer/MIPS observations.
Table 3: Integrated flux densities measured with 2MASS, IRAS, Spitzer and LABOCA.
Table 4: Size range and mass densities of the three dust grain components from Zubko et al. (2004).
Table 5: Parameters of our SED models using or not submm constraints and Dust-to-Gas mass ratios of our galaxies.
Table 6:
Parameters of our SED models for the UM311 system using
different values for the 160 m constraint.
Table 7: Parameters of the SED models introducing a cold dust component at 10 K.
Table 8: Dust masses derived from SED models using different shapes of ISRFs.
Table 9: Minimum and maximum equilibrium temperature and distribution of the dust mass with dust temperature ranges.
Table 10: Luminosities, size and SFR of our galaxies.
All Figures
![]() |
Figure 1:
a) H |
Open with DEXTER | |
In the text |
![]() |
Figure 2:
3.6 |
Open with DEXTER | |
In the text |
![]() |
Figure 2: continued. |
Open with DEXTER | |
In the text |
![]() |
Figure 3:
a) The positions of the short-high (green)
and low-high (red) slits of the IRS observations superimposed on the
Spitzer/3.6 |
Open with DEXTER | |
In the text |
![]() |
Figure 4:
SED models of Mrk 1089, the UM 311 system,
NGC 1705 and Haro 11 using the fiducial model. The
SEDs are plotted in black. Observational constraints (listed in
Table 3)
are superimposed (filled circles). The green and red lines respectively
distinguish the stellar and the dust contributions. The dashed black
lines present the SED models of our galaxies obtained when the
LABOCA constraint is not used in the modelling. The open circles
represent the expected modeled fluxes integrated over the instrumental
bands. When the error bars are not shown, the errors are smaller than
symbols. Note that the IRS MIR spectrum used in the modelling
is overlaid in orange for Haro 11. For the UM 311
system of 3 compact sources, the 160 |
Open with DEXTER | |
In the text |
![]() |
Figure 5:
SED models of NGC 1705 and Haro 11, adding a cold
dust component of 10 K with an emissivity coefficient |
Open with DEXTER | |
In the text |
![]() |
Figure 6:
a) Ratio between the total infrared luminosty
(
|
Open with DEXTER | |
In the text |
![]() |
Figure 7:
Positions of Haro 11, NGC 1705 and Mrk 1089
in the Schmidt-Kennicutt diagram. The triangles represent normal
spirals and squares represent starburst galaxies (see Kennicutt 1998, for details
on the galaxies represented by triangles). Red stars indicate our
sources. The position of Haro 11 in this diagram accounts for
the HI+H2 upper limit of total gas mass ( |
Open with DEXTER | |
In the text |
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