Issue |
A&A
Volume 518, July-August 2010
Herschel: the first science highlights
|
|
---|---|---|
Article Number | L87 | |
Number of page(s) | 4 | |
Section | Letters | |
DOI | https://doi.org/10.1051/0004-6361/201014537 | |
Published online | 16 July 2010 |
Herschel: the first science highlights
LETTER TO THE EDITOR
Dust-temperature of an isolated star-forming cloud:
Herschel observations of the Bok globule
CB244![[*]](/icons/foot_motif.png)
A. Stutz1,2 - R. Launhardt1 - H. Linz1 - O. Krause1 - T. Henning1 - J. Kainulainen1 - M. Nielbock1 - J. Steinacker3,1 - P. André4
1 - Max-Planck-Institut für Astronomie,
Königstuhl 17, 69117 Heidelberg, Germany
2 -
Department of Astronomy and Steward Observatory,
University of Arizona, 933 North Cherry Avenue,
Tucson, AZ 85721, USA
3 -
LERMA & UMR 8112 du CNRS, Observatoire de Paris,
61 Av. de l'Observatoire, 75014 Paris, France
4 -
Laboratoire AIM, CEA/DSM-CNRS-Université Paris Diderot,
IRFU/Service d'Astrophysique, C.E. Saclay, Orme des
Merisiers, 91191 Gif-sur-Yvette, France
Received 29 March 2010 / Accepted 15 April 2010
Abstract
We present Herschel observations of the isolated,
low-mass star-forming Bok globule CB244. It contains two cold
sources, a low-mass Class 0 protostar and a starless core, which is
likely to be prestellar in nature, separated by 90
(
18 000 AU). The Herschel data sample the peak of the
Planck spectrum for these sources, and are therefore ideal for
dust-temperature and column density modeling. With these data and
a near-IR extinction map, the MIPS 70
m mosaic, the SCUBA
850
m map, and the IRAM 1.3 mm map, we model the
dust-temperature and column density of CB 244 and present the first
measured dust-temperature map of an entire star-forming molecular
cloud. We find that the column-averaged dust-temperature near the
protostar is
17.7 K, while for the starless core it is
10.6 K, and that the effect of external heating causes the
cloud dust-temperature to rise to
17 K where the hydrogen
column density drops below 1021 cm-2. The total hydrogen
mass of CB 244 (assuming a distance of 200 pc) is
.
The mass of the protostellar core is
and the mass
of the starless core is
,
indicating that
45% of
the mass in the globule is participating in the star-formation
process.
Key words: ISM: individual objects: CB244 - infrared: ISM - dust, extinction - ISM: clouds - submillimeter: ISM - stars: formation
1 Introduction
Bok globules are nearby, small, relatively isolated molecular clouds undergoing low-mass star-formation (e.g., Clemens & Barvainis 1988; Launhardt & Henning 1997). They tend to have only one or two star-forming cores that are embedded in a larger common cloud. These relatively simple characteristics make these objects ideal for studying the detailed processes taking place in low-mass star formation. Specifically, the temperature and density structure are fundamental physical parameters necessary to understand core fragmentation, collapse, and chemical evolution (e.g., Stutz et al. 2008; Launhardt et al. 2010; Ward-Thompson et al. 2007; Stutz et al. 2009). The Herschel (Pilbratt et al. 2010) data cover the wavelength range which samples the peak of the Planck spectrum for cold sources (6-20 K). This wavelength regime is critical for accurate modeling of the temperature and density structure in the cold environments where stars are born (e.g., Shetty et al. 2009).
![]() |
Figure 1:
|
Open with DEXTER |
The Herschel guaranteed time key program ``Early Phases of
Star-formation'' (EPoS; P.I. O. Krause) sample consists of the
Photodetector Array Camera and Spectrometer (PACS; Poglitsch et al. 2010) and
the Spectral and Photometric Imaging REceiver
(SPIRE; Griffin et al. 2010) imaging-mode observations of sites of both
high- and low-mass star formation. The low-mass science
demonstration phase portion of the sample is the focus of this
contribution. The source CB 244 (L1262; Lynds 1962) is a Bok
globule at a distance of 200 pc (Hilton & Lahulla 1995), with an
approximate extent of
,
or about 0.5 pc. The
CB 244 globule contains two submm peaks, one associated with a Class 0
protostar located at
,
,
and one associated with a starless core
located at
,
.
The protostar drives a molecular outflow
(e.g., Clemens et al. 1991), while the detection of the CB 244 starless
core was first published as an additional source inside the globule
by Launhardt (1996) and Shirley et al. (2000) and produces both an
8
m (Tobin et al. 2010) and a 24
m shadow. The YSO and
starless core are separated by
,
and are therefore
well resolved throughout the PACS and SPIRE bands. We use
Herschel imaging to construct spatially resolved spectral energy
distributions (SEDs) of the entire cloud that cover both sides of
the peak of the SED. These data allow us to reconstruct the
dust-temperature map and column density distribution of the Bok
globule and hence the density profiles and mass distribution with
unprecedented accuracy. They also reveal the role of external
heating and shielding by the envelopes in the energy balance of such
cores in isolated globules.
2 Observations and data processing
2.1 Herschel observations
The source CB 244 was observed with the PACS instrument on board the Herschel Space Observatory on 2009, December 30, during the science
demonstration program. The globule CB 244 was observed at 100 m and
160
m. We obtained two orthogonal scan maps with scan leg
lengths of 9
using a scan speed of 20
/s. The scan
leg position angles guarantee an almost homogeneous coverage of CB 244.
We produced highpass-filtered intensity maps from these data
using the HIPE software package (Ott 2010), version 3.0, build 455.
Besides the standard steps leading to level-1 calibrated data, a
second-level deglitching as well as a correction for offsets in the
detector sub-matrices were performed. Finally, the data were
highpass-filtered, using a median window with a width of 271 data
samples to remove the effects of bolometer temperature
drifts during the course of the data acquisition. Furthermore, we masked
emission structures, in this case both the YSO and starless core
regions, before computing the running median. Masking bright sources
minimizes over-subtraction of source emission in the highpass
filtering step. Finally, the data were projected onto a coordinate
grid using the photProject routine inside HIPE. As a last step, the
flux correction factors provided by the PACS ICC team were
applied. We note that these data have relatively flat background
values, indicating that the highpass reduction used in conjunction
with the masking is a relatively robust scheme for avoiding artifacts
and recovering extended emission in the PACS maps. In addition to
these processing steps, we checked the pointing in the PACS
100
m map against the MIPS 24
m mosaic of the same
region. Using point-sources detected in both images, we found a
pointing offset of
in the 100
m map
relative to the 24
m mosaic. Because the 160
m PACS map
contains no point-sources and was acquired at the same time as the
100
m data, we blindly applied the same pointing correction. The
final PACS 100 and 160
m images are shown in
Fig. 1.
![]() |
Figure 2:
Dust-temperature (color) and hydrogen column density
(white contours) in CB 244. The line-of-sight-averaged mean
dust-temperature was derived pixel by pixel from modified
black-body SED fits to homogeneously beam-smoothed emission maps
from Herschel PACS and SPIRE, Spitzer MIPS70, and
ground-based extinction mapping and submillimeter dust-continuum
maps at 0.8 and 1.3 mm (see text for details). Column density
contours are at {0.1 (thick) 0.3, 0.5, 1 (thick), 2, 3.5, 5, and
7} |
Open with DEXTER |
Maps at 250, 350, and 500 m were obtained with SPIRE on October
20, 2009. Two 9
scan legs were used to cover the source. Two
repetitions resulted in 146 s of scanning time with the nominal speed
of 30''/s. The data were processed within HIPE with the standard
photometer script up to level 1. During baseline removal, we masked
out the high-emission area in the center of the field. For these
data no cross-scan was obtained; therefore, the resulting maps still
showed residual stripes along the scan direction. We used the
Bendo et al. (2010) de-stripping scheme to mitigate this effect. In
addition, we checked the pointing in the SPIRE data by
cross-correlating the images with the PACS 160
m image; we
found that the pointing offsets for all three wavelengths are on order
of 2
or smaller, and therefore we did not correct for this.
The SPIRE 250, 350, and 500
m images are shown in
Fig. 1.
2.2 Other data
Near-IR data: We observed CB 244 in the near-IR






Spitzer data: The Spitzer observations presented here are from two programs: the MIPS observations are from program 53 (P.I. Rieke), while the IRAC observations are from program 58 (P.I. Lawrence). The MIPS observations were reduced using the data analysis tool (DAT; Gordon et al. 2005) according to steps outlined in Stutz et al. (2007). The IRAC frames were processed using the IRAC Pipeline v14.0, and mosaics were created from the basic calibrated data (BCD) frames using a custom IDL program (see Gutermuth et al. 2008).
(Sub)mm continuum data: The SCUBA 850






3 Dust temperature and column density modeling
We used the PACS 100 and 160










For each image pixel, an SED was extracted and fitted with a
single-temperature modified black-body of the form
,
where
is the solid angle of the emitting element,
is the Planck function,
is the
dust-temperature, and
is the optical depth at frequency
.
In a first iteration, we used a simple dust opacity model of
the form
to fit for
,
using
minimization. We found that
fited the
data best over the entire cloud. Note that compact structures were
smoothed out; therefore this cannot be taken as evidence against grain
growth in the centers of the two dense cores. In a second step, we
then fixed the dust model to the Ossenkopf & Henning (1994) model for an MRN
grain size distribution, with thin ice mantles and no coagulation,
which has a
cm2 g-1. The
hydrogen-to-dust mass ratio was fixed to the canonical value of 110
(e.g., Sodroski et al. 1997). We then searched for the optimum
and hydrogen column density
values (the two free
parameters) by calculating flux densities and AV values and then
comparing to the emission and extinction observations, using
minimization. The resulting line-of-sight-averaged
dust-temperature and column density maps are shown in
Fig. 2 together with the SED fits at the central
positions of the two submillimeter peaks. We found the best-fit
column-averaged dust-temperatures for the protostar and prestellar
core of
17.7 K and
10.6 K, respectively. Despite the
fact that each individual image pixel was fitted independently and the
maps at different wavelengths have different outer boundaries, both
the temperature and the column density maps have very little noise and
are very smooth, demonstrating the robustness of our fitting approach.
Furthermore, we evaluated the effect of a possible filtered-out
extended emission component in the chopped 850
m and 1.3 mm
maps. Adding in offsets of 60 mJy/15
beam at 850
m and
12 mJy/11
beam at 1.3 mm, corresponding to 20% of the peak
surface brightness of the cold prestellar core, did not affect the
fitted temperature and column density (less than a 2% change) for the
prestellar core or the protostar. Hence, we conclude that possible
missing extended emission in the (sub)mm maps does not affect our results.
4 Summary and conclusions
As shown in Fig. 2, the line-of-sight-averaged dust-temperature decreases constantly without any significant jump from















Including the new Herschel data, we derive the following parameters
for the protostar:
,
,
K, and
/
,
(cf. Launhardt et al. 2010), confirming the Class 0 classification
according to Chen et al. (1995) and Andre et al. (2000). Furthermore, the
C18O (2-1) FWHM line width for the prestellar core is
0.9 km s-1 (Stutz et al., in prep.); using our fitted
prestellar core mass and temperature, we find that the ratio of
gravitational energy to thermal and turbulent energy is
,
a marginally
sub-critical value which is expected for prestellar cores. For
comparison, Tobin et al. (2010) derive a mass of
3-4
for the prestellar core (integrated over a similar area and scaled
to a distance of 200 pc) using the 8
m shadow (see Fig. 1), a
good agreement given the uncertainties in both mass derivation
methods. Theprominent and extended 3.6
m coreshine (see
Fig. 1), originating from dust-grain scattering of the background
radiation field, is an indication of grain growth (Steinacker et al. 2010) in
the CB 244 cloud. These pieces of evidence together indicate that the
CB 244 globule, and other globules like it, are excellent sources in
which to study the earliest phases of low-mass star-formation. As a
next step and in a follow-up paper, we will employ 3D-modeling to
overcome the effects of line-of-sight averaging and beam-smoothing,
and to reconstruct the full dust-temperature and density structure of
CB 244 and the other sources in our sample. Measuring reliable
temperatures and column densities with the Herschel data in a sample
of prestellar and protostellar cores is a fundamental step towards
revealing the initial conditions of low-mass star-formation.
The authors thank J. Tobin for helpful discussions and D. Johnstone for a critical and helpful referee report. PACS has been developed by a consortium of institutes led by MPE (Germany) and including UVIE (Austria); KU Leuven, CSL, IMEC (Belgium); CEA, LAM (France); MPIA (Germany); INAF- IFSI/OAA/OAP/OAT, LENS, SISSA (Italy); IAC (Spain). This development has been supported by the funding agencies BMVIT (Austria), ESA-PRODEX (Belgium), CEA/CNES (France), DLR (Germany), ASI/INAF (Italy), and CICYT/MCYT (Spain). SPIRE has been developed by a consortium of institutes led by Cardiff University (UK) and including Univ. Lethbridge (Canada); NAOC (China); CEA, LAM (France); IFSI, Univ. Padua (Italy); IAC (Spain); Stockholm Observatory (Sweden); Imperial College London, RAL, UCL-MSSL, UKATC, Univ. Sussex (UK); and Caltech, JPL, NHSC, Univ. Colorado (USA). This development has been supported by national funding agencies: CSA (Canada); NAOC (China); CEA, CNES, CNRS (France); ASI (Italy); MCINN (Spain); Stockholm Observatory (Sweden); STFC (UK); and NASA (USA).
References
- Andre, P., Ward-Thompson, D., & Barsony, M. 2000, Protostars and Planets IV, 59 Bendo, G. J., et al. 2010, A&A, 518, L65 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Chen, H., Myers, P. C., Ladd, E. F., & Wood, D. O. S. 1995, ApJ, 445, 377 [NASA ADS] [CrossRef] [Google Scholar]
- Clemens, D. P., & Barvainis, R. 1988, ApJS, 68, 257 [NASA ADS] [CrossRef] [Google Scholar]
- Clemens, D. P., Yun, J. L., & Heyer, M. H. 1991, ApJS, 75, 877 [NASA ADS] [CrossRef] [Google Scholar]
- Gordon, K. D., Rieke, G. H., Engelbracht, C. W., et al. 2005, PASP, 117, 503 [NASA ADS] [CrossRef] [Google Scholar]
- Griffin, M. J., et al. 2010, A&A, 518, L3 [Google Scholar]
- Gutermuth, R. A., Myers, P. C., Megeath, S. T., et al. 2008, ApJ, 674, 336 [NASA ADS] [CrossRef] [Google Scholar]
- Hilton, J., & Lahulla, J. F. 1995, A&AS, 113, 325 [NASA ADS] [Google Scholar]
- Lada, C. J., Lada, E. A., Clemens, D. P., & Bally, J. 1994, ApJ, 429, 694 [NASA ADS] [CrossRef] [Google Scholar]
- Launhardt, R. 1996, Ph.D. Thesis, University of Jena [Google Scholar]
- Launhardt, R., & Henning, T. 1997, A&A, 326, 329 [NASA ADS] [Google Scholar]
- Launhardt, R., et al. 2010, ApJS, 188, 139 [NASA ADS] [CrossRef] [Google Scholar]
- Lynds, B. T. 1962, ApJS, 7, 1 [NASA ADS] [CrossRef] [Google Scholar]
- Ossenkopf, V., & Henning, T. 1994, A&A, 291, 943 [NASA ADS] [Google Scholar]
- Ott, S. 2010, in Astronomical Data Analysis Software and Systems XIX, ASP Conf. Ser., 00 [Google Scholar]
- Pilbratt, G. L., et al. 2010, A&A, 518, L1 [CrossRef] [EDP Sciences] [Google Scholar]
- Poglitsch, A., et al. 2010, A&A, 518, L2 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Rieke, G. H., & Lebofsky, M. J. 1985, ApJ, 288, 618 [NASA ADS] [CrossRef] [Google Scholar]
- Schlegel, D. J., Finkbeiner, D. P., & Davis, M. 1998, ApJ, 500, 525 [NASA ADS] [CrossRef] [Google Scholar]
- Shetty, R., Kauffmann, J., Schnee, S., Goodman, A. A., & Ercolano, B. 2009, ApJ, 696, 2234 [NASA ADS] [CrossRef] [Google Scholar]
- Shirley, Y. L., Evans, II, N. J., Rawlings, J. M. C., & Gregersen, E. M. 2000, ApJS, 131, 249 [NASA ADS] [CrossRef] [Google Scholar]
- Skrutskie, M. F., Cutri, R. M., Stiening, R., et al. 2006, AJ, 131, 1163 [NASA ADS] [CrossRef] [Google Scholar]
- Sodroski, T. J., Odegard, N., Arendt, R. G., et al. 1997, ApJ, 480, 173 [NASA ADS] [CrossRef] [Google Scholar]
- Steinacker, J., Pagani, L., Bacmann, A., & Guieu, S. 2010, A&A, 511, A9 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Stutz, A. M., Bieging, J. H., Riehe, G. H., et al. 2007, ApJ, 665, 466 [NASA ADS] [CrossRef] [Google Scholar]
- Stutz, A. M., Rubin, M., Werner, M. W., et al. 2008, ApJ, 687, 389 [NASA ADS] [CrossRef] [Google Scholar]
- Stutz, A. M., Rieke, G. H., Bieging, J. H., et al. 2009, ApJ, 707, 137 [NASA ADS] [CrossRef] [Google Scholar]
- Tobin, J. J., Hartmann, L., Looney, L. W., & Chiang, H. 2010, ApJ, 712, 1010 [NASA ADS] [CrossRef] [Google Scholar]
- Ward-Thompson, D., André, P., Crutcher, R., et al. 2007, Protostars and Planets V, 33 [Google Scholar]
Footnotes
- ... CB244
- Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.
All Figures
![]() |
Figure 1:
|
Open with DEXTER | |
In the text |
![]() |
Figure 2:
Dust-temperature (color) and hydrogen column density
(white contours) in CB 244. The line-of-sight-averaged mean
dust-temperature was derived pixel by pixel from modified
black-body SED fits to homogeneously beam-smoothed emission maps
from Herschel PACS and SPIRE, Spitzer MIPS70, and
ground-based extinction mapping and submillimeter dust-continuum
maps at 0.8 and 1.3 mm (see text for details). Column density
contours are at {0.1 (thick) 0.3, 0.5, 1 (thick), 2, 3.5, 5, and
7} |
Open with DEXTER | |
In the text |
Copyright ESO 2010
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