Issue |
A&A
Volume 518, July-August 2010
Herschel: the first science highlights
|
|
---|---|---|
Article Number | L102 | |
Number of page(s) | 7 | |
Section | Letters | |
DOI | https://doi.org/10.1051/0004-6361/201014666 | |
Published online | 16 July 2010 |
Online Material
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Figure 3:
Composite 3-color images of the |
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Figure 4:
Mass vs. size diagrams for the starless cores detected with Herschel-SPIRE/PACS in Aquila ( left) and Polaris ( right) (blue triangles). The masses were derived as explained in Appendix A (see also Könyves et al. 2010) and the sizes were measured at 250 |
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Appendix A: Derivation of core/filament properties and effects of distance uncertainties
As described in more detail in a companion paper by Könyves et al. (2010) on Aquila, the masses of the cores identified in the Herschel images with the getsources algorithm (see Men'shchikov et al. 2010)
were derived by fitting grey-body functions to the spectral energy distributions (SEDs) constructed from the integrated
flux densities measured with SPIRE/PACS for each core. We assumed the dust opacity law
cm2/g, where
denotes frequency and
is the dust opacity per unit (gas + dust) mass column
density. This dust opacity law, which is very similar to that advocated
by Hildebrand (1983), is consistent with the value
cm2/g adopted for starless cores in numerous
earlier studies (e.g., Motte et al. 1998).
Ignoring any systematic distance effect (see below), the core mass uncertainties are dominated by the uncertainty in
,
typically a factor of
2.
Cores were classified as either protostellar or starless based on the presence or absence of significant PACS emission
at 70
m, respectively (cf. Bontemps et al. 2010; Dunham et al. 2008).
In the Polaris field, the cirrus noise level is so low (cf. Fig. 4-right) that we cannot exclude
that a fraction of the 302 candidate starless cores extracted with getsources correspond to background galaxies.
A column density map was derived for each region from the Herschel images smoothed to the SPIRE 500 m
resolution (36.9
FWHM) using a similar SED fitting procedure on a pixel by pixel basis (see, e.g., Figs. 1 and 6 of Könyves et al. 2010 for Aquila).
To obtain the maps of the filamentary background shown in Fig. 1 of this paper, we then performed
a ``morphological component analysis'' decomposition (e.g., Starck et al. 2003) of the original column density maps on curvelets and wavelets. The curvelet component images shown in Fig. 1
provide a good measurement of the column density distribution of the
filamentary background after subtraction of the compact sources/cores
since the latter are contained in the wavelet component. We estimate
that these column density maps are accurate to within a factor of
2.
The scaling in terms of the mass per unit length along the filaments is
more uncertain, however, as it depends on distance (see below) and
would in principle require a detailedanalysis of the radial profiles of
the filaments, which is beyond the scope of the present letter. Here,
we simply assumed that the filaments had a Gaussian radial column
density profile and multiplied the surface density maps by
,
where W is the typical FWHM width of the filaments. We assumed a mean molecular weight of
.
At this stage, the correspondence between the critical line mass of the filaments,
,
and the visual extinction threshold,
(see Sect. 4), is thus accurate to at best a factor of
2.
There is some ambiguity concerning the distance to the Aquila Rift region.
A number of arguments, presented in a companion paper by Bontemps et al. (2010),
suggest that the whole region corresponds to a coherent cloud complex at
d- = 260 pc (see also Gutermuth et al. 2008), which is the default distance adopted in the present paper for Aquila.
However, other studies in the literature (see references in Bontemps et al. 2010) place the complex at a larger distance,
d+ = 400 pc. It is thus worth discussing briefly how our Aquila results would be affected
if we adopted the larger distance estimate, d+, instead of d-.
The core mass estimates, which scale as
where
is integrated flux density and
is the Planck function, would systematically increase by a factor of 2.4.
This would shift the CMF shown in Fig. 2-left to the right and thus lower the efficiency
from
20-40% to
10-20%.
In the mass versus size diagram of Fig. 4, the cores would move upward as indicated in the left panel
of the figure, which would increase the fraction of candidate bound cores in Aquila from 63% to 81%.
The column density map of the Aquila filaments shown in Fig. 1 would be unchanged, but
the scaling in terms of the mass per unit length along the filaments would change by
50% upward, since the physical width of the filaments would increase by
50%. In other words, the highlighted regions in Fig. 1-left, where the mass per unit length of the filaments exceeds half the critical value, would slightly expand,
increasing the contrast with the Polaris filaments and improving the
correspondence between the spatial distribution of the prestellar
cores/protostars in Aquila and that of the gravitationally unstable
filaments. To summarize, our main conclusions do not depend strongly on
the adopted distance.
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