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Volume 540, April 2012
Article Number L11
Number of page(s) 8
Section Letters
Published online 04 April 2012

Online material

Appendix A: Observations and column density map

The Rosette was observed during the science demonstration phase (SDP) within the HOBYS key program. This program is dedicated to the earliest stages of high-mass star formation and images all molecular complexes that form high-mass stars at less than 3 kpc with SPIRE (Griffin et al. 2010) and PACS (Poglitch et al. 2010) using the Herschel satellite (Pilbratt et al. 2010). The SPIRE and PACS data6 from 70 μm to 500 μm were obtained on October 20, 2009 in parallel mode with a scanning speed of 20′′/s. Two orthogonal coverages of size 1°45′ × 1°25′ were performed, mapping the (largest) southeast part of the Rosette molecular cloud. The SPIRE data were reduced with HIPE version 7.1956, using a modified version of the pipeline scripts, i.e., observations that were taken during the turnaround at the map borders were included, the most recent calibration tree was used, and the destriper-module with a polynomial baseline of 0th order was applied. The two orthogonally scanned maps were then combined using the “naive-mapper” (i.e., a simple averaging algorithm). The destriper module significantly improved the resulting maps, compared to the first data reduction just after the SDP (Schneider et al. 2010b). The angular resolutions at 160, 250, 350, and 500 μm, are  ~12′′,  ~18′′,  ~25′′, and  ~37′′, respectively.

The column density was determined from a pixel-to-pixel modified black body fit to four wavelengths of PACS and SPIRE (160, 250, 350, 500 μm, all maps were smoothed to the beamsize of the 500 μm map, i.e.,  ~37′′). For the region covered by PACS and SPIRE simultaneously, we fixed the specific dust opacity per unit mass (dust+gas) approximated by the power law κν    =    0.1   (ν/1000   GHz)β cm2/g and β = 2, and left the dust temperature and column density as free parameters (see Hill et al. 2011; Arzoumanian et al. 2011 for details). For the region only covered with SPIRE7 we used 17.3 K, the median value of the SED-derived temperature across the main map where PACS and SPIRE overlap giving us four-band coverage at 160, 250, 350, and 500 μm. We checked the fitted SEDs and found no major discrepancy in the fits, though the method described above assumes a single temperature and optically thin emission, which is not always a good approximation if there is a temperature variation along the line-of-sight, noise, and if the dust becomes optically thick at shorter wavelengths. Shetty et al. (2009), for example, showed that this can even produce an anti-correlation of β and T which was claimed to be observed by other authors. However, it is beyound the scope of this paper to go more into detail. While the column density map shown in Schneider et al. (2010b) was calibrated using extinction maps, we now recovered the Herschel zero-flux levels of the Rosette field with Planck data (Bernard et al., priv. commun.). The final column density map is shown in Fig. 4.

Appendix B: Curvelet/wavelet decomposition and filament tracing

There are two parameters determining the detection of filaments: First, the seperation into curvelets and wavelets, and second the threshold of DisPerSE to detect filaments. From our experience on the curvelet/wavelet analysis from Herschel column density maps so far (André et al. 2010; Arzoumanian et al. 2011; Hill et al. 2011), and from several tests with Rosette, we arrived at a good compromise of 20% of the intensity being in the curvelets (a difference of around  ± 10%, however, does not change the overall picture). This reveals the filamentary structure without completely suppressing the more compact sources. The DisPerSE algorithm detects filaments starting from a given threshold (defined as difference between saddle points and peak values) on the curvelet image. However, the column density map is a 2D-projection of the volume density while DisPerSE works topologically, connecting all emission features such that projection effects may create links between filaments that are not physically related. To overcome this caveat, filament tracing using molecular line data cubes can be a solution, as first tests on the DR21 filament have shown (Schneider et al., in prep.).

Figure 5 shows as an example a close-up of the crowded center region of Rosette where different thresholds were applied. A threshold is defined by an intensity contrast between pixels, the lowest one starting at 0.5 × 1021 cm-2 and accordingly finding many filaments, up to to a fairly conservative value of 2.9 × 1021 cm-2, leaving only the most prominent features. For this paper, a threshold of 1.0 × 1021 cm-2 was choosen in order not to detect too faint filaments. It is only the most prominent ones that are able to provide enough material that is accreted onto the cluster center to build up high enough masses. Again, changing the threshold does not alter these prominent filaments, they always remain detected.

Appendix C: Probability density function of the Rosette cloud

The probability density function of the whole cloud obtained from the column density map (Figs. 2 or 4) is shown in Fig. 6 in linear and logarithmic scaling. It displays a log-normal form for lower column densities and a clearly defined power-law tail for higher column densities that was fitted with a power-law. This is not generally the case, while the PDF of the high-mass SF region NGC 6334 also shows a clear power-law tail (Russeil et al., in prep.), the PDFs of other high-mass SF clouds are more complex and show several breaks in the PDFs (Hill et al. 2011; Csengeri et al., in prep.). The reason for that can partly be line-of-sight effects and limited angular resolution. A more detailed discussion of PDFs of intermediate- and high-mass SF regions and comparison to models is presented in Csengeri et al. (in prep.).

thumbnail Fig. 4

Column density map of the Rosette molecular cloud, obtained from the 160, 250, 350, and 500 μm maps from Herschel. Known infrared-clusters are indicated in the plot as blue stars (“Pl” refers to Phelps & Lada (1997), A, B, etc. the clusters from Poulton et al. 2008), and labeling “Refl” those from Román-Zúñiga et al. 2008). White stars in the upper right corner indicate the O-stars from NGC2244.

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thumbnail Fig. 5

Close-up of the curvelet image (Fig. 1) of the center region of the Rosette molecular cloud with the filamentary structure traced by DisPerSE, indicated with white lines. Different thresholds (called “persistence”, i.e. intensity contrast level, for filament detection were used (2.9, 1.0, 0.5 × 1021 cm-2 from left to right). The curvelet image has a maximum value for the column density of 2 × 1022 cm-2 with a sigma of 0.5 × 1021 and the original column density map a maximum of 9.4 × 1022 cm-2 with a sigma of 1.4 × 1021.

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thumbnail Fig. 6

Probability density function of the whole cloud obtained from the column density map in linear (top) and logarithmic (bottom) scaling. The upper labeling indicates the visual extinction. The red dashed line shows a power-law fit (the high-density range beyond AV = 20m is not well resolved, we therefore did not attempt to fit a second power law.)

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© ESO, 2012

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