Free Access
Issue
A&A
Volume 527, March 2011
Article Number A111
Number of page(s) 14
Section Interstellar and circumstellar matter
DOI https://doi.org/10.1051/0004-6361/201015916
Published online 04 February 2011

Online material

Appendix A: Frequency maps

Figures A.1 − A.3 show the 100 μm, 160 μm, 250 μm, and 350 μm surface brightness maps for the three SDP fields. The maps for 500 μm are not included but their appearance, apart from the lower intensity and lower spatial resolution, is almost identical with the 350 μm maps.

thumbnail Fig. A.1

Surface brightness maps of the field PCC288. The zero point of the intensity scale has been set by comparison with the IRIS and Planck maps. In the lower frames the dashed line corresponds to the size of the upper frames showing the PACS observations.

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thumbnail Fig. A.2

Surface brightness maps of the field PCC550.

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thumbnail Fig. A.3

Surface brightness maps of the field PCC249.

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Appendix B: Residual maps at 160 μm–500 μm

The quality of the Bν(T)νβ fits and the maps themselves can be evaluated by examining the residual maps at the five wavelengths used in the SED fit. These maps are shown in Figs. B.1B.3.

In PCC288 the average residuals are  −4.0, 16.9, 6.7,  −6.3, and 1.4 MJy sr-1 in the five bands in the order of increasing wavelength. The corresponding values are  −0.35, 2.4, 2.4,  −1.9, and 0.4 MJy sr-1 in the field PCC550 and  −3.8, 17.3,  −0.7,  −1.6, and 0.47 MJy sr-1 in the field PCC249. Allowing some errors in the gain, the estimated accuracies of the offsets (see Table 2) appear to have been realistic.

In PCC288 the largest residuals,  ~100 MJy sr-1, are found at the centre of the 160 μm map. This is associated with the brightest point source and is still less than 10% of the surface brightness. In Fig. B.3 the residual images are strongly saturated and one can see both negative and positive values on the two sides of a source. Although the residuals reach several hundred MJy sr-1 these are only at a  ~5% level. The positions of the sources themselves agree in all frequency maps so that astrometric errors should not be a significant factor. Unlike in the case of the fast scanning speed, the intermediate scanning speed used in our observations should not result in a significant smearing of the PACS beam. Nevertheless, the residuals could be associated with an imperfect deconvolution of the detector time constants.

thumbnail Fig. B.1

Residual maps of the surface brightness in the field PCC288 at four wavelengths when observations were fitted with the spectral index as a free parameter. The resolution is 1 arcmin.

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thumbnail Fig. B.2

Residual maps of the surface brightness in the field PCC550 at four wavelengths.

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thumbnail Fig. B.3

Residual maps of the surface brightness in the field PCC249 at the four wavelengths.

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B.1. Maps of the spectral index uncertainty

The derived spectral index values are affected by observational noise, errors in the zero point of the adopted surface brightness scale, and errors in the gain calibration. Figure B.4 shows maps that can be used to assess the importance of gain calibration and zero point errors. As discussed in Sect. 3.3, we modified the 250 μm and 500 μm surface brightness maps by adding or subtracting the zero point uncertainties from Table 2 and by scaling the maps by an amount corresponding to a 10% gain uncertainty. The changes at the two wavelengths were made in opposite directions in order to have the maximum effect in the β value. By applying 1σ shifts in the gain and in the offset and at both wavelengths critical for the determination of the spectral index we should get conservative limits for the spectral indices. The maps of minimum and maximum spectral indices are shown in Fig. B.4.

thumbnail Fig. B.4

Estimated uncertainty of the spectral index maps. The first column shows the derived values (as in Fig. 4). The second and the third columns show the minimum and maximum values of β consistent the estimated zero point uncertainties and an error of 10% in the gain calibration. The contours are drawn between 1.4 and 2.9 in steps of 0.3 units (white contours starting with value 2.3).

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B.2. Temperature and spectral index maps without 100 μm data

The subtraction of the VSG emission from the 100 μm data relied on the ratio of the VSG and BG grains in the Désert et al. (1990) dust model. This also affects the 160 μm data but only as an uncertainty of the zero point of the intensity scale. To check to what extent the colour temperature and the spectral index maps are influenced by the 100 μm data, we recomputed the parameters using the 160 μm−500 μm data only. The resulting maps of the colour temperature and the spectral index are shown in Fig. B.5.

The maps are morphologically similar to those shown in Fig. 4. The largest differences are in PCC550 where, without the 100 μm data, the spectral index map closely follows the shape of the dense filament. The appearance of SW part of that map again suggests the presence of some artifact, the β values decreasing close to one. Compared to Fig. 4, PCC249 exhibits somewhat lower values of β and a higher range of temperatures.

thumbnail Fig. B.5

The colour temperature and dust spectral index map obtained by fitting the observations between 160 μm and 500 μm.

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© ESO, 2011

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