Möglichkeitsdenken

Roussel, Martin

doi:10.30965/9783846755549_010

Cited by 1 publication

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As shown by various authors (e.g., Kainulainen et al 2009, Hill et al 2011, Russeil et al 2013, 2013, a power-law tail for high column densities emerges for starforming regions. We perform a linear regression fit in order to determine the slope s of the power-law tail.…”

Section: Pdfs From Observationsmentioning

confidence: 77%

“…All maps presented in this paper -and in the furthcoming ones -were treated in the same way with regard to data reduction and determination of the column density maps. For the data reduction of the Herschel wavelengths, we used the HIPE10 pipeline, including the destriper task for SPIRE (250, 350, 500 µm), and HIPE10 and scanamorphos v12 (Roussel et al 2013) for PACS (70 and 160 , Poglitsch et al 2010). The SPIRE (Griffin et al 2010) maps include the turnaround-data (when the satellite changed mapping direction for the scan) and were calibrated for extended emission.…”

Section: Appendix A: Effects Of Binning and Cropping On The Pdfmentioning

confidence: 99%

See 1 more Smart Citation

Understanding star formation in molecular clouds I. Effects of line-of-sight contamination on the column density structure

Schneider,

Ossenkopf,

Csengeri

et al. 2014

Preprint

View full text Add to dashboard Cite

Column-density maps of molecular clouds are one of the most important observables in the context of molecular cloud-and starformation (SF) studies. With the Herschel satellite it is now possible to precisely determine the column density from dust emission, which is the best tracer of the bulk of material in molecular clouds. However, line-of-sight (LOS) contamination from fore-or background clouds can lead to overestimating the dust emission of molecular clouds, in particular for distant clouds. This implies values that are too high for column density and mass, which can potentially lead to an incorrect physical interpretation of the column density probability distribution function (PDF). In this paper, we use observations and simulations to demonstrate how LOS contamination affects the PDF. We apply a first-order approximation (removing a constant level) to the molecular clouds of Auriga and Maddalena (low-mass star-forming), and Carina and NGC3603 (both high-mass SF regions). In perfect agreement with the simulations, we find that the PDFs become broader, the peak shifts to lower column densities, and the power-law tail of the PDF for higher column densities flattens after correction. All corrected PDFs have a lognormal part for low column densities with a peak at A v ∼2 mag, a deviation point (DP) from the lognormal at A v (DP)∼4-5 mag, and a power-law tail for higher column densities. Assuming an equivalent spherical density distribution ρ ∝ r −α , the slopes of the power-law tails correspond to α PDF = 1.8, 1.75, and 2.5 for Auriga, Carina, and NGC3603. These numbers agree within the uncertainties with the values of α ≈ 1.5, 1.8, and 2.5 determined from the slope γ (with α = 1 − γ) obtained from the radial column density profiles (N ∝ r γ ). While α ∼ 1.5-2 is consistent with a structure dominated by collapse (local free-fall collapse of individual cores and clumps and global collapse), the higher value of α > 2 for NGC3603 requires a physical process that leads to additional compression (e.g., expanding ionization fronts). From the small sample of our study, we find that clouds forming only low-mass stars and those also forming high-mass stars have slightly different values for their average column density (1.8 10 21 cm −2 vs. 3.0 10 21 cm −2 ), and they display differences in the overall column density structure. Massive clouds assemble more gas in smaller cloud volumes than low-mass SF ones. However, for both cloud types, the transition of the PDF from lognormal shape into power-law tail is found at the same column density (at A v ∼4-5 mag). Low-mass and high-mass SF clouds then have the same low column density distribution, most likely dominated by supersonic turbulence. At higher column densities, collapse and external pressure can form the power-law tail. The relative importance of the two processes can vary between clouds and thus lead to the observed differences in PDF and column density structure.

show abstract

Section: Pdfs From Observationsmentioning

confidence: 77%

Section: Appendix A: Effects Of Binning and Cropping On The Pdfmentioning

confidence: 99%