Understanding star formation in molecular clouds I. A universal probability distribution of column densities ? [GA]


Column density maps of molecular clouds are one of the most important observables in the context of molecular cloud- and star-formation (SF) studies. With Herschel it is now possible to reveal rather precisely the column density of dust, 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 an overestimation of the dust emission of molecular clouds, in particular for distant clouds. This implies too high values for column density and mass, and a misleading interpretation of probability distribution functions (PDFs) of the column density. In this paper, we demonstrate by using observations and simulations 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 Av ~ 2 and a deviation point (DP) from the lognormal at Av(DP) ~ 4-5 (corresponding to a surface density of ~45 Msun pc-2). For higher column densities, all PDFs have a power-law tail with an average slope that corresponds to an exponent alpha = 1.9+-0.2 for an equivalent spherical density distribution rho ~ r^-alpha consistent with a structure dominated by self-gravity (local free-fall of individual cores and global collapse of gas on larger scales, such as filaments). Our PDF study suggests that there is a common, universal column density break at Av ~ 4-5 for all cloud types where the transition between supersonic turbulence and self-gravity takes place.

Read this paper on arXiv…

N. Schneider, V. Ossenkopf, T. Csengeri, et. al.
Thu, 13 Mar 14