Understanding star formation in molecular clouds

Abstract

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 the Herschel satellite it is now possible to determine the column density from dust emission. We use observations and simulations to demonstrate how LOS contamination affects the column density probability distribution function (PDF). We apply a first-order approximation (removing a constant level) to the molecular clouds of Auriga, Maddalena, Carina and NGC3603. 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 flattens after correction. All PDFs have a lognormal part for low column densities with a peak at Av~2, a deviation point (DP) from the lognormal at Av(DP)~4-5, and a power-law tail for higher column densities. Assuming a density distribution rho~r^-alpha, the slopes of the power-law tails correspond to alpha(PDF)=1.8, 1.75, and 2.5 for Auriga, Carina, and NGC3603 (alpha~1.5-2 is consistent gravitational collapse). We find that low-mass and high-mass SF clouds 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 Av~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.