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Register a new userThe Probability Distribution Function of Gas Surface Density in M33
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The probability distribution functions (PDFs) for atomic, molecular, and total gas surface densities of M33 are determined at a resolution of about 50~pc over regions that share coherent morphological properties to unveil fingerprints of self-gravity across the star-forming disk. Most of the total gas PDFs from the central region to the edge of the star-forming disk are well-fitted by log-normal functions whose width decreases radially outwards. Because the HI velocity dispersion is approximately constant across the disk, the decrease of the PDF width is consistent with a lower Mach number for the turbulent ISM at large galactocentric radii where a higher fraction of HI is in the warm phase. The atomic gas is found mostly at face-on column densities below N$_{H}^{lim}$=2.5 10$^{21}$~cm$^{-2}$, with small radial variations of N$_{H}^{lim}$. The molecular gas PDFs do not show strong deviations from log-normal functions in the central region where molecular fractions are high. Here the high pressure and rate of star formation shapes the PDF as a log-normal function dispersing self-gravitating complexes with intense feedback at all column densities that are spatially resolved. Power law PDFs for the molecules are found near and above N$_H^{lim}$, in the well defined southern spiral arm and in a continuous dense filament extending at larger galactocentric radii; this is evident in cloud samples at different evolutionary stages along the star formation cycle. In the filament nearly half of the molecular gas departs from a log-normal PDF and power laws are also observed in pre-star forming molecular complexes. The slope of the power law is between -1 and -2. This slope, combined with maps showing where the different parts of the power law PDFs come from, suggest a power-law stratification of density within molecular cloud complexes, which is consistent with the dominance of self-gravity.
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Both observational and theoretical research over the past decade has demonstrated that the probability distribution function (PDF) of the gas density in turbulent molecular clouds is a key ingredient for understanding star formation. It has recently been argued that the PDF of molecular clouds is a pure power-law distribution. It has been claimed that the log-normal part is ruled out when using only the part of the PDF up/down to which it is complete, that is where the column density contours are still closed. By using the results from high-resolution magnetohydrodynamical simulations of molecular cloud formation and evolution, we find that the column density PDF is indeed composed of a log-normal and, if including self-gravity, a power-law part. We show that insufficient sampling of a molecular cloud results in closed contours that cut off the log-normal part. In contrast, systematically increasing the field of view and sampling the entire cloud yields a completeness limit at the lower column densities, which also recovers the log-normal part. This demonstrates that the field of view must be sufficiently large for the PDF to be complete down to its log-normal part, which has important implications for predictions of star-formation activity based on the PDF.
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