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Column density Probability Distribution Function

RESEARCH

A combined column density-temperature map for Mon R2 giant molecular cloud. Color is mapped as temperature and intensity as column density.

Star formation is an end product of cloud fragmentation. The newly formed stars are called protostars and are found in the densest part of molecular clouds. Using the far-infrared dust emission, we can estimate the density of the clouds. Further, by studying the distribution of column density in such cloud, we can infer the conditions of star formation. Using this approach, I studied the column density probability distribution function (N-PDF in short) for Mon R2 giant molecular cloud and report a prominent powerlaw feature in denser parts of this molecular cloud. Moreover, I do the entire analysis in various localized regions of Mon R2, defined according to the geometry of gas and number of protostars in those regions. Our findings show that for regions with relatively diffuse gas and no protostars, N-PDF takes a lognormal form. Similarly, for regions that contain a high number of protostars, such as a protostellar cluster, the N-PDF has lognormal shape in the low density regime but develops a prominent powerlaw tail in high density regime. Finally, for the regions that have an a aggregate of gas filaments and a moderate number of protostars, the main powerlaw breaks into another secondary powerlaw. This paper provides first observational evidence of such a double powerlaw feature, which is a unique characteristic of regions that have an aggregate of filamentary structures. The lognormal behavior of N-PDF is attributed to supersonic turbulence, whereas a powerlaw feature develops when gas self-gravity starts to dominate.

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