Characteristic structure of star-forming clouds

TL;DR

This paper introduces a new diagnostic method using the probability density function of column density to assess the star-forming potential of molecular clouds, emphasizing the role of filament profiles and their dynamical states.

Contribution

It provides analytical expressions for filament profiles based on N-pdf types and links filament concentration to star formation potential, offering a dynamical perspective.

Findings

Characteristic filament profiles can distinguish star-forming regions.

Star formation potential increases with filament concentration and column density.

Filament models are more relevant than spherical collapse models for star-forming regions.

Abstract

This paper gives a new way to diagnose the star-forming potential of a molecular cloud region from the probability density function of its column density (N-pdf). It gives expressions for the column density and mass profiles of a symmetric filament having the same N-pdf as a filamentary region. The central concentration of this characteristic filament can distinguish regions and can quantify their fertility for star formation. Profiles are calculated for N-pdfs which are pure lognormal, pure power law, or a combination. In relation to models of singular polytropic cylinders, characteristic filaments can be unbound, bound, or collapsing depending on their central concentration. Such filamentary models of the dynamical state of N-pdf gas are more relevant to star-forming regions than are models of spherical collapse. The star formation fertility of a bound or collapsing filament is quantified by its mean mass accretion rate when in radial free fall. For a given mass per length, the fertility increases with the filament mean column density and with its initial concentration. In selected regions the fertility of their characteristic filaments increases with the level of star formation.