Abstract
Abstract The column density probability distribution function (N-PDF) of Giant Molecular Clouds (GMCs) has been used as a diagnostic of star formation. Simulations and analytic predictions have suggested that the N-PDF is composed of a low-density lognormal component and a high-density power-law component tracing turbulence and gravitational collapse, respectively. In this paper, we study how various properties of the true 2D column density distribution create the shape, or “anatomy,” of the PDF. We test our ideas and analytic approaches using both a real, observed PDF based on Herschel observations of dust emission and a simulation that uses the ENZO code. Using a dendrogram analysis, we examine the three main components of the N-PDF: the lognormal component, the power-law component, and the transition point between these two components. We find that the power-law component of an N-PDF is the summation of N-PDFs of power-law substructures identified by the dendrogram algorithm. We also find that the analytic solution to the transition point between lognormal and power-law components proposed by Burkhart et al. is applicable when tested on observations and simulations, within the uncertainties. Based on the resulting anatomy of the N-PDF, we suggest applying the N-PDF analysis in combination with the dendrogram algorithm to obtain a more complete picture of the global and local environments and their effects on the density structures.
Highlights
Star formation occurs in dense filamentary structures within molecular environments that are governed by the complex interaction of gravity, magnetic fields, and turbulence (McKee & Ostriker 2007)
When we examine the N-PDFs of individual “leaf” structures, we find that the N-PDFs of the individual “leaf” structures can be roughly categorized into three categories
The red curve is a lognormal + power-law fit to the histogram above the range of column density affected by the uncertainty due to the choice of the map area and the detection limit
Summary
Star formation occurs in dense filamentary structures within molecular environments that are governed by the complex interaction of gravity, magnetic fields, and turbulence (McKee & Ostriker 2007). Simulations and observations have shown N-PDFs to be an important diagnostic of turbulence and star formation efficiency in local star forming clouds (Federrath & Klessen 2012; Collins et al 2010; Burkhart et al 2015a; Myers 2015). N-PDFs, as available from observations, have been utilized extensively for many different tracers of the ISM This includes molecular line tracers such as CO (Lee et al.2012; Burkhart et al 2013b) and column density tracers such as dust (Kainulainen et al 2009; Froebrich & Rowles 2010; Schneider et al 2013, 2014, 2015b; Lombardi et al 2015). Tracing the N-PDF using dust emission and absorption provides the largest dynamic range of densities, in contrast to molecular line tracers such as CO, which do not trace the true column density distribution due to depletion and opacity effects (Goodman et al 2009a; Burkhart et al 2013a,b)
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