Hung-Lin Liao(NTNU); Yueh-Ning Lee(NTNU)
The density probability density function (PDF) is a widely used tool to investigate the structures of molecular clouds and the underlying physics. Simulations and analytical models have suggested that the hierarchical structures, resulting from turbulent motion, produce a lognormal PDF with a power-law tail at high density due to self-gravity. The aim of this project is to find out the characteristic scale of gravitational collapse. We identify the dense, gravitationally collapsing substructures in molecular clouds with use of the dendrogram and test different ways to smooth the data of dense region to detect the characteristic scale. We apply this approach on both column density PDF and density PDF to analyze the effect of self-gravity on density structure of molecular clouds and star formation process.