学术文献库

To understand the formation of stars from clouds of molecular gas, one essentially needs to know two things: What gas collapses, and how long it takes to do so. We address these questions by embedding pseudo-Lagrangian tracer particles in three simulations of self-gravitating turbulence. We identify prestellar cores at the end of the collapse, and use the tracer particles to rewind the simulations to identify the preimage gas for each core at the beginning of each simulation. This is the first of a series of papers, wherein we present the technique and examine the first question: What gas collapses? For the preimage gas at the t=0, we examine a number of quantities; the probability distribution function (PDF) for several quantities, the structure function for velocity, several length scales, the volume filling fraction, the overlap between different preimages, and fractal dimension of the preimage gas. Analytic descriptions are found for the PDFs of density and velocity for the preimage gas. We find that the preimage of a core is large and sparse, and we show that gas for one core comes from many turbulent density fluctuations and a few velocity fluctuations. We find that binary systems have preimages that overlap in a fractal manner. Finally, we use the density distribution to derive a novel prediction of the star formation rate.