Lee Hartmann, Edwin Bergin, and Fabian Heitsch (University of Michigan) will compute models of flow-driven molecular cloud formation to derive the appropriate initial conditions for star formation. The goal is to generate the turbulent substructure needed to create the dense concentrations which ultimately form stars as a result of various instabilities in post-shock gas, rather than put this substructure in ''by hand''. The turbulence generated by these instabilities will be modified by global flows generated by self-gravity; such flows can produce mid-scale concentrations of mass leading to the formation of star clusters. The program will involve a series of calculations of increasing complexity, including molecule formation and other chemistry, cooling at high densities, self-gravity, and the effects of magnetic fields. Detailed radiative transfer calculations will be employed to compare in detail with observations of molecular clouds.
This project will attempt to answer the following questions: Do instabilities which arise naturally in flow-driven molecular cloud formation produce a mass spectrum of dense concentrations consistent with observations of protostellar cores? Do these initial perturbations solely determine the core mass function, or is there significant gravitational merging/coagulation? Is the resulting core spectrum consistent with the stellar initial mass function, or must there be additional fragmentation? How does the environment (metallicities, flow parameters) affect the fragmentation and thus the initial mass function? And how do magnetic fields affect the formation of protostellar cores within flow-formed molecular clouds? These questions are of direct importance to understanding star formation and the origin of the stellar initial mass function.
The results of this project will have application to research in the areas of galaxy mergers and star formation at low metallicities because the mechanism of colliding flows is not limited to current Galactic star formation. This project will result in a numerical data set that can be readily compared to observational data of existing or upcoming high-resolution facilities; the simulation results will be made publicly accessible, with analysis tools also provided to extract basic observables. In addition, the numerical projects as well as their results will provide ample training opportunities for undergraduate or graduate student research projects.
