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Joining worlds apart: Observations and Simulations of the First Stars in the Universe (OBSI-FSU)
Start date: Oct 8, 2008, End date: Apr 7, 2010 PROJECT  FINISHED 

"The First Stars in the universe are of great importance in the astrophysical context as a probe of the early universe, although the existence of their survivors has not yet been established in searches of metal-poor stars. The simulations of the First Stars have a key role in not only identifying them but also gaining insight into the evolution of the universe and the star formation history of our Galaxy. The applicant's specialized knowledge in simulating the First Stars in the global 1D stellar evolution approximation will help advanced stellar simulation including non-standard physics at the host institute. Several aspects of these first stars are different from stars born more recently, like our sun. Differences are especially important in the mixing physics (complex convective events) that evade the 1D approach. The applicant's models will provide the understanding of the overall astrophysical context especially for multi-dimensional effects such as convection, rotation and magnetic fields on the mixing episodes carried out by the Keele group. The proposed research project will lay the foundation for future long-term collaboration as we are just beginning to explore the complex mixing physics in the First Stars. The applicant has also conceived and implemented a database of the metal-poor stars, and developed tools that allow effective interpretation of new model results. The increasing number of these important tracers of the early Universe allows a statistical foundation of general properties of the First Stars. The applicant's expertise, database and tools are unique and not yet public. These knowledge components will greatly enhance the ability of the Keele group in this area to systematically apply their advanced, hydrodynamics based models to observations and will accelerate its innovation cycle by having faster feedback from confronting new simulations and model predictions with observations."

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