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Galaxy formation through the eyes of globular clusters (CLUSTERS)
Date du début: 1 nov. 2013, Date de fin: 31 oct. 2018 PROJET  TERMINÉ 

"Globular clusters (GCs) are among the first baryonic structures to form at a redshift of 10 and they witnessed the earliest phases of galaxy formation. Despite their ubiquity and importance for our understanding of the stellar initial mass function, star formation and chemical evolution in the early Universe, their origin is shrouded in mystery. They could have formed in gas rich discs, similarly to young massive clusters (YMCs) that we see forming today in starburst environments; or they could require a more exotic environment such as the centre of dark matter ``mini-haloes"".The Milky Way GCs are resolved into their constituent stellar population making them the obvious place to look for clues. Their pristine properties are, however, affected by a Hubble time of dynamical evolution within an evolving Milky Way. In this proposal I present three projects to determine the initial properties of GCs, allowing them to be used as robust probes of early star formation, stellar evolution and cosmology. Specifically, I will: (1) dynamically evolve YMCs on a star-by-star basis and achieve a complete census of the fate of the clusters and their debris (``cold"" streams) within the framework of the hierarchical assembly of the Milky Way; (2) I will develop an extremely fast cluster evolution algorithm to do population synthesis of (globular) star clusters which will uniquely establish their initial masses, densities and the corresponding distributions; and (3) I will break the degeneracy of a dark matter halo, tidal heating and alternative gravity laws on the kinematics of GCs and determine whether Milky Way GCs contain dark matter, or not.Galactic archaeology is entering a Golden Age. ALMA is operational and already putting constraints on the formation of YMCs and Gaia is due to fly next year. The three novel projects presented here will pave the way and prepare for the wealth of unprecedented data."

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