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Inference from modelling the chemodynamical evolution of the Milky Way disc
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In this thesis, the field star Initial Mass Function (IMF) and chemical evolution parameters for the Milky Way (MW) are derived using a forward modelling technique in combination with Bayesian statistics. Starting from a local MM disc model, observations of stellar samples in the Solar Neighbourhood are synthesised and compared to the corresponding volume-complete observational samples of Hipparcos stars. The resulting IMF, derived from observations in the range from 0.5 to 8Msun, is a two-slope broken power law with powers of -1.49 +- 0.08 and -3.02 +- 0.06 for the low-mass slope and the high-mass slope, respectively, with a break at 1.39 +- 0.05Msun. In order to constrain the IMF for stars more massive than 8Msun, a fast and flexible chemical enrichment code, Chempy, was developed, which is also able to reproduce spatial and stellar population selections of observational samples. The inferred high-mass slope for stellar masses above 6Msun is -2.28 +- 0.09, accounting for the systematic effects of different yield sets from the literature. This shows that constraints from chemical modelling, similarly to hydrodynamical simulations of the Galaxy, demand a Salpeter high-mass index. This is hard to recover from star count analysis given the rareness of high-mass stars.
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Cited by 1 Pith paper
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Inferring Galactic Parameters from Chemical Abundances: A Multi-Star Approach
The method recovers the IMF high-mass slope and Type Ia supernova rate to sub-percent precision from the chemical abundances of up to 200 simulated stars using a neural-network emulator and Hamiltonian Monte Carlo.
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