Inference from modelling the chemodynamical evolution of the Milky Way disc
Jan Rybizki
TL;DR
This thesis uses Bayesian forward modelling and chemical evolution simulations to derive the Milky Way's initial mass function and chemical parameters, revealing a broken power law for low-mass stars and a Salpeter-like slope for high-mass stars.
Contribution
It introduces a new chemical enrichment code, Chempy, and provides the first detailed IMF constraints for stars above 8Msun based on chemical evolution modeling.
Findings
IMF for 0.5-8Msun is a broken power law with a break at 1.39Msun.
High-mass slope above 6Msun is -2.28, consistent with Salpeter.
Chemical modeling constrains high-mass IMF better than star counts.
Abstract
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…
Click any figure to enlarge with its caption.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16
Figure 17
Figure 18
Figure 19
Figure 20
Figure 21
Figure 22
Figure 23
Figure 24
Figure 25
Figure 26
Figure 27
Figure 28
Figure 1
Figure 2
Figure 31
Figure 32
Figure 33
Figure 34
Figure 35
Figure 36
Figure 37
Figure 38
Figure 39
Figure 40Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.