How badly do we understand star formation?
||How badly do we understand star formation?|
||SNIC Medium Compute|
||Florent Renaud <firstname.lastname@example.org>|
||2022-01-02 – 2023-02-01|
The process of star formation is the most important process in the evolution of galaxies. It sets how the gas of hydrogen and helium formed shortly after the BigBang is converted into stars, and how these stars create and release all the heavier chemical elements of the periodic table. In the last decade, simulations of galaxy formation have concluded that, without star formation and stellar feedback, it is impossible to match most of the observables of galaxies. That is, the small-scale process of star formation influences the galactic evolution on scales 5 to 7 orders of magnitude greater. However, virtually every galaxy and cosmological simulation has its own implementation of the star formation in a sub-grid model, and quantitative convergence on the final results is yet missing. Because of the diversity of physical conditions in which star formation takes place, and because of the enormous range of scales involved, the research community still has not found which recipe best matches the observations. Even worst: the differences caused by the various models have not been properly examined.
In this project, we aim at tackling this question by running a suite of galaxy simulations encompassing a wide range of physical conditions (Milky Way-like, dwarf galaxies, gas-rich galaxies, interacting galaxies, galaxies in the early Universe), and use several of the most commonly-used models for star formation. We will then compare the star formation rates and efficiencies between the different models, the clustering of star formation, the number of star clusters formed, their mass function, spatial distribution etc. We will build maps, 2-point correlation functions, power spectra, probability distribution function to quantify precisely the differences between the models. We will likely find that some models lead to similar results, which will be a very important outcome for the community. But we also expect models to induce important divergences, particularly on the properties of the star clusters. Depending on the differences, we will create observables to be confronted to observational data, to either confirm or rule out specific recipes. The strength of this project consists in evaluating these differences over a broad range of physical conditions, including extreme cases of turbulence, gas-fraction etc. Testing how well the models hold over this variety of cases will also provide strong constraints. One possible outcome of our study could be that none of the existing models decently match the observations in all these physical conditions. This would call for a deep shift of the current paradigm of star formation. In that case, our simulations would be an excellent benchmark to propose a revised theory of this fundamental process.
Our team in Lund has a very strong experience with galaxy and cosmological simulations, some of them run on Tetralith. We will use our previous simulations as a starting point for this project.