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Formation sites of Population III star formation: The effects of different levels of rotation and turbulence on the fragmentation behavior of primordial gas

Wollenberg, Katharina M. J., Glover, Simon C. O., Clark, Paul C. and Klessen, Ralf S. 2020. Formation sites of Population III star formation: The effects of different levels of rotation and turbulence on the fragmentation behavior of primordial gas. Monthly Notices of the Royal Astronomical Society 10.1093/mnras/staa289/5721520

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Abstract

We use the moving-mesh code arepo to investigate the effects of different levels of rotation and turbulence on the fragmentation of primordial gas and the formation of Population III stars. We consider 9 different combinations of turbulence and rotation and carry out 5 different realizations of each setup, yielding one of the largest sets of simulations of Population III star formation ever performed. We find that fragmentation in Population III star-forming systems is a highly chaotic process and show that the outcomes of individual realizations of the same initial conditions often vary significantly. However, some general trends are apparent. Increasing the turbulent energy promotes fragmentation, while increasing the rotational energy inhibits fragmentation. Within the ∼1000 yr period that we simulate, runs including turbulence yield flat protostellar mass functions while purely rotational runs show a more top-heavy distribution. The masses of the individual protostars are distributed over a wide range from a few 10−3 M⊙ to several tens of M⊙. The total mass growth rate of the stellar systems remains high throughout the simulations and depends only weakly on the degree of rotation and turbulence. Mergers between protostars are common, but predictions of the merger fraction are highly sensitive to the criterion used to decide whether two protostars should merge. Previous studies of Population III star formation have often considered only one realization per set of initial conditions. However, our results demonstrate that robust trends can only be reliably identified by considering averages over a larger sample of runs.

Item Type: Article
Date Type: Published Online
Status: In Press
Schools: Physics and Astronomy
Advanced Research Computing @ Cardiff (ARCCA)
Publisher: Oxford University Press
ISSN: 0035-8711
Date of First Compliant Deposit: 31 January 2020
Date of Acceptance: 27 January 2020
Last Modified: 25 Apr 2020 17:00
URI: http://orca-mwe.cf.ac.uk/id/eprint/129243

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