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Published June 11, 2016 | Published + Submitted
Journal Article Open

Star formation in a turbulent framework: from giant molecular clouds to protostars

Abstract

Turbulence is thought to be a primary driving force behind the early stages of star formation. In this framework large, self-gravitating, turbulent clouds fragment into smaller clouds which in turn fragment into even smaller ones. At the end of this cascade we find the clouds which collapse into protostars. Following this process is extremely challenging numerically due to the large dynamical range, so in this paper we propose a semi-analytic framework which is able to model star formation from the largest, giant molecular cloud scale, to the final protostellar size scale. Because of the simplicity of the framework it is ideal for theoretical experimentation to explore the principal processes behind different aspects of star formation, at the cost of introducing strong assumptions about the collapse process. The basic version of the model discussed in this paper only contains turbulence, gravity and crude assumptions about feedback; nevertheless it can reproduce the observed core mass function and provide the protostellar system mass function (PSMF), which shows a striking resemblance to the observed initial mass function (IMF), if a non-negligible fraction of gravitational energy goes into turbulence. Furthermore we find that to produce a universal IMF protostellar feedback must be taken into account otherwise the PSMF peak shows a strong dependence on the background temperature.

Additional Information

© 2016 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society. Accepted 2016 March 11. Received 2016 March 4. In original form 2015 July 23. First published online March 15, 2016. We thank Ralf Klessen and Mark Krumholz for their insights and inspirational conversations throughout the development of this work. Support for PFH and DG was provided by an Alfred P. Sloan Research Fellowship, NASA ATP Grant NNX14AH35G and NSF Collaborative Research Grant #1411920 and CAREER grant #1455342. Numerical calculations were run on the Caltech computer cluster 'Zwicky' (NSF MRI award #PHY-0960291) and allocation TGAST130039 granted by the Extreme Science and Engineering Discovery Environment (XSEDE) supported by the NSF.

Attached Files

Published - MNRAS-2016-Guszejnov-9-20.pdf

Submitted - 1507.06678v1.pdf

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September 15, 2023
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