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Published September 2021 | Published + Accepted Version
Journal Article Open

A model for the formation of stellar associations and clusters from giant molecular clouds

Abstract

We present a large suite of magnetohydrodynamic simulations of turbulent, star-forming giant molecular clouds (GMCs) with stellar feedback, extending previous work by simulating 10 different random realizations for each point in the parameter space of cloud mass and size. It is found that once the clouds disperse due to stellar feedback, both self-gravitating star clusters and unbound stars generally remain, which arise from the same underlying continuum of substructured stellar density, i.e. the hierarchical cluster formation scenario. The fraction of stars that are born within gravitationally bound star clusters is related to the overall cloud star formation efficiency set by stellar feedback, but has significant scatter due to stochastic variations in the small-scale details of the star-forming gas flow. We use our numerical results to calibrate a model for mapping the bulk properties (mass, size, and metallicity) of self-gravitating GMCs on to the star cluster populations they form, expressed statistically in terms of cloud-level distributions. Synthesizing cluster catalogues from an observed GMC catalogue in M83, we find that this model predicts initial star cluster masses and sizes that are in good agreement with observations, using only standard IMF and stellar evolution models as inputs for feedback. Within our model, the ratio of the strength of gravity to stellar feedback is the key parameter setting the masses of star clusters, and of the various feedback channels direct stellar radiation (photon momentum and photoionization) is the most important on GMC scales.

Additional Information

© 2021 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model). Accepted 2021 June 24. Received 2021 June 24; in original form 2020 August 10. Published: 05 July 2021. We thank Erik Rosolowsky and Mark Krumholz for useful discussions and for providing data and analysis code from Freeman et al. (2017) and Krumholz et al. (2019) respectively. We thank the referee for helpful feedback that improved the manuscript. We thank Charles Lada, Anna Rosen, Hui Li, Mark Vogelsberger, Bruce Elmegreen, Angela Adamo, Eve Ostriker, Jeong-Gyu Kim, Marta Reina-Campos, and Sebastian Trujillo-Gomez for enlightening discussions that informed and motivated this work. Support for MYG was provided by a CIERA Postdoctoral Fellowship. Support for PFH was provided by an Alfred P. Sloan Foundation Research Fellowship, NSF Collaborative Research grant #1715847 and CAREER grant #1455342, and NASA grants NNX15AT06G,JPL 1589742, and 17-ATP17-0214. CAFG was supported by NSF through grants AST-1412836,AST-1517491, AST-1715216, and CAREER award AST-1652522, by NASA through grant NNX15AB22G, and by a Cottrell Scholar Award from the Research Corporation for Science Advancement. JMDK gratefully acknowledges funding from the German Research Foundation (DFG) in the form of an Emmy Noether Research Group (grant number KR4801/1-1) and the DFG Sachbeihilfe (grant number KR4801/2-1), as well as from the European Research Council (ERC) under the European Union's Horizon 2020 Framework Programme via the ERC Starting Grant MUSTANG (grant agreement number 714907). MBK acknowledges support from NSF CAREER award AST-1752913, NSF grant AST-1910346, NASA grant NNX17AG29G, and HST-AR-15006, HST-AR-15809, HST-GO-15658, HST-GO-15901, and HST-GO-15902 from the Space Telescope Science Institute, which is operated by AURA, Inc., under NASA contract NAS5-26555. This research was undertaken, in part, thanks to funding from the Canada Research Chairs program. Numerical calculations were run on the Caltech compute cluster 'Wheeler,' allocations from XSEDE TG-AST130039 and PRAC NSF.1713353 (awards OCI-0725070 and ACI-1238993) supported by the NSF, and NASA HEC SMD-16-7592. This research has made use of use of NASA's Astrophysics Data System, ipython (Pérez & Granger 2007), numpy, scipy (Jones et al. 2001), and matplotlib (Hunter 2007). Data Availability: The data supporting the plots within this article are available on reasonable request to the corresponding author. A public version of the GIZMO code is available at http://www.tapir.caltech.edu/~phopkins/Site/GIZMO.html.

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Additional details

Created:
August 20, 2023
Modified:
October 23, 2023