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Supermassive stars as the origin of the multiple populations in globular clusters

Published online by Cambridge University Press:  11 March 2020

Mark Gieles
Affiliation:
ICCUB, Universitat de Barcelona, Martí i Franquès 1, 08028 Barcelona, Spain ICREA, Pg. Lluis Companys 23, 08010 Barcelona, Spain Department of Physics, University of Surrey, Guildford, GU2 7XH, UK
Corinne Charbonnel
Affiliation:
Department of Astronomy, University of Geneva, Chemin des Maillettes 51, 1290, Versoix, Switzerland IRAP, UMR 5277, CNRS and Université de Toulouse, 14, avenue Édouard Belin, 31400 Toulouse, France
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Abstract

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Globular clusters (GCs) display anomalous light-elements abundances (HeCNONaMgAl), resembling the yields of hot-hydrogen burning, but there is no consensus yet on the origin of these ubiquitous multiple populations. We present a model in which a super-massive star (SMS, ≳103 M) forms via stellar collisions during GC formation and pollutes the intra-cluster medium. The growth of the SMS finds a balance with the wind mass loss rate, such that the SMS can produce a significant fraction of the total GC mass in processed material, thereby overcoming the so-called mass-budget problem that plagues other models. Because of continuous rejuvenation, the SMS acts as a ‘conveyer-belt’ of hot-hydrogen burning yields with (relatively) low He abundances, in agreement with empirical constraints. Additionally, the amount of processed material per unit of GC mass correlates with GC mass, addressing the specific mass budget problem. We discuss uncertainties and tests of this new self-enrichment scenario.

Type
Contributed Papers
Copyright
© International Astronomical Union 2020

References

Antonini, F., Gieles, M., & Gualandris, A. 2019, MNRAS, 486, 5008CrossRefGoogle Scholar
Bastian, N. & Lardo, C. 2018, ARAA, 56, 83CrossRefGoogle Scholar
Bonnell, I. A., Bate, M. R., & Zinnecker, H. 1998, MNRAS, 298, 93CrossRefGoogle Scholar
Carretta, E., Bragaglia, A., Gratton, R., et al. 2009a, A&A, 505, 139Google Scholar
Carretta, E., Bragaglia, A., Gratton, R. G., et al. 2009b, A&A, 505, 117Google Scholar
Denissenkov, P. A. & Hartwick, F. D. A. 2014, MNRAS, 437, L21CrossRefGoogle Scholar
Gieles, M., Charbonnel, C., Krause, M. G. H., et al. 2018, MNRAS, 478, 2461CrossRefGoogle Scholar
Haemmerlé, L., Woods, T. E., Klessen, R. S., et al. 2018, MNRAS, 474, 2757CrossRefGoogle Scholar
Li, H., Gnedin, O. Y., Gnedin, N. Y., et al. 2017, ApJ, 834, 69CrossRefGoogle Scholar
Martocchia, S., Cabrera-Ziri, I., Lardo, C., et al. 2018, MNRAS, 473, 2688CrossRefGoogle Scholar
Milone, A. P., Marino, A. F., Dotter, A., et al. 2014, ApJ, 785, 21CrossRefGoogle Scholar
Milone, A. P., Piotto, G., Renzini, A., et al. 2017, MNRAS, 464, 3636CrossRefGoogle Scholar
Milone, A. P., Marino, A. F., Renzini, A., et al. 2018, MNRAS, 481, 5098CrossRefGoogle Scholar
Moeckel, N. & Clarke, C. J. 2011, MNRAS, 410, 2799CrossRefGoogle Scholar
Piotto, G., Milone, A. P., Bedin, L. R., et al. 2015, AJ, 149, 91CrossRefGoogle Scholar
Portegies Zwart, S. F., Baumgardt, H., Hut, P., et al. 2004, Nature, 428, 724CrossRefGoogle Scholar
Prantzos, N., Charbonnel, C., & Iliadis, C. 2017, A&A, 608, A28Google Scholar
Sakurai, Y., Yoshida, N., Fujii, M. S., et al. 2017, MNRAS, 472, 1677CrossRefGoogle Scholar
Smith, L. J., Crowther, P. A., Calzetti, D., et al. 2016, ApJ, 823, 38CrossRefGoogle Scholar
Tremou, E., Strader, J., Chomiuk, L., et al. 2018, ApJ, 862, 16CrossRefGoogle Scholar
Vanzella, E., Calura, F., Meneghetti, M., et al. 2019, MNRAS, 483, 3618CrossRefGoogle Scholar
Zocchi, A., Gieles, M., & Hénault-Brunet, V. 2019, MNRAS, 482, 4713CrossRefGoogle Scholar