paper

SIEGE III: The formation of dense stellar clusters in sub-parsec resolution cosmological simulations with individual star feedback

arXiv:2411.02502 · doi:10.1051/0004-6361/202452876

Abstract

Star clusters stand at the crossroads between galaxies and single stars. Resolving the formation of star clusters in cosmological simulations represents an ambitious and challenging goal, since modelling their internal properties requires very high resolution. This paper is the third of a series within the SImulating the Environment where Globular clusters Emerged (SIEGE) project, where we conduct zoom-in cosmological simulations with sub-parsec resolution that include the feedback of individual stars, aimed to model the formation of star clusters in high-redshift proto-galaxies. We investigate the role of three fundamental quantities in shaping the intrinsic properties of star clusters, i. e., i) pre-supernova stellar feedback (continuous or instantaneous ejection of mass and energy through stellar winds); ii) star formation efficiency, defined as the fraction of gas converted into stars per freefall time, for which we test 2 different values (epsi_ff=0.1 and 1), and iii) stellar initial mass function (IMF, standard vs top-heavy). All our simulations are run down to z=10.5, which is sufficient for investigating some structural properties of the emerging clumps and clusters. [Abridged] The prescription for a continuous, low-intensity feedback, along with the adoption of epsi_ff=1, produces star clusters with maximum stellar density values up to 10^4 M_sun pc^(-2), in good agreement with the surface density-size relation observed in local young star clusters (YSCs). Therefore, a realistic stellar wind description and a high star formation effiency are the key ingredients that allow us to achieve realistic star clusters characterised by properties comparable to those of local YSCs. In contrast, the other models produce too diffuse clusters, in particular the one with a top-heavy IMF.

A&A, accepted. 20 pages, 14 figures

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