Star cluster formation from turbulent clumps. V. Stellar clustering around massive stars
astro-ph.GA, astro-ph.SR
Submitted: 2026-04-30
Updated: 2026-09-08
Comments: Accepted by MNRAS. 23 pages, 12 figures, 4 tables
License: http://creativecommons.org/licenses/by/4.0/
The gist: Massive stars (> 8 M) are known to have high degrees of multiplicity, e.g., with about 60% in triples or higher-order multiples.
Terminology
Abstract
Massive stars (> 8 M) are known to have high degrees of multiplicity, e.g., with about 60% in triples or higher-order multiples. Such high levels of multiplicity may arise during formation (primary multiplicity) or through dynamical processing of already formed stars in dense clusters (secondary multiplicity). The level of primary multiplicity is an important metric to help distinguish between different formation scenarios, such as core accretion and competitive accretion. The level of secondary multiplicity is expected to evolve with time and be sensitive to local cluster environment. Here we analyze a suite of N-body simulations to study bound multiplicity and local projected stellar density, N*, around massive stars within gradually forming star clusters with 50% primordial binaries in the Turbulent Clump Core Accretion (TCCA) paradigm. We find that massive stars rapidly gather triple or higher-order bound companions and enhancements in local N* via dynamical processes. We study these metrics as a function of environment in a given cluster, quantifying the increasing multiplicity that arises towards cluster centers. We find that secondary multiplicity tends to decrease in more massive clusters due to their higher velocity dispersions, but rises as the mean density of the bound cluster increases. We find our N* radial profiles are shallower compared to those in the STARFORGE simulations, which form massive stars via competitive accretion. A comparison to the AFGL 5180 system suggests it is better described by TCCA models. However, a larger number of observed systems is needed to better discriminate between these formation models.
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