Does God play dice with star clusters?

TL;DR

This study compares stochastic sampling of stellar masses with physical models using simulations, revealing that while stochastic models approximate final cluster properties, they do not accurately reflect the formation process.

Contribution

It demonstrates that stochastic sampling does not capture the formation sequence of stars but can approximate final cluster demographics if the correct IMF is used.

Findings

Simulated IMF has a sharp truncation at ~28 solar masses.

Massive stars tend to start accreting earlier and finish later.

Stochastic sampling matches final cluster properties with known IMF.

Abstract

When a detailed model of a stellar population is unavailable, it is most common to assume that stellar masses are independently and identically distributed according to some distribution: the universal initial mass function (IMF). However, stellar masses resulting from causal, long-ranged physics cannot be truly random and independent, and the IMF may vary with environment. To compare stochastic sampling with a physical model, we run a suite of 100 STARFORGE radiation magnetohydrodynamics simulations of low-mass star cluster formation in $2000M_\odot$ clouds that form $\sim 200$ stars each on average. The stacked IMF from the simulated clouds has a sharp truncation at $\sim 28 M_\odot$, well below the typically-assumed maximum stellar mass $M_{\rm up} \sim 100-150M_\odot$ and the total cluster mass. The sequence of star formation is not totally random: massive stars tend to start accreting sooner and finish later than the average star. However, final cluster properties such as maximum stellar mass and total luminosity have a similar amount of cloud-to-cloud scatter to random sampling. Therefore stochastic sampling does not generally model the stellar demographics of a star cluster as it is forming, but may describe the end result fairly well, if the correct IMF -- and its environment-dependent upper cutoff -- are known.