Analysing star cluster populations with stochastic models: the HST/WFC3 sample of clusters in M83

TL;DR

This study applies stochastic models to analyze star cluster populations in M83, revealing that accounting for stochastic sampling improves age and mass estimates, and confirms power-law distributions for cluster properties.

Contribution

It introduces a stochastic modeling method for low-mass star clusters, improving age and mass estimates and extending the analysis to lower masses with better resolution.

Findings

Cluster mass distribution follows a power-law with index -2.1.

Age distribution follows a power-law with index -1.0.

Stochastic models yield similar overall distributions as traditional methods, but with improved resolution.

Abstract

The majority of clusters in the Universe have masses well below 10^5 Msun. Hence their integrated fluxes and colors can be affected by the random presence of a few bright stars introduced by stochastic sampling of the stellar mass function. Specific methods are being developed to extend the analysis of cluster SEDs into the low-mass regime. In this paper, we apply such a method to observations of star clusters, in the nearby spiral galaxy M83. We reassess ages and masses of a sample of 1242 objects for which UBVIHalpha fluxes were obtained with the HST/WFC3 images. Synthetic clusters with known properties are used to characterize the limitations of the method. The ensemble of color predictions of the discrete cluster models are in good agreement with the distribution of observed colors. We emphasize the important role of the Halpha data in the assessment of the fraction of young objects, particularly in breaking the age-extinction degeneracy that hampers an analysis based on UBVI only. We find the mass distribution of the cluster sample to follow a power-law of index -2.1 +/-0.2, and the distribution of ages a power-law of index -1.0 +/-0.2 for M > 10^3.5 Msun and ages between 10^7 and 10^9 yr. An extension of our main method, that makes full use of the probability distributions of age and mass of the individual clusters, is explored. It produces similar power-law slopes and will deserve further investigation. Although the properties derived for individual clusters significantly differ from those obtained with traditional, non-stochastic models in ~30% of the objects, the first order aspect of the age and mass distributions are similar to those obtained previously for this M83 sample in the range of overlap of the studies. We extend the power-law description to lower masses with better mass and age resolution and without most of the artifacts produced by the classical method.