Galactic properties that favour star cluster formation: a statistical view

TL;DR

This study uses Bayesian models to analyze how galaxy properties like star formation rate influence the likelihood and mass of star cluster formation, revealing higher efficiency at earlier cosmic times.

Contribution

It introduces Bayesian logistic and hurdle models to quantify galaxy factors affecting star cluster formation, a novel approach in this context.

Findings

Star formation rate is the best predictor for cluster presence and mass.

Cluster formation was more efficient at higher redshifts.

Galaxies with higher gas content favored star cluster formation.

Abstract

The presence or absence of star clusters in galaxies, and the properties of star cluster populations compared to their host galaxy properties, are important observables for validating models of cluster formation, galaxy formation, and galaxy assembly. In this work, we apply a Bayesian approach to fit two models to data from surveys of young clusters in star forming galaxies. The first model is a logistic regression, which allows us to include galaxies which do not have any young clusters. The second model is a hurdle model, which includes galaxies with zero clusters and also incorporates information about the total mass in the cluster system. We investigate two predictors (star formation rate and total stellar mass in the galaxy) and look at clusters younger than 10 or 100 Myr. We find that in all cases, star formation rate is the better predictor for both the probability of hosting clusters and the total mass in the cluster system. We compare our results to similar models for old globular clusters, and conclude that star cluster formation was more abundant and more efficient at higher redshifts, likely because of the high gas content of galaxies at that time.