The Youngest Star Clusters in the Large Magellanic Cloud

Abstract

This study presents a comprehensive analysis of the youngest stellar clusters in the Large Magellanic Cloud (LMC), utilising a multi-wavelength approach. We analyse data spanning from infrared to ultraviolet wavelengths, with the goal of enhancing our understanding of these clusters' physical properties, such as age, mass, and size. Our methodology includes a novel cluster detection procedure; it employs machine learning techniques for the accurate identification of these young clusters. The Markov Chain Monte Carlo analysis, using the Automated Stellar Cluster Analysis tool, plays a crucial role in deriving the clusters' key physical parameters. Our findings provide significant insights into the early stages of stellar and galactic evolution, particularly in dwarf galaxy environments, and contribute to the broader understanding of star formation and cluster evolution. For the 109 clusters in our sample younger than 5 Myr, we measure a positive correlation between cluster mass and the mass of the most massive star in the cluster. This study emphasises the importance of multi-wavelength observations in revealing the intricate properties of young stellar clusters.