# Astrophysical properties of star clusters in the Magellanic Clouds homogeneously estimated by $\texttt{ASteCA}$

## TL;DR

This paper presents a homogeneous catalog of astrophysical parameters for 239 star clusters in the Magellanic Clouds, derived using the automated ASteCA tool, enabling reproducible and statistically robust analysis of their properties.

## Contribution

The study introduces a fully automated, reproducible method for estimating fundamental cluster parameters from photometric data, applied to a large Magellanic Clouds cluster sample.

## Key findings

- Generated a consistent catalog of cluster parameters including metallicity, age, reddening, distance, and mass.
- Performed detailed error analysis and comparison with previous studies.
- Analyzed the age-metallicity relationship in the Magellanic Clouds.

## Abstract

Aims. To produce an homogeneous catalog of astrophysical parameters of 239 resolved star clusters located in the Small and Large Magellanic Clouds, observed in the Washington photometric system. Methods. The cluster sample was processed with the recently introduced Automated Stellar Cluster Analysis ($\texttt{ASteCA}$) package, which ensures both an automatized and a fully reproducible treatment, together with a statistically based analysis of their fundamental parameters and associated uncertainties. The fundamental parameters determined with this tool for each cluster, via a color-magnitude diagram (CMD) analysis, are: metallicity, age, reddening, distance modulus, and total mass. Results. We generated an homogeneous catalog of structural and fundamental parameters for the studied cluster sample, and performed a detailed internal error analysis along with a thorough comparison with values taken from twenty-six published articles. We studied the distribution of cluster fundamental parameters in both Clouds, and obtained their age-metallicity relationships. Conclusions. The $\texttt{ASteCA}$ package can be applied to an unsupervised determination of fundamental cluster parameters; a task of increasing relevance as more data becomes available through upcoming surveys.