Embedded clusters: upgrading visual and infrared photometric analysis with Gaia DR2 and ASteCA

TL;DR

This paper enhances the analysis of embedded star clusters by integrating deep optical and infrared photometry with Gaia DR2 data, using the ASteCA tool for automatic parameter determination.

Contribution

It introduces a method combining multi-band photometry, Gaia data, and ASteCA for precise characterization of embedded clusters, a novel approach in this context.

Findings

Accurate distances and properties for five embedded clusters.

Effective integration of optical, infrared, and Gaia data.

Automated analysis with ASteCA improves cluster parameter estimation.

Abstract

Embedded clusters are groups of stars which have not dispersed yet the residual of the parental cloud where they were born so getting precise distances and properties of these groups turns out to be an essential task. We present results for five embedded clusters: [DBS2003]5, [DBS2003]60, [DBS2003]98, [DBS2003]116 and [DBS2003]117. Results come from a combination of deep CCD UBVI photometry suitable to identify blue faint stars and infrared information from available surveys. In turn photometry was linked with proper motions and parallaxes from Gaia DR2. Each object was treated in a multi-space using ASteCA, a code especially designed to perform an automatic data analysis and aimed at providing the fundamental parameters of star groups, in case they compose a real entity.