Multi-wavelength characterization of VVVX open clusters

¹ Instituto de Astronomía, Universidad Católica del Norte, Av. Angamos 0610, Antofagasta, Chile
² ESO – European Southern Observatory, Alonso de Cordova 3107, Vitacura, Santiago, Chile
³ Instituto de Astrofísica, Depto. de Ciencias Fisicas, Facultad de Ciencias Exactas, Universidad Andrés Bello, Av. Fernández Concha 700, Las Condes, Santiago, Chile
⁴ Vatican Observatory, V00120 Vatican City State, Italy
⁵ Observatorio Astronómico, Universidad Nacional de Córdoba, Laprida 854, X5000BGR Córdoba, Argentina
⁶ Instituto de Astronomía Teórica y Experimental (CONICET-UNC), Laprida 854, X5000BGR Córdoba, Argentina
⁷ Departamento de Matemática, Facultad de Ingeniería, Universidad de Atacama, Copiapó, Chile

^★ Corresponding authors; casmir.obasi@ucn.cl; jose.fernandez@ucn.cl

Received: 29 November 2024
Accepted: 17 February 2025

Abstract

Context. With the rise of large surveys across wavelengths, both supervised and unsupervised machine learning algorithms have increasingly aided in detecting large samples of old open clusters in high-extinction regions of the Milky Way bulge and disk.

Aims. Our primary goal is to confirm or discard automatically detected open clusters from poorly studied, heavily contaminated regions of the Milky Way. Cleaning these samples is critical for reconstructing the Galactic disk’s star formation history and understanding the thin and thick disk formation model.

Methods. We used data from the VVVX, 2MASS, and Gaia DR3 surveys to confirm and characterize nine open cluster candidates: BH118, BH 144, Schuster-MWSC 1756, Saurer 3, FSR 1521, Saurer 2, Haffner 10-FSR 1231, Juchert 12, and Pismis 3. We constructed density maps and vector–proper motion diagrams to analyse the targets and performed photometric analysis to derive their main physical parameters.

Results. We examined cluster images from the 2MASS, WISE, and DECaPS surveys, identifying star clusters through an over-density of stars. This was confirmed with a VVVX photometry density map and validated using Gaussian kernel density estimation. Using Gaia proper motion data, we refined cluster memberships and decontaminated the data to build the final cluster catalogue with objects with a high probability of being star cluster members. We derived the following parameters: extinction values (A_Ks) ranging from 0.07±0.03 to 0.50±0.04; colour excess values (E(J-K_s)) from 0.16±0.03 to 0.60±0.03; distances (D) from 2.19±0.06 kpc to 8.94±0.06 kpc; Galactocentric distances (R_G) from 7.82 kpc to 15.08 kpc; vertical distance component values (Z) from −0.09 kpc to 0.34 kpc; and tangential velocities (V_T) from 30.59 km/s to 245.42 km/s. We also computed ages and metallicities by fitting PARSEC isochrones, finding ages (t) ranging from 20 Myr to 5 Gyr and metallicities ([Fe/H]) from −0.5 to 0.5. Structural parameters include core radii (r_c) from 0.71′ to 5.21′, tidal radii (r_t) from 3.4′ to 12.0′, and concentration indices (c) from 0.36 to 0.83.

Conclusions. We photometrically confirm the open cluster nature for the nine targets in our compilation and updated their main physical parameters.