The possibility of determining open-cluster parameters from BVRI photometry

TL;DR

This paper presents a new automated method for determining open-cluster parameters using only BVRI photometry, achieving high accuracy without relying on U-band data or subjective visual fitting.

Contribution

The authors develop a global optimization-based isochrone fitting tool that reduces subjectivity and accurately recovers cluster parameters from BVRI photometry alone.

Findings

Method recovers synthetic cluster parameters with less than 10% error.

Results for observed clusters agree with previous literature.

Applicable to a wide range of ages, distances, and reddening values.

Abstract

In the last decades we witnessed an increase in studies of open clusters of the Galaxy, especially because of the good determination for a wide range of values of parameters such as age, distance, reddening, and proper motion. The reliable determination of the parameters strongly depends on the photometry available and especially on the U filter, which is used to obtain the color excess E(B-V) through the color-color diagram (U-B) by (B-V) by fitting a zero age main-sequence. Owing to the difficulty of performing photometry in the U band, many authors have tried to obtain E(B-V) without the filter. But because of the near linearity of the color-color diagrams that use the other bands, combined with the fact that most fitting procedures are highly subjective (many done "by eye") the reliability of those results has always been questioned. Our group has recently developed, a tool that performs isochrone fitting in open-cluster photometric data with a global optimization algorithm, which removes the need to visually perform the fits and thus removes most of the related subjectivity. Here we apply our method to a set of synthetic clusters and two observed open clusters (Trumpler 1 and Melotte 105) using only photometry for the BVRI bands. Our results show that, considering the cluster structural variance caused only by photometric and Poisson sampling errors, our method is able to recover the synthetic cluster parameters with errors of less than 10% for a wide range of ages, distances, and reddening, which clearly demonstrates its potential. The results obtained for Trumpler 1 and Melotte 105 also agree well with previous literature values.