Hot Stellar Populations of Berkeley 39 using Swift/UVOT

TL;DR

This study uses Swift/UVOT data and machine learning to identify and characterize blue straggler stars in the old open cluster Berkeley 39, revealing potential hot companions through spectral energy distribution analysis.

Contribution

It introduces a novel application of machine learning for cluster membership and detailed spectral analysis of blue stragglers in Berkeley 39.

Findings

Identification of 861 cluster members including 17 blue stragglers

Detection of UV excess in one blue straggler suggesting a hot companion

Comprehensive spectral energy distributions for blue stragglers

Abstract

Open clusters are excellent tools to probe the history of the Galactic disk and properties of star formation. In this work, we present a study of an old age open cluster Berkley 39 using the observations from UVOT instrument of the Neil Gehrels Swift observatory. Making use of a machine learning algorithm, ML-MOC, we have identified a total of 861 stars as cluster members out of which 17 are blue straggler stars. In this work, we present a characterisation of 2 blue straggler stars. To estimate the fundamental parameters of blue straggler stars and their companions (if any), we constructed spectral energy distributions using UV data from swift/UVOT and GALEX, optical data from Gaia DR3, and infrared (IR) data from 2MASS, Spitzer/IRAC, and WISE. We find excess flux in UV in one blue straggler star, implying the possibility of a hot companion.