A Naive Bayes Source Classifier for X-ray Sources

TL;DR

This paper introduces a naive Bayes classifier to determine the membership of X-ray sources in the Carina star-forming region, effectively distinguishing stars from contaminants using multi-wavelength data.

Contribution

It presents a novel application of naive Bayes classification to X-ray source data for membership determination in a complex star-forming region.

Findings

75% of sources classified as members

11% identified as contaminants

14% remain unclassified

Abstract

The Chandra Carina Complex Project (CCCP) provides a sensitive X-ray survey of a nearby starburst region over >1 square degree in extent. Thousands of faint X-ray sources are found, many concentrated into rich young stellar clusters. However, significant contamination from unrelated Galactic and extragalactic sources is present in the X-ray catalog. We describe the use of a naive Bayes classifier to assign membership probabilities to individual sources, based on source location, X-ray properties, and visual/infrared properties. For the particular membership decision rule adopted, 75% of CCCP sources are classified as members, 11% are classified as contaminants, and 14% remain unclassified. The resulting sample of stars likely to be Carina members is used in several other studies, which appear in a Special Issue of the ApJS devoted to the CCCP.