Towards a systematization of the process of detecting Open Star Clusters

Abstract

The classification of stellar objects is a fundamental step in the characterization of star clusters and star-forming regions. Traditional methods are based on empirical criteria defined by thresholds on photometric attributes obtained from catalogs; however, these thresholds vary between different studies, which introduces uncertainty and makes it difficult to consistently identify the different classes of objects. This paper proposes a classification model based on fuzzy set theory that reformulates the binary classification rules used in the literature by means of fuzzy membership functions and aggregation operators. The model allows representing the degree of compatibility of a source to a given class and preserves the knowledge contained in traditional schemes and provides a flexible framework for integrating information from different catalogs. This work constitutes a methodological basis for the development of more robust classification systems and for the subsequent incorporation of classification analysis techniques and characterization of star clusters.