Validating Open Cluster Candidates with Photometric Bayesian Evidence

Fuente: arXiv
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Main Authors: Li, Lu, Li, Zhaozhou, Shao, Zhengyi
Format: Preprint
Published: 2025
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author Li, Lu
Li, Zhaozhou
Shao, Zhengyi
author_facet Li, Lu
Li, Zhaozhou
Shao, Zhengyi
contents The thousands of open cluster (OC) candidates identified by the Gaia mission are significantly contaminated by false positives from field star fluctuations, posing a major validation challenge. Based on the Mixture Model for OCs (MiMO), we present a Bayesian framework for validating OC candidates in the color--magnitude diagram. The method compares the Bayesian evidence of two competing models: a single stellar population with field contamination versus a pure field population. Their ratio, the Bayes factor (BF), quantifies the statistical support for cluster existence. Tests on confirmed clusters and random fields show that a threshold of BF > 100 effectively distinguishes genuine clusters from chance field overdensities. This approach provides a robust, quantitative tool for OC validation and catalog refinement. The framework is extendable to multi-dimensional validation incorporating kinematics and is broadly applicable to other resolved stellar systems, including candidate moving groups, stellar streams, and dwarf satellites.
format Preprint
id arxiv_https___arxiv_org_abs_2510_23375
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Validating Open Cluster Candidates with Photometric Bayesian Evidence
Li, Lu
Li, Zhaozhou
Shao, Zhengyi
Astrophysics of Galaxies
The thousands of open cluster (OC) candidates identified by the Gaia mission are significantly contaminated by false positives from field star fluctuations, posing a major validation challenge. Based on the Mixture Model for OCs (MiMO), we present a Bayesian framework for validating OC candidates in the color--magnitude diagram. The method compares the Bayesian evidence of two competing models: a single stellar population with field contamination versus a pure field population. Their ratio, the Bayes factor (BF), quantifies the statistical support for cluster existence. Tests on confirmed clusters and random fields show that a threshold of BF > 100 effectively distinguishes genuine clusters from chance field overdensities. This approach provides a robust, quantitative tool for OC validation and catalog refinement. The framework is extendable to multi-dimensional validation incorporating kinematics and is broadly applicable to other resolved stellar systems, including candidate moving groups, stellar streams, and dwarf satellites.
title Validating Open Cluster Candidates with Photometric Bayesian Evidence
topic Astrophysics of Galaxies
url https://arxiv.org/abs/2510.23375