Bayesian assessment of moving group membership: importance of models and prior knowledge

TL;DR

This paper improves Bayesian models for identifying young moving group members, specifically in the beta-Pictoris group, by updating member lists and distribution functions, leading to the confirmation of 57 bona fide members and 17 probable ones.

Contribution

It introduces three key model improvements for Bayesian moving group membership assessments and demonstrates their effectiveness in confirming and identifying members.

Findings

Confirmed 57 bona fide members of BPMG, including 12 new ones.

Suggested 17 additional probable members based on improved models.

Showed that comprehensive model updates enhance membership accuracy.

Abstract

Young nearby moving groups are important and useful in many fields of astronomy such as studying exoplanets, low-mass stars, and the stellar evolution of the early planetary systems over tens of millions of years, which has led to intensive searches for their members. Identification of members depends on the used models sensitively, therefore, careful examination of the models is required. In this study, we investigate the effects of the models used in moving group membership calculations based on a Bayesian framework (e.g., BANYAN II) focusing on the beta-Pictoris moving group (BPMG). Three improvements for building models are suggested: (1) updating a list of accepted members by re-assessing memberships in terms of position, motion, and age, (2) investigating member distribution functions in $XYZ$, and (3) exploring field star distribution functions in $XYZ$ and $UVW$. The effect of each change is investigated, and we suggest using all of these improvements simultaneously in future membership probability calculations. Using this improved MG membership calculation and the careful examination of the age, 57 bona fide members of BPMG are confirmed including 12 new members. We additionally suggest 17 highly probable members.