Multi-Dimensional Bayesian Membership Analysis of the Sco OB2 moving Group

TL;DR

This paper introduces a Bayesian method for identifying members of the Sco OB2 association using astrometric and radial velocity data, resulting in a new high-mass membership list and insights into the group's spatial mixing.

Contribution

A novel Bayesian membership analysis method that does not distinguish subgroups and incorporates linear models for probability calculation.

Findings

Identified 436 members, including 88 new ones.

Included classical non-members as new members.

Showed the association is well mixed over 8-degree sky distances.

Abstract

We present a new high-mass membership of the nearby Sco OB2 association based on HIPPARCOS positions, proper motions and parallaxes and radial velocities taken from the Kharchenko et al. (2007) catalogue. The Bayesian membership selection method developed makes no distinction between subgroups of Sco OB2 and utilises linear models in calculation of membership probabilities. We select 436 members, 88 of which are new members not included in previous membership selections. We include the classical non members Alpha-Cru and Beta-Cru as new members as well as the pre-main-sequence stars HIP 79080 and 79081. We also show that the association is well mixed over distances of 8 degrees on the sky, and hence no determination can be made as to the formation process of the entire association.