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Bayesian Inference of Kinematics and Mass Segregation of Open Cluster

  • Z. Shao (a1), X. Xie (a1), L. Chen (a1), J. Zhong (a1), J. Hou (a1) and C-C. Lin (a1)...

Abstract

Based on the Bayesian Inference (BI) method, the Mixture-Model approach is improved to combine all kinematic data, including the coordinative position( $\vec{x}$ ), proper motion ( $\vec{\mu}$ ) and radial velocity(v), to separate the motion of the cluster from field stars, as well as to determine the intrinsic kinematic status and dynamical effects of the cluster, such as the mass segregation, anisotropy etc.. Meanwhile, the membership probability of individual stars are estimated as by product results. This method has been testified by simulation of toy models and also successfully used for well studied open clusters, such as M67 and NGC188. It is expected to largely help the studies of open clusters while combine the coming GAIA data.

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Copyright

References

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Feroz, F. & Hobson, M. P. 2008, MNRAS, 384, 449
Geller, A. M., Mathieu, R. D., Harris, H. C., & McClure, R. D. 2008, AJ, 135, 2264
Platais, I., Kozhurina-Platais, V., Mathieu, R. D., Girard, T. M., et al. 2003, AJ, 126, 2922
Shao, Z. & Zhao, J. 1996, Acta Astronomica Sinica 37 377. (ChAA, 1997, 21, 254)
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Keywords

Bayesian Inference of Kinematics and Mass Segregation of Open Cluster

  • Z. Shao (a1), X. Xie (a1), L. Chen (a1), J. Zhong (a1), J. Hou (a1) and C-C. Lin (a1)...

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