The velocity distribution of nearby stars from Hipparcos data I. The significance of the moving groups
Jo Bovy (NYU), David W. Hogg (NYU, MPIA), Sam T. Roweis (Toronto,, Google)

TL;DR
This study reconstructs the 3D velocity distribution of nearby stars using Hipparcos data, finding limited evidence for new structures beyond known moving groups, and emphasizes the importance of radial velocity data for understanding stellar kinematics.
Contribution
It introduces a maximum likelihood density estimation method for reconstructing velocity distributions from incomplete data, validated with external and internal tests.
Findings
Limited evidence for new velocity structures beyond known groups.
Radial velocity measurements significantly enhance information about stellar velocities.
The method effectively accounts for individual measurement errors and missing data.
Abstract
We present a three-dimensional reconstruction of the velocity distribution of nearby stars (<~ 100 pc) using a maximum likelihood density estimation technique applied to the two-dimensional tangential velocities of stars. The underlying distribution is modeled as a mixture of Gaussian components. The algorithm reconstructs the error-deconvolved distribution function, even when the individual stars have unique error and missing-data properties. We apply this technique to the tangential velocity measurements from a kinematically unbiased sample of 11,865 main sequence stars observed by the Hipparcos satellite. We explore various methods for validating the complexity of the resulting velocity distribution function, including criteria based on Bayesian model selection and how accurately our reconstruction predicts the radial velocities of a sample of stars from the Geneva-Copenhagen survey…
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