Issue |
A&A
Volume 551, March 2013
|
|
---|---|---|
Article Number | A9 | |
Number of page(s) | 7 | |
Section | Galactic structure, stellar clusters and populations | |
DOI | https://doi.org/10.1051/0004-6361/201220430 | |
Published online | 08 February 2013 |
Maximum likelihood estimation of local stellar kinematics
Lund Observatory, Lund University, PO Box 43, 22100 Lund, Sweden
e-mail: toktam.aghajani@gmail.com, Lennart.Lindegren@astro.lu.se
Received: 21 September 2012
Accepted: 28 November 2012
Context. Kinematical data such as the mean velocities and velocity dispersions of stellar samples are useful tools to study galactic structure and evolution. However, observational data are often incomplete (e.g., lacking the radial component of the motion) and may have significant observational errors. For example, the majority of faint stars observed with Gaia will not have their radial velocities measured.
Aims. Our aim is to formulate and test a new maximum likelihood approach to estimating the kinematical parameters for a local stellar sample when only the transverse velocities are known (from parallaxes and proper motions).
Methods. Numerical simulations using synthetically generated data as well as real data (based on the Geneva-Copenhagen survey) are used to investigate the statistical properties (bias, precision) of the method, and to compare its performance with the much simpler “projection method” described by Dehnen & Binney (1998, MNRAS, 298, 387).
Results. The maximum likelihood method gives more correct estimates of the dispersion when observational errors are important, and guarantees a positive-definite dispersion matrix, which is not always obtained with the projection method. Possible extensions and improvements of the method are discussed.
Key words: methods: numerical / methods: analytical / astrometry
© ESO, 2013
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.