Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-23T10:18:32.612Z Has data issue: false hasContentIssue false
  • English
  • Français

A comprehensive tool for the statistical comparison of Large Surveys to Models of the Galaxy

Published online by Cambridge University Press:  06 January 2014

Andreas Ritter
Andreas Ritter*
Affiliation:
Graduate Department of Astronomy, National Central University, 300 Zhongda Rd., Jhongli City, 325 Taoyuan County, Taiwan, email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The advent of large spectroscopic surveys of the Galaxy offers the possibility to compare Galactic models to actual measurements for the first time. I have developed a tool for the comprehensive comparison of any large data set to the predictions made by models of the Galaxy using sophisticated statistical methods, and to visualise the results for any given direction. This enables us to point out systematic differences between the model and the measurements, as well as to identify new (sub-)structures in the Galaxy. These results can then be used to improve the models, which in turn will allow us to find even more substructures like stellar streams, moving groups, or clusters. In this paper I show the potential of this tool by applying it to the RAdial Velocity Experiment (RAVE, Steinmetz 2003) and the Besançon model of the Galaxy Robin et al. 2003.

Keywords

methods: statisticalsurveysstars: statisticsGalaxy: kinematics and dynamicsGalaxy: stellar contentGalaxy: structure
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 9 , Symposium S298: Setting the scene for Gaia and LAMOST , May 2013 , pp. 92 - 97
Copyright
Copyright © International Astronomical Union 2014 

References

Coşkunoǧlu, B., et al. 2011, MNRAS, 412, 1237Google Scholar
Robin, A. C., Reylé, C., Derriére, S., & Picaud, S. 2003, A&A, 409, 523Google Scholar
Seabroke, G. M. 2007, PhD thesis, University of CambridgeGoogle Scholar
Siebert, A., et al. 2011, AJ, 141, 187Google Scholar
Steinmetz, M. 2003, ASP Conference Series, 298, 381Google Scholar
Williams, M. E. K., et al. 2011, ApJ, 728, 102Google Scholar