Automated data analysis - algorithms for Gaia Cepheids

Details Automated data analysis - algorithms for Gaia Cepheids Automated data analysis - algorithms for Gaia Cepheids

Mar 2010

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010jphcs.218a2026t&link_type=abstract

Journal of Physics: Conference Series, Volume 218, Issue 1, pp. 012026 (2010).

Physics

Scientific paper

Gaia space astrometric mission, to be launched in 2012, is expected to provide a bulk of data observing a thousand million objects within its five year time-span. Due to its scanning law the all sky will be covered, and all the available objects will be observed repeatedly with a moderate time sampling, therefore Gaia will obtain a large amount of photometric data that carry valuable information on a wide range of variability phenomena.
The Gaia group of the Konkoly Observatory works on the preparation of automated characterisation algorithms of pre-classified Cepheid type sources within the Variability Processing group of Gaia.
Gaia is expected to provide observational data on all available objects with a number of data points gradually increasing during the mission. Based on the scanning law a moderate number of data points per source are expected. That, though makes the processing necessarily to be fine tuned, is sufficient for the characterisation including determination of period(s), Fourier parameters, possible period changes, and hints on binarity. Therefore we use for testing public and unpublished data sources that are comparable to those expected from Gaia in term of sampling combined with simulated Gaia measurements. Depending on the phase coverage ground based supplementary observations may be needed to improve the accuracy of the results.
The final product of this work will be a contribution to the Gaia database, that will be compiled primarily based on the Gaia on-board measurements, and probably include a number of newly discovered Cepheids. This work may lead to an improved knowledge of the nature of these objects, that are fundamental to approach a more precise cosmic distance scale.

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