Self-Organizing Maps. An application to the OGLE data and the Gaia Science Alerts

Details Self-Organizing Maps. An application to the OGLE data and the Gaia Science Alerts Self-Organizing Maps. An application to the OGLE data and the Gaia Science Alerts

2008-11-12

arxiv.org/abs/0811.1808v1

Astronomy and Astrophysics

Astrophysics

Presented as a poster at the "Classification and Discovery in Large Astronomical Surveys" meeting, Ringberg Castle, 14-17 Octo

Scientific paper

10.1063/1.3059046

Self-Organizing Map (SOM) is a promising tool for exploring large multi-dimensional data sets. It is quick and convenient to train in an unsupervised fashion and, as an outcome, it produces natural clusters of data patterns. An example of application of SOM to the new OGLE-III data set is presented along with some preliminary results. Once tested on OGLE data, the SOM technique will also be implemented within the Gaia mission's photometry and spectrometry analysis, in particular, in so-called classification-based Science Alerts. SOM will be used as a basis of this system as the changes in brightness and spectral behaviour of a star can be easily and quickly traced on a map trained in advance with simulated and/or real data from other surveys.

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