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Data Mining in Astronomical Photo Plate Archives

Astronomical surveys, e.g. the photo plate based Sky Patrol of Sonneberg or the ongoing Gaia observations, yield data of huge amount of stars beyond any individual and manual analysis. Modern data mining methods are necessary to classify the objects of these surveys. The example shows the classification of RR Lyrae variables from the OGLE-III survey.

Example: Classification of LMC RR–Lyrae variables

Classification of LMC RR–Lyrae variables in fundamental and first overtone pulsators, OGLE-III
C. Dersch
Classification of LMC RR–Lyrae variables in fundamental and first overtone pulsators, OGLE-III

Classification of RR–Lyrae variables from the Large Magellanic Cloud (LMC) in fundamental and first overtone pulsators, data from the OGLE-III survey

Light curves from photo plates usually are more noisy than CCD data and are not taken with high cadence. However, they may cover a much longer time range. The challenge of their analysis using data mining methods is the determination of good quality parameters for classification. The goals are

  • study of long term properties of variable stars
  • detection of transient phenomena, e.g. flares, novae, etc.