Observing sites at the East-Antarctic plateau are considered to provide exceptional conditions for astronomy. The aim of this work is to assess its potential for detecting transiting extrasolar planets through a comparison and combination of photomet
ric data from Antarctica with time series from a midlatitude site. During 2010, the two small aperture telescopes ASTEP 400 (Dome C) and BEST II (Chile) together performed an observing campaign of two target fields and the transiting planet WASP-18b. For the latter, a bright star, Dome C appears to yield an advantageous signal-to-noise ratio. For field surveys, both Dome C and Chile appear to be of comparable photometric quality. However, within two weeks, observations at Dome C yield a transit detection efficiency that typically requires a whole observing season in Chile. For the first time, data from Antarctica and Chile have been combined to extent the observational duty cycle. This approach is both feasible in practice and favorable for transit search, as it increases the detection yield by 12-18%.
The CoRoT field LRa02 has been observed with the Berlin Exoplanet Search Telescope II (BEST II) during the southern summer 2007/2008. A first analysis of stellar variability led to the publication of 345 newly discovered variable stars. Now, a deeper
analysis of this data set was used to optimize the variability search procedure. Several methods and parameters have been tested in order to improve the selection process compared to the widely used J index for variability ranking. This paper describes an empirical approach to treat systematic trends in photometric data based upon the analysis of variance statistics that can significantly decrease the rate of false detections. Finally, the process of reanalysis and method improvement has virtually doubled the number of variable stars compared to the first analysis by Kabath et al. A supplementary catalog of 272 previously unknown periodic variables plus 52 stars with suspected variability is presented. Improved ephemerides are given for 19 known variables in the field. In addition, the BEST II results are compared with CoRoT data and its automatic variability classification.
