A trend filtering algorithm for wide-field variability surveys

Géza Kovács, Gáspár Bakos, Robert W. Noyes

Research output: Contribution to journalReview articlepeer-review

254 Scopus citations


We show that various systematics related to certain instrumental effects and data reduction anomalies in wide-field variability surveys can be efficiently corrected by a trend filtering algorithm (TFA) applied to the photometric time-series produced by standard data pipelines. Statistical tests, performed on the data base of the HAT Network project, show that by the application of this filtering method the cumulative detection probability of periodic transits increases by up to 0.4 for variables brighter than 11 mag, with a trend of increasing efficiency toward brighter magnitudes. We also show that the TFA can be used for the reconstruction of periodic signals by iteratively filtering out systematic distortions.

Original languageEnglish (US)
Pages (from-to)557-567
Number of pages11
JournalMonthly Notices of the Royal Astronomical Society
Issue number2
StatePublished - Jan 11 2005
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science


  • Methods: data analysis
  • Planetary systems
  • Stars: variables: other
  • Surveys


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