Work

A trend filtering algorithm for wide-field variability surveys

Year: 2004
Type: article
Abstract: 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.
Authors: Géza Kovács, Gáspár Bakos, Robert W. Noyes
Language: English
Open Access status: green
OpenAlex ID: W2168799422
FWCI: 2.267
Cites: 13
Cited by: 293
Related to: 10