A trend filtering algorithm for wide-field variability surveys

By G. Kovacs, Gáspár Á. Bakos, R. W. Noyes. 2004

264 citations recorded by the source corpus.

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.

Subfields: Astronomy and Astrophysics, Control and Systems Engineering

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Citations in the corpus

A SYSTEMATIC SEARCH FOR TRANSITING PLANETS IN THE K2 DATA (2015, methodology): “Other datadriven approaches have been developed and applied to the Kepler data (for example, Stumpe et al. 2012; Smith et al. 2012; Roberts et al. 2013; Wang et al. 2015) and ground-based surveys (for example, Kovács et al. 2005) but they have yet to be generalized to K2.”
HAT-P-16b: A 4 MJ PLANET TRANSITING A BRIGHT STAR ON AN ECCENTRIC ORBIT, (2010, methodology): “The resulting light curves were decorrelated (cleaned of trends) using the External Parameter Decorrelation technique in “constant” mode (EPD; see Bakos et al. 2009) and the Trend Filtering Algorithm (TFA; see Kovács et al. 2005).”
The SARS algorithm: detrending CoRoT light curves with Sysrem using simultaneous external parameters (2010, background): “• Bright stars both make planetary transits easier to detect, and are more susceptible to relative effects (that are later corrected by Sysrem/TFA (Kovács et al. 2005) /other).”
Transits and Occultations (2010, methodology): “Major efforts were made to automate the observations, and to develop algorithms for precise wide-field photometry (Tamuz et al. 2005, Kovács et al. 2005) and transit detection (Kovács et al. 2002).”
HATSouth: A Global Network of Fully Automated Identical Wide-Field Telescopes (2012, methodology): “The current reduction procedure, after application of the Trend Filtering Algorithm (TFA Kovács et al. 2005), yields light curves reaching 6mmag r.m.s. at 240 s cadence at around the saturation limit.”
HAT-P-11b: A SUPER-NEPTUNE PLANET TRANSITING A BRIGHT K STAR IN THE KEPLER FIELD (2009, methodology): “The two basic methods we have employed are the External Parameter Decorrelation (EPD) technique, briefly described earlier in Bakos et al. (2007b), and the Trend Filtering Algorithm (TFA; Kovács et al. 2005).”
A PHOTOMETRIC VARIABILITY SURVEY OF FIELD K AND M DWARF STARS WITH HATNet (2009, methodology): “We note that for the analysis in this paper we do not use the signal-reconstruction mode TFA presented by Kovács et al. (2005).”
DISCOVERY OF A TRANSITING PLANET AND EIGHT ECLIPSING BINARIES IN HATNet FIELD G205 (2009, background): “Some of these trends were not understood, and our intense effort to suppress them led to the development of the Trend Filtering Algorithm (TFA; Kovács et al. 2005).”
HAT-P-7b: An Extremely Hot Massive Planet Transiting a Bright Star in the Kepler Field (2008, methodology): “We note that TFA was run in signal reconstruction mode, i.e. systematics were iteratively filtered out from the observed time series assuming that the underlying signal is a trapezeshaped transit (see Kovács et al. 2005, for additional details).”
TRANSIT DETECTION IN THE MEarth SURVEY OF NEARBY M DWARFS: BRIDGING THE CLEAN-FIRST, SEARCH-LATER DIVIDE (2012, methodology): “A brief side note: cleaning methods like TFA or EPD can be run in a “reconstructive mode,” in which they fit away systematics (Kovács et al. 2005) and/or variability (Kovacs & Bakos 2008) towards a known signal present in the data.”
The XO Project: Searching for Transiting Extrasolar Planet Candidates (2005, methodology): “We use a robust average as described previously, but a possible enhancement would be to use a weighted average as described by Kovács et al. (2005).”