Comparative blind test of five planetary transit detection algorithms on realistic synthetic light curves

Abstract

Abstract. Because photometric surveys of exoplanet transits are very promising sources of future discoveries, many algorithms are being developed to detect transit signals in stellar light curves. This paper compares such algorithms for the next generation of space-based transit detection surveys like CoRoT, Kepler, and Eddington. Five independent analyses of a thousand synthetic light curves are presented. The light curves were produced with an end-to-end instrument simulator and include stellar microvariability and a varied sample of stellar and planetary transits diluted within a much larger set of light curves. The results show that different algorithms perform quite differently, with varying degrees of success in detecting real transits and avoiding false positives. We also find that the detection algorithm alone does not make all the difference, as the way the light curves are filtered and detrended beforehand also has a strong impact on the detection limit and on the false alarm rate. The microvariability of sun-like stars is a limiting factor only in extreme cases, when the fluctuation amplitudes are large and the star is faint. In the majority of cases it does not prevent detection of planetary transits. The most sensitive analysis is performed with periodic box-shaped detection filters. False positives are method-dependent, which should allow reduction of their detection rate in real surveys. Background eclipsing binaries are wrongly identified as planetary transits in most cases, a result which confirms that contamination by background stars is the main limiting factor. With parameters simulating the CoRoT mission, our detection test indicates that the smallest detectable planet radius is on the order of 2 Earth radii for a 10-day orbital period planet around a K0 dwarf.

Planetary transit candidates in Corot-IRa01 field

“…Table 1 contains a list of the different institutions involved and the names of the contributors. Some of these methods were presented during a pre-launch performance simulation described in Moutou et al (2005), while others have been or will be developed in separated papers (i.e., Carpano & Fridlund 2008;Renner et al 2008;Régulo et al 2007). The algorithms described in these works are generally based on the following fundamental approaches: correlation with sliding transit template, box-shaped signal search, box-fitting least-squares (BLS), wavelet transformation, or Gaussian fitting of folded light curve.…”

“…-CoRoT light curves are processed and filtered for instrumental noise as described in Drummond et al (2008); -each of the detection teams applies its own algorithms for detrending the signal (e.g., variability, noise) and searching for planetary transits (see Moutou et al 2005Moutou et al , 2007; -the results of each team are combined and each candidate is discussed individually.…”

Planetary transit candidates in CoRoT-LRc01 field

“…Again, each detection team is responsible for constructing and applying its own algorithms. Some of this methods have already been published (Alapini & Aigrain 2008;Bordé et al 2007;Carpano & Fridlund 2008;Moutou et al 2005Moutou et al , 2007Régulo et al 2007;Renner et al 2008) so do not need to be described. We do, however, discuss their performances below (also treated in Barge 2009 andAuvergne et al 2009).…”

Discovery of a cool planet of 5.5 Earth masses through gravitational microlensing

“…Our discovery of such a low-mass planet by gravitational microlensing lends further support to this model, but more detections of similar and lower-mass planets over a wide range of orbits are clearly needed. Planets with separations of ,0.1 AU will be detected routinely by the radial velocity method or space observations of planetary transits in the coming years [24][25][26][27] , but the best chance to increase our understanding of such planets over orbits of 1-10 AU in the next 5-10 years is by future interferometer programs 28 and more advanced microlensing surveys 11,29,30 . …”