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Register a new userThe SARS algorithm: detrending CoRoT light curves with Sysrem using simultaneous external parameters
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Surveys for exoplanetary transits are usually limited not by photon noise but rather by the amount of red noise in their data. In particular, although the CoRoT spacebased survey data are being carefully scrutinized, significant new sources of systematic noises are still being discovered. Recently, a magnitude-dependant systematic effect was discovered in the CoRoT data by Mazeh & Guterman et al. and a phenomenological correction was proposed. Here we tie the observed effect a particular type of effect, and in the process generalize the popular Sysrem algorithm to include external parameters in a simultaneous solution with the unknown effects. We show that a post-processing scheme based on this algorithm performs well and indeed allows for the detection of new transit-like signals that were not previously detected.
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The CoRoT space mission was operating for almost 6 years, producing thousands of continuous photometric light curves. The temporal series of exposures are processed by the production pipeline, correcting the data for known instrumental effects. But even after these model-based corrections, some collective trends are still visible in the light curves. We propose here a simple exposure-based algorithm to remove instrumental effects. The effect of each exposure is a function of only two instrumental stellar parameters, position on the CCD and photometric aperture. The effect is not a function of the stellar flux, and therefore much more robust. As an example, we show that the $sim2%$ long-term variation of the early run LRc01 is nicely detrended on average. This systematics removal process is part of the CoRoT legacy data pipeline.
When a planet occults a spotty area on a stellar surface, the flux increases and a characteristic feature in a light curve - a bump - is observed. Among the planets detected by the CoRoT-mission CoRoT-18 is especially interesting as it exhibited spot crossings that we have analysed in detail. We used four ground-based observations obtained at a 1.5-m telescope in Spain and the 13 available CoRoT-transits to refine and constrain stellar, planetary and geometrical parameters of the system. We found that the derived physical properties slightly deviate from the previously published values, most likely due to the different treatment of the stellar activity. Following a spot over several transits enabled us to measure the stellar rotation period and the spin-orbit alignment. Our derived values of Prot=5.19 +/- 0.03 d and Lambda=6 +/- 13 deg are in agreement with the literature values that were obtained with other methods. Although we cannot exclude a very old age for CoRoT-18, our observations support the young star hypothesis and, hence, yield constraints on the time-scale of planet formation and migration.
We present K2SC (K2 Systematics Correction), a Python pipeline to model instrumental systematics and astrophysical variability in light curves from the K2 mission. K2SC uses Gaussian process regression to model position-dependent systematics and time-dependent variability simultaneously, enabling the user to remove both (e.g., for transit searches) or to remove systematics while preserving variability (for variability studies). For periodic variables, K2SC automatically computes estimates of the period, amplitude and evolution timescale of the variability. We apply K2SC to publicly available K2 data from campaigns 3--5, showing that we obtain photometric precision approaching that of the original Kepler mission. We compare our results to other publicly available K2 pipelines, showing that we obtain similar or better results, on average. We use transit injection and recovery tests to evaluate the impact of K2SC on planetary transit searches in K2 PDC (Pre-search Data Conditioning) data, for planet-to-star radius ratios down Rp/Rstar = 0.01 and periods up to P = 40 d, and show that K2SC significantly improves the ability to distinguish between correct and false detections, particularly for small planets. K2SC can be run automatically on many light curves, or manually tailored for specific objects such as pulsating stars or large amplitude eclipsing binaries. It can be run on ASCII and FITS light curve files, regardless of their origin. Both the code and the processed light curves are publicly available, and we provide instructions for downloading and using them. The methodology used by K2SC will be applicable to future transit search missions such as TESS and PLATO.
We present the first case in which the BEER algorithm identified a hot Jupiter in the Kepler light curve, and its reality was confirmed by orbital solutions based on follow-up spectroscopy. The companion Kepler-76b was identified by the BEER algorithm, which detected the BEaming (sometimes called Doppler boosting) effect together with the Ellipsoidal and Reflection/emission modulations (BEER), at an orbital period of 1.54 days, suggesting a planetary companion orbiting the 13.3 mag F star. Further investigation revealed that this star appeared in the Kepler eclipsing binary catalog with estimated primary and secondary eclipse depths of 5e-3 and 1e-4 respectively. Spectroscopic radial-velocity follow-up observations with TRES and SOPHIE confirmed Kepler-76b as a transiting 2.0+/-0.26 Mjup hot Jupiter. The mass of a transiting planet can be estimated from either the beaming or the ellipsoidal amplitude. The ellipsoidal-based mass estimate of Kepler-76b is consistent with the spectroscopically measured mass while the beaming-based estimate is significantly inflated. We explain this apparent discrepancy as evidence for the superrotation phenomenon, which involves eastward displacement of the hottest atmospheric spot of a tidally-locked planet by an equatorial super-rotating jet stream. This phenomenon was previously observed only for HD 189733b in the infrared. We show that a phase shift of 10.3+/-2.0 degrees of the planet reflection/emission modulation, due to superrotation, explains the apparently inflated beaming modulation, resolving the ellipsoidal/beaming amplitude discrepancy. Kepler-76b is one of very few confirmed planets in the Kepler light curves that show BEER modulations and the first to show superrotation evidence in the Kepler band. Its discovery illustrates for the first time the ability of the BEER algorithm to detect short-period planets and brown dwarfs.
We present a matched-filter based algorithm for transit detection and its application to simulated COROT light curves. This algorithm stems from the work by Borde, Rouan & Leger (2003). We describe the different steps we intend to take to discriminate between planets and stellar companions using the three photometric bands provided by COROT. These steps include the search for secondary transits, the search for ellipsoidal variability, and the study of transit chromaticity. We also discuss the performance of this approach in the context of blind tests organized inside the COROT exoplanet consortium.
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