Difference image analysis: The interplay between the photometric scale factor and systematic photometric errors

Context: Understanding the source of systematic errors in photometry is essential for their calibration. Aims: We investigate how photometry performed on difference images can be influenced by errors in the photometric scale factor. Methods: We explore the equations for difference image analysis (DIA) and we derive an expression describing how errors in the difference flux, the photometric scale factor and the reference flux are propagated to the object photometry. Results: We find that the error in the photometric scale factor is important, and while a few studies have shown that it can be at a significant level, it is currently neglected by the vast majority of photometric surveys employing DIA. Conclusions: Minimising the error in the photometric scale factor, or compensating for it in a post-calibration model, is crucial for reducing the systematic errors in DIA photometry.Comment: Accepted A&

A massive exoplanet candidate around KOI-13: Independent confirmation by ellipsoidal variations

We present an analysis of the KOI-13.01 candidate exoplanet system included in the September 2011 Kepler data release. The host star is a known and relatively bright $(m_{\rm KP} = 9.95)$ visual binary with a separation significantly smaller (0.8 arcsec) than the size of a Kepler pixel (4 arcsec per pixel). The Kepler light curve shows both primary and secondary eclipses, as well as significant out-of-eclipse light curve variations. We confirm that the transit occurs round the brighter of the two stars. We model the relative contributions from (i) thermal emission from the companion, (ii) planetary reflected light, (iii) Doppler beaming, and (iv) ellipsoidal variations in the host-star arising from the tidal distortion of the host star by its companion. Our analysis, based on the light curve alone, enables us to constrain the mass of the KOI-13.01 companion to be $M_{\rm C} = 8.3 \pm 1.25M_{\rm J}$ and thus demonstrates that the transiting companion is a planet (rather than a brown dwarf which was recently proposed by \cite{b7}). The high temperature of the host star (Spectral Type A5-7V, $T_{\rm eff} = 8511-8020$ K), combined with the proximity of its companion KOI-13.01, may make it one of the hottest exoplanets known, with a detectable thermal contribution to the light curve even in the Kepler optical passband. However, the single passband of the Kepler light curve does not enable us to unambiguously distinguish between the thermal and reflected components of the planetary emission. Infrared observations may help to break the degeneracy, while radial velocity follow-up with $\sigma \sim$ 100 m s$^{-1}$ precision should confirm the mass of the planet.Comment: 7 pages, 5 figure

An algorithm for correcting CoRoT raw light curves

We introduce the CoRoT detrend algorithm (CDA) for detrending CoRoT stellar light curves. The algorithm CDA has the capability to remove random jumps and systematic trends encountered in typical CoRoT data in a fully automatic fashion. Since enormous jumps in flux can destroy the information content of a light curve, such an algorithm is essential. From a study of 1030 light curves in the CoRoT IRa01 field, we developed three simple assumptions which upon CDA is based. We describe the algorithm analytically and provide some examples of how it works. We demonstrate the functionality of the algorithm in the cases of CoRoT0102702789, CoRoT0102874481, CoRoT0102741994, and CoRoT0102729260. Using CDA in the specific case of CoRoT0102729260, we detect a candidate exoplanet around the host star of spectral type G5, which remains undetected in the raw light curve, and estimate the planetary parameters to be Rp=6.27Re and P=1.6986 days.Comment: 8 pages, 13 figure

Global stellar variability study in the field-of-view of the Kepler satellite

We present the results of an automated variability analysis of the Kepler public data measured in the first quarter (Q1) of the mission. In total, about 150 000 light curves have been analysed to detect stellar variability, and to identify new members of known variability classes. We also focus on the detection of variables present in eclipsing binary systems, given the important constraints on stellar fundamental parameters they can provide. The methodology we use here is based on the automated variability classification pipeline which was previously developed for and applied successfully to the CoRoT exofield database and to the limited subset of a few thousand Kepler asteroseismology light curves. We use a Fourier decomposition of the light curves to describe their variability behaviour and use the resulting parameters to perform a supervised classification. Several improvements have been made, including a separate extractor method to detect the presence of eclipses when other variability is present in the light curves. We also included two new variability classes compared to previous work: variables showing signs of rotational modulation and of activity. Statistics are given on the number of variables and the number of good candidates per class. A comparison is made with results obtained for the CoRoT exoplanet data. We present some special discoveries, including variable stars in eclipsing binary systems. Many new candidate non-radial pulsators are found, mainly Delta Sct and Gamma Dor stars. We have studied those samples in more detail by using 2MASS colours. The full classification results are made available as an online catalogue.Comment: 15 pages, 5 figures, Accepted for publication in Astronomy and Astrophysics on 09/02/201

Characterizing Transiting Extrasolar Planets with Narrow-Band Photometry and GTC/OSIRIS

We report the first extrasolar planet observations from the 10.4-m Gran Telescopio Canarias (GTC), currently the world's largest, fully steerable, single-aperture optical telescope. We used the OSIRIS tunable filter imager on the GTC to acquire high-precision, narrow-band photometry of the transits of the giant exoplanets, TrES-2b and TrES-3b. We obtained near-simultaneous observations in two near-infrared (NIR) wavebands (790.2 and 794.4 +/- 2.0 nm) specifically chosen to avoid water vapor absorption and skyglow so as to minimize the atmospheric effects that often limit the precision of ground-based photometry. Our results demonstrate a very-high photometric precision with minimal atmospheric contamination despite relatively poor atmospheric conditions and some technical problems with the telescope. We find the photometric precision for the TrES-2 observations to be 0.343 and 0.412 mmag for the 790.2 and 794.4 nm light curves, and the precision of the TrES-3 observations was found to be 0.470 and 0.424 mmag for the 790.2 and 794.4 nm light curves. We also discuss how future follow-up observations of transiting planets with this novel technique can contribute to the characterization of Neptune- and super-Earth-size planets to be discovered by space-based missions like CoRoT and Kepler, as well as measure atmospheric properties of giant planets, such as the strength of atmospheric absorption features.Comment: 9 pages, including 3 figures and 2 tables; accepted for publication in MNRA

Difference image analysis : automatic kernel design using information criteria

This publication was made possible by NPRP grant # X-019-1-006 from the Qatar National Research Fund (a member of Qatar Foundation).We present a selection of methods for automatically constructing an optimal kernel model for difference image analysis which require very few external parameters to control the kernel design. Each method consists of two components; namely, a kernel design algorithm to generate a set of candidate kernel models, and a model selection criterion to select the simplest kernel model from the candidate models that provides a sufficiently good fit to the target image. We restricted our attention to the case of solving for a spatially invariant convolution kernel composed of delta basis functions, and we considered 19 different kernel solution methods including six employing kernel regularization. We tested these kernel solution methods by performing a comprehensive set of image simulations and investigating how their performance in terms of model error, fit quality, and photometric accuracy depends on the properties of the reference and target images. We find that the irregular kernel design algorithm employing unregularized delta basis functions, combined with either the Akaike or Takeuchi information criterion, is the best kernel solution method in terms of photometric accuracy. Our results are validated by tests performed on two independent sets of real data. Finally, we provide some important recommendations for software implementations of difference image analysis.Publisher PDFPeer reviewe