Prof Suzanne Aigrain

Abstract:

Aims. As an extension of a previous work, we present a comparison of four methods of filtering solar-like variability to increase the efficiency of detection of Earth-like planetary transits by means of box-shaped transit finder algorithms. Two of these filtering methods are the harmonic fitting method and the iterative nonlinear filter that, coupled respectively with the box least-square (BLS) and box maximum likelihood algorithms, demonstrated the best performance during the first detection blind test organised inside the CoRoT consortium. The third method, the 3-spot model, is a simplified physical model of Sun-like variability and the fourth is a simple sliding boxcar filter.Methods. We apply a Monte Carlo approach by simulating a large number of 150-day light curves (as for CoRoT long runs) for different planetary radii, orbital periods, epochs of the first transit, and standard deviations of the photon shot noise. Stellar variability is given by the total solar irradiance variations as observed close to the maximum of solar cycle 23. After filtering solar variability, transits are searched for by means of the BLS algorithm.Results. We find that the iterative nonlinear filter is the best method for filtering light curves of solar-like stars when a suitable window can be chosen. As the performance of this filter depends critically on the length of its window, we point out that the window must be as long as possible, according to the magnetic activity level of the star. We show an automatic method to choose the extension of the filter window from the power spectrum of the light curves.Conclusions. The iterative nonlinear filter, when used with a suitable choice of its window, has a better performance than more complicated and computationally intensive methods of fitting solar-like variability, like the 200-harmonic fitting or the 3-spot model. © 2009 ESO.

Abstract:

The detrending algorithms which are widely used to reduce the impact of stellar variability on space-based transit surveys are ill-suited for estimating the parameters of confirmed planets, as they unavoidably alter the transit signal. We present a post-detection detrending algorithm, which filters out signal on other time-scales than the period of the transit while preserving the transit signal. We compare the performance of this new filter to a well-established pre-detection detrending algorithm, by applying both to a set of 20 simulated light curves containing planetary transits, stellar variability and instrumental noise as expected for the CoRoT space mission, and performing analytic fits to the transits. Compared to the pre-detection benchmark, the new post-detection filter systematically yields significantly reduced errors (median reduction in relative error over our sample ∼40 per cent) on the planet-to-star-radius ratio, system scale and impact parameter. This is particularly important for active stars, where errors induced by variability can otherwise dominate the final error budget on the planet parameters. Aside from improving planet parameter estimates, the new filter preserves all signal at the orbital period of the planet, and thus could also be used to search for light reflected by the planet. © 2009 RAS.