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Several tools have been developed in the past few years for the statistical analysis of the exoplanet search surveys, mostly using a combination of Monte-Carlo simulations or a Bayesian approach.Here we present the Quick-MESS, a grid-based, non-Monte Carlo tool aimed to perform statistical analyses on results from and help with the planning of direct imaging surveys. Quick-MESS uses the (expected) contrast curves for direct imaging surveys to assess for each target the probability that a planet of a given mass and semi-major axis can be detected. By using a grid-based approach Quick-MESS is typically more than an order of magnitude faster than tools based on Monte-Carlo sampling of the planet distribution. In addition, Quick-MESS is extremely flexible, enabling the study of a large range of parameter space for the mass and semi-major axes distributions without the need of re-simulating the planet distribution. In order to show examples of the capabilities of the Quick-MESS, we present the analysis of the Gemini Deep Planet Survey and the predictions for upcoming surveys with extreme-AO instruments.
The Exoplanet Imaging Data Challenge is a community-wide effort meant to offer a platform for a fair and common comparison of image processing methods designed for exoplanet direct detection. For this purpose, it gathers on a dedicated repository (Ze
The solar gravitational lens (SGL) provides a factor of $10^{11}$ amplification for viewing distant point sources beyond our solar system. As such, it may be used for resolved imaging of extended sources, such as exoplanets, not possible otherwise. T
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We present the novel, semi-automated clustering tool ASPECT for analysing voluminous archives of spectra. The heart of the program is a neural network in form of Kohonens self-organizing map. The resulting map is designed as an icon map suitable for