In this section, we list other data challenges (or blind test) related to exoplanet search.

Roman Space Telescope Exoplanet Data Challenge

The Nancy Grace Roman Space Telescope (formerly known as WFIRST, Wide Field Infrared Survey Telescope), also called Roman Space Telescope (RST) is a 2.4m telescope working in the infrared. The RST is a NASA observatory designed for a 5-year mission, whose launch is foreseen during the mid-2020. The RST Exoplanet Data Challenge aims at looking at several detection techniques (coronagraphy, microlensing...) based on simulated images and data created and provided by the RST consortium.

RST Exoplanet Imaging Data Challenge

Starshade Exoplanet Data Challenge

The Starshade is an external occulter that, similarly to a coronagraph, hides the glaring light of the target star in order to unveil close-in companions. A starshade is a thin layer of material spread over a diameter of about ten meters, with a specific outter "flower-like" shape to avoid spurious diffraction effects (like an apodizer). Therefore the technlogical challenge of starshades is that they must be carefully wrapped on ground and deployed in space. Moreover, the starshade must be located at tens of thousands of kilometers from the telescope, pushing for another technological challenge in the domain of high accuracy formation flight. This Starshade technology is designed, built and tested by NASA and planned to be co-launched with the Roman Space Telescope for a rendez vous within the first years of operation.

Starshade Exoplanet Data Challenge

Interferometry Data Challenge

Every two years, the visible/infrared long baseline interferometry community organizes an Interferometry Imaging Contest. The results are published during the SPIE Astronomical Telescope and Instrumentation bi-yearly conference. The platform used to distribute and store the data is the Optical interferometry Database (OiDB), itself a community service from the Jean-Marie Mariotti Center (JMMC) gathering numerous ressources about astronomical interferometry in the visible/infrared domain. We invite interested participants to subscribe to the Optical Long Baseline Interferometry News (OLBIN) mailing-list to receive news of the on-going contest.

Interferometry Beauty Contest 2018
Interferometry Beauty Contest 2016
Interferometry Beauty Contest 2014
Interferometry Beauty Contest 2012
Interferometry Beauty Contest 2010
Interferometry Beauty Contest 2008
Interferometry Beauty Contest 2006
Interferometry Beauty Contest 2004

ARIEL Data Challenge

ARIEL (Atmospheric Remote-sensing Infrared Exoplanet Large-survey) is a space-based mission whose goal is to analyse exoplanet atmospheres using transmission spectroscopy of a thousand of transiting exoplanets. The ARIEL mission is led by the European Space Agency (ESA) and its launch is forescast for 2029 for a mission duration of four years. The ARIEL community has launched a number of data challenges, based on simulated data, to be ready to optimally exploit the data during the mission time.

ARIEL Data Challenge

Precursor high-contrast imaging data challenge

In 2012, a group of researcher from the HCI community gathered to organize a similar initiative with simulated data of GPI and SPHERE.

Near Campaign at the Very Large Telescope

The NEAR campaign aims to search for low-mass planets around both components of the binary a Centauri, the closest stellar system to Earth. As such, 100-hour of observations were conducted using a dedicated upgrade of the VLT mid-infrared imager VISIR. The NEAR campaign is a collaboration between ESO and the Break-through Initiatives. Here, through the data challenge initiative, we propose to offer access to the NEAR campaign data. As such, anyone has the possibility of applying the best algorithm on these data and therefore taking part in this fascinating adventure: attempting to image the closest planet to Earth.

The NEAR campaign data can be found here. These data are gathered in a serie of .fits files, each consisting of 401x401 images (Primary HDU), and parallactic angle as an ImageHDU.

Compared to the raw data:

For more enquiry about the data or to discuss your results, please contact P. Pathak and M. Kasper