The Ariel Data Challenge 2023 launched on 14 April and invites AI and machine learning experts to help astronomers in understanding planets outside our solar system.
. This is a huge number of observations, representing around a sixth of all the 6,000 or so currently known worlds in the exoplanet catalog, and the help of the AI and machine learning community could be vital in interpreting the Ariel data.
The ESA space telescope works by studying light from an exoplanet's host star after it has filtered through that planet's atmosphere. Because chemical elements absorb and emit light at set wavelengths, looking at the spectra of theafter passing through exoplanet atmospheres can reveal what said atmospheres are made of. This in turn could reveal how the planet in question formed and whether they could host life.
But, scientists behind Ariel will need a new method of interpreting this data to better understand the impact of different atmospheric phenomena on the observed spectrum of light. The fourth Ariel Data Challenge follows on from previous events in 2019, 2021, and 2022 will close on June 18, 2023. The Challenge asks computing experts using any model, algorithm, or data processing technique to come up with solutions to this problem.
Not only can the experts taking part submit as many potential solutions as they come up with, but they can also join forces and collaborate with other teams. Through the challenge, participants are offered access to the High Powered Computing resources through DiRAC, part of the U.K's Science and Technology Facilities Council's computing facilities.
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