Do you have experience with AI? If so, you could help scientists learn more about exoplanets
Artificial intelligence (AI) experts have been called upon to support a new space mission to investigate Earth’s place in the universe. The Ariel Data Challenge 2022, which began on June 30, asks professionals with expertise in artificial intelligence and machine learning to help astronomers understand exoplanets, or planets outside our solar system. Dr. Ingo Waldmann, Associate Professor of Astrophysics, UCL (University College London) and head of the Ariel Data Challenge said: “Artificial intelligence has revolutionized many areas of science and industry in recent years. The exoplanet field has fully entered the era of big data, and cutting edge artificial intelligence is needed to break some of the biggest bottlenecks holding us back.” Ariel will be placed in orbit around the Lagrange Point 2 (L2), a point of gravitational balance 1.5 million kilometers beyond Earth’s orbit around the Sun. Credit: ESA/STFC RAL Space/UCL/Europlanet-Science Office
Understanding our place in the universe
Astronomers could only see the planets in our solar system for many years, but in recent years, thanks to space telescopes, scientists have found more than 5000 planets orbiting other stars in our galaxy. By studying the atmospheres of nearly a fifth of known exoplanets, the European Space Agency’s Ariel telescope will complete one of the largest surveys of these worlds ever. Ariel mission scientists are asking the artificial intelligence and machine learning community to help interpret the data due to the sheer number of planets in this survey and the expected complexity of the observations.
Ariel Data Challenge
Ariel will study the light from each exoplanet’s host star after it has traveled through the planet’s atmosphere in what is known as a spectrum. Information from these spectra can help scientists investigate the chemical composition of the planet’s atmosphere and discover more about these planets and how they formed. Scientists involved in the Ariel mission need a new method to interpret this data. Advanced machine learning techniques could help them understand the impact of different atmospheric phenomena on the observed spectrum. Artist’s impression of Ariel. Credit: ESA/STFC RAL Space/UCL/UK Space Agency/ATG Medialab The Ariel Data Challenge invites the AI community to explore solutions. The competition is open from June 30 to early October. Participants are free to use any model, algorithm, data preprocessing technique or other tools to provide a solution. They can submit as many solutions as they want, and cross-team collaborations are welcome. For the first time, this year the competition also offers 20 entrants access to High Performance Computing resources through DiRAC, part of the UK Science and Technology Facilities Council’s computing facilities. Kai Hou (Gordon) Yip, Postdoctoral Researcher at UCL and the head of the Ariel Data Challenge said: “With the arrival of next-generation instruments, astronomers are struggling to keep up with the complexity and volume of incoming exoplanetary data. The NeurIPS 2022 data challenge provides an excellent platform to facilitate interdisciplinary solutions with AI experts.”
The competition
Winners will be invited to present their solutions at the prestigious NeurIPS conference. First prize winning teams will receive $2,000 and second prize winners will receive $500. Winners will also be invited to present their solutions to the Ariel consortium. The competition is supported by the UK Space Agency, the European Research Council, the European Space Agency and Europlanet.
Previous competition
This is the third Ariel Machine Learning Data Challenge after successful competitions in 2019 and 2021. The 2021 challenge welcomed 130 participants from across Europe, including participants from leading academic institutions and AI companies. This challenge and its predecessor have taken a small aspect of a larger problem to help make exoplanet research more accessible to the machine learning community. The challenge is not designed to solve the data analysis issues facing the mission, but to provide a forum for discussion and to encourage future collaborations. More details about the competition and how to enter can be found on the Ariel Data Challenge website.
