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AI experts called on to join the hunt for exoplanets

Written by  Saturday, 02 July 2022 11:09
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London, UK (SPX) Jul 01, 2022
Artificial Intelligence (AI) experts have been challenged to help a new space mission to investigate Earth's place in the universe. The Ariel Data Challenge 2022, which launches on 30 June, is inviting AI and machine learning experts from industry and academia to help astronomers understand planets outside our solar system, known as exoplanets. Dr Ingo Waldmann, Associate Professor i

Artificial Intelligence (AI) experts have been challenged to help a new space mission to investigate Earth's place in the universe.

The Ariel Data Challenge 2022, which launches on 30 June, is inviting AI and machine learning experts from industry and academia to help astronomers understand planets outside our solar system, known as exoplanets.

Dr Ingo Waldmann, Associate Professor in Astrophysics, UCL (University College London) and Ariel Data Challenge lead said:

"AI has revolutionised many fields of science and industry in the past years. The field of exoplanets has fully arrived in the era of big-data and cutting edge AI is needed to break some of our biggest bottlenecks holding us back."

Understanding our place in the universe
For centuries, astronomers could only glimpse the planets in our solar system but in recent years, thanks to telescopes in space, they have discovered more than 5000 planets orbiting other stars in our galaxy.

The European Space Agency's Ariel telescope will complete one of the largest ever surveys of these planets by observing the atmospheres of around one fifth of the known exoplanets.

Due to the large number of planets in this survey, and the expected complexity the captured observations, Ariel mission scientists are calling for the help of the AI and machine learning community to help interpret the data.

Ariel Data Challenge
Ariel will study the light from each exoplanet's host star after it has travelled through the planet's atmosphere in what is known as a spectrum. The information from these spectra can help scientists investigate the chemical make-up 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 these data. Advanced machine learning techniques could help them to understand the impact of different atmospheric phenomena on the observed spectrum.

The Ariel Data Challenge calls on the AI community to investigate solutions. The competition is open from 30 June to early October.

Participants are free to use any model, algorithm, data pre-processing technique or other tools to provide a solution. They may submit as many solutions as they like and collaborations between teams are welcomed.

For the first time, this year the competition is also offering 20 participants access to High Powered Computing resource through DiRAC, part of the UK's Science and Technology Facilities Council's computing facilities.

Kai Hou (Gordon) Yip, Postdoctoral Research Fellow at UCL and Ariel Data Challenge Lead said:

"With the arrival of next-generation instrumentation, astronomers are struggling to keep up with the complexity and volume of incoming exo-planetary data. The NeurIPS data challenge 2022 provides an excellent platform to facilitate cross-disciplinary solutions with AI experts."

The competition
Winners will be invited to present their solution at the prestigious NeurIPS conference. First prize winning teams will be awarded $2,000 and second prize winners will receive $500.

Winners will also be invited to present their solution to the Ariel consortium.

The competition is supported by the UK Space Agency, European Research Council, European Space Agency and Europlanet Society.

Previous competition
This is the third Ariel Machine Learning Data challenge following successful competitions in 2019 and 2021. The 2021 challenge welcomed 130 participants from across Europe, including entrants from leading academic institutes and AI companies.

This challenge, and its predecessor have taken a bite-sized 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 faced by the mission outright but provides a forum for discussion and to encourage future collaborations.


Related Links
Europlanet
Ariel Data Challenge
Lands Beyond Beyond - extra solar planets - news and science
Life Beyond Earth

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