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The NeurIPS - Ariel Data Challenge 2024, hosted on Kaggle, invites participants to develop innovative algorithms to analyse this exoplanetary atmospheric data. The challenge focuses on improving techniques for interpreting observations from the upcoming ESA Ariel mission. Participants will work with synthetic data generated to simulate real observations, providing a unique opportunity to contribute to cutting-edge exoplanet research.
I am responsible for generating the synthetic data used in this challenge, ensuring it accurately represents the kind of information expected from the ESA Ariel mission.
The discovery of exoplanets—planets orbiting stars other than our Sun—has significantly altered our understanding of the cosmos, questioning Earth's uniqueness and the potential for life elsewhere. To date, over 5,600 exoplanets have been identified. However, detection is just the beginning; understanding and characterising these planets through atmospheric studies is crucial. The ESA Ariel Mission, set for 2029, will be the first to conduct a comprehensive study of 1,000 exoplanets in our galactic vicinity.
Analysing exoplanetary atmospheres is among the most challenging tasks in contemporary astronomy. When an exoplanet transits its host star, a minute fraction of the starlight (50–200 photons per million) passes through the planet's atmosphere, interacting with its chemical components, clouds, and winds. These faint signals, ranging from 50ppm for Super-Earths to 200ppm for Jupiter-like planets, are often obscured by instrumental noise.
The task of this competition is to extract atmospheric spectra from these observations, including an estimate of their uncertainty levels. Participants must detrend a series of sequential 2D images of the spectral focal plane taken during several hours of exoplanet observation as it eclipses its star. This detrending process is essential for extracting accurate atmospheric spectra and their error bars from raw data, a common prerequisite for any modern astronomical instrument before scientific analysis can proceed.
Participation and Prizes
Participation and Prizes
The competition is open to data scientists, researchers, and enthusiasts worldwide. It offers substantial prizes to reward the best solutions, motivating participants to push the boundaries of current exoplanetary data analysis techniques. Specific details about the prizes, including amounts and distribution, can be found on the competition page.
By participating in the Ariel Data Challenge 2024, you will be contributing to a pioneering mission in exoplanet research and helping to unlock the secrets of distant worlds. Join us in this exciting endeavour to advance our understanding of the universe.
About NeurIPS
About NeurIPS
The challenge is part of the NeurIPS 2024 competitions, showcasing advancements in AI and machine learning. NeurIPS (Neural Information Processing Systems) is a prestigious conference that brings together researchers and practitioners to discuss breakthroughs and applications in AI. The Thirty-eighth Annual Conference on Neural Information Processing Systems will be held at the Vancouver Convention Center from Monday, December 9 through Sunday, December 15.
About Kaggle
About Kaggle
Kaggle is the world's largest data science and machine learning community, with over 8 million registered users. It provides a collaborative environment for data scientists to explore and analyse datasets, build models, and compete in challenges. Being hosted on Kaggle offers significant visibility and credibility to the Ariel Data Challenge, attracting top talent from around the globe and fostering high-quality contributions. Kaggle competitions have been a launchpad for many innovative solutions in the data science field, making our challenge's presence on this platform a major endorsement and a tremendous opportunity for widespread participation and impact
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