Project description
Analysis tools for Euclid’s rare astronomical object discoveries
Euclid, an ESA space telescope set to launch in July 2023, will study dark energy and dark matter by mapping over one-third of the sky. Its data will help explore galaxy formation, the co-evolution of galaxies and black holes, and the discovery of rare astronomical objects. However, existing tools may not be sufficient to fully use this valuable data. The EU-funded ELSA project will develop advanced tools and algorithms to enhance the spectroscopic analysis of faint and rare galaxies observed by Euclid. By leveraging state-of-the-art machine learning, complemented by citizen science, the project will handle high-dimensional data to uncover underlying physical processes. This effort requires dedicated computing resources and collaboration with leading experts in galaxy evolution.
Objective
Euclid is an ESA space telescope launching in July 2023, designed to understand the nature of dark energy and dark matter. To achieve this, Euclid will observe over a third of the sky with high resolution imaging and spectroscopy, which will establish “the” reference map of the extra-galactic celestial sphere for decades to come. The giant archive produced will be a goldmine to study the history of the formation and growth of galaxies over the age of the Universe, driving answers to many fundamental science questions on the co-evolution of galaxies and supermassive black holes, the interaction between stars, gas, and galactic nuclei in galaxies at cosmic noon, and excelling in the discovery of rare objects including gravitational lenses. However, the richest gold veins are also the most difficult to exploit: the tools developed for Euclid’s primary science will not be enough to open the rich legacy for the astronomical community. We therefore propose ELSA to explore new methodologies and create cutting-edge pipelines, tools and algorithms. Our ambitious goal is to push the boundaries of spectroscopic analysis to the limits, uncovering hidden details of even the faintest and rarest galaxies measured by Euclid. We will leverage state of the art machine learning to efficiently handle the high-dimensional data and reveal the underlying physical processes they encode. This will need dedicated computing resources and highly motivated researchers versed in the most advanced techniques, that will work with our team of leading experts in the field of galaxy evolution to reveal the treasures preserved in the Euclid vault. Our machine learning will be supplemented by citizen science, enormously extending the reach of ELSA’s impact. ELSA will be a forge of knowledge and advanced tools that will not be confined within the boundaries of our teams, but shared with the whole scientific community and beyond to foster new projects and unforeseen discoveries.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
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HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
40126 Bologna
Italy