Project description
Machine learning could aid direct exoplanet observations
Characterising the physical and chemical properties of rocky exoplanets orbiting in the habitable zone of nearby stars is one of the most compelling quests in modern astrophysics. Although exoplanets can be directly observed, this method works best for those that emit infrared light and are far from the glare of the star; otherwise, the huge contrast and minute angular separation between the exoplanet and the host star make the former vanish. The EU-funded EPIC project plans to use high-contrast infrared imaging on ground-based telescopes. The project's activities will include the development of optical imaging tools that can reduce the blinding glare of the host stars and the use of state-of-the-art machine learning techniques for image processing.
Objective
One of the most ambitious goals of modern astrophysics is to characterise the physical and chemical properties of rocky planets orbiting in the habitable zone of nearby Sun-like stars. Although the observation of planetary transits could in a few limited cases be used to reach such a goal, it is widely recognised that only direct imaging techniques will enable such a feat on a statistically significant sample of planetary systems. Direct imaging of Earth-like exoplanets is however a formidable challenge due to the huge contrast and minute angular separation between such planets and their host star. The proposed EPIC project aims to enable the direct detection and characterisation of terrestrial planets located in the habitable zone of nearby stars using ground-based high-contrast imaging in the thermal infrared domain. To reach that ambitious goal, the project will focus on two main research directions: (i) the development and implementation of high-contrast imaging techniques and technologies addressing the smallest possible angular separations from bright, nearby stars, and (ii) the adaptation of state-of-the-art machine learning techniques to the problem of image processing in high-contrast imaging. While the ultimate goal of this research can likely only be reached with the advent of giant telescopes such as the Extremely Large Telescope (ELT) around 2025, the EPIC project will lay the stepping stones towards that goal and produce several high-impact results along the way, e.g. by re-assessing the occurrence rate of giant planets in direct imaging surveys at the most relevant angular separations (i.e. close to the snow line), by conducting the deepest high-contrast imaging search for rocky planets in the alpha Centauri system, by preparing the scientific exploitation of the ELT, and by providing the first open-source high-contrast image processing toolbox relying on supervised machine learning techniques.
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: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences physical sciences astronomy astrophysics
- natural sciences physical sciences astronomy planetary sciences planets exoplanetology
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-COG - Consolidator Grant
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2018-COG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
4000 LIEGE
Belgium
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.