14. How to hunt for an asteroid - with JWST.

     

    ESA supervisor: Pablo Gomez
    Collaborator(s): Sandor Kruk, Anthony Marston, Jan Reerink

    Site: ESAC

    While the main scientific objectives of missions such as the Hubble Space Telescope (HST), Euclid or the James Webb Space Telescope (JWST) do not primarily focus on capturing images of solar system objects (SSOs), these objects often appear incidentally in the foreground of other observations. In previous research (Racero et al. 2022), we have introduced techniques to cross-reference the orbits of existing asteroids in the Minor Planet Center database, the most extensive database of SSOs, with archival observations from some ESA science missions. Additionally, we have developed AI and crowdsourcing-based methods to identify over one thousand asteroids appearing serendipitously in HST images (Kruk et al. 2022), while in JWST archival images we have visually identified the smallest asteroid in the Main Belt (Mueller et al. 2023). As the data volume archived at the ESAC Science Data Center from these observatories continues to expand, there is a growing demand for innovative tools capable of systematically searching these archives for asteroids. The objective of this traineeship is to adapt existing techniques and develop new ones to detect serendiptous Solar System Objects appearing in public archival JWST images using the ESA Datalabs platform.

    Project duration: 6 months.

    Desirable expertise or programming language:

    • Programming experience in Python  
    • Interest and experience in data mining is a plus 

     

    To apply for this project please fill in an online application form through the following link.