9. Periodicity in billions of Gaia astrometric timeseries.

     

    ESA supervisor: Jan Reerink
    Collaborator(s): José Hernandez, Johannes Sahlmann, Alex Bombrun

    Site: ESAC

    Gaia's fourth data release (GDR4) will contain series of highly-accurate positional measurements for more than 2 billion astronomical sources. These astrometric timeseries carry a wealth of information of astrophysical and technical nature, but only a small fraction are searched for periodic patterns beyond parallax by the Gaia data processing pipelines. The goal of this project is to enable the source-specific discovery of periodic astrometric signals across the entire GDR4 dataset, which will make it possible to discover and study phenomena related to binary stars, black holes, exoplanets, instrumental effects, survey artefacts, and much more. The trainee will develop a robust and scalable approach for computing periodograms of large amounts of astrometric timeseries in the Gaia archive, using the computational and scientific resources available at ESAC. Depending on the trainee's interest and expertise, it will be possible to shift the project's focus between the possible astrophysical exploitation (e.g. initial classification) of the results, performance and interface improvements, and data visualisation. In accordance with Gaia consortium policies, no publication based on the analysed Gaia data will be allowed before GDR4.
     

    Project duration: 6 months.

    Desirable expertise or programming language:

    • Computer and data science  
    • Programming experience in Python would be an advantage

     

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