8. Straying from the path: improving the XMM-Newton mirror models with out-of-field observations of Sco X-1

     

    ESA supervisor: Felix Meeker-Fuerst
    Collaborator(s): Ivan Valtchanov

    Site: ESAC

    XMM-Newton is the X-ray telescope of ESA and a workhorse for understanding black holes, supernovae, and galaxy clusters. It works by focusing X-rays through 3 telescopes made of gold coated concentric mirror shells.  The mirrors were measured on the ground and based on these data a mirror model was built, which is still in use today. This model describes the effective area of the mirrors at different energies and off-axis angles. Some astrophysical observations show that the model might not perfectly reflect reality and needs updating. 

    In this trainee project, the successful candidate will analyse recently obtained out-of-field observation of Sco X-1, which show characteristic single reflection rings from the mirror shells. By comparing the images of these shells to ray-tracing simulations based on a custom-built software, a better understanding of the exact alignment of all shells can be obtained. These data will be paramount to update the mirror model and improve the calibration of XMM-Newton.

    The candidate will work in close collaboration with the calibration experts at ESAC and the Max-Planck Institute for Extraterrestrial Physics in Germany. The project sits at the intersection between engineering and science and is therefore suited for any candidate curious about X-ray optics, X-ray astronomy, and modern satellite operations. The expected duration is 6 months, to allow time for the candidate to familiarize themselves with XMM-Newton and the necessary software.

    Project duration: 6 months.

    Desirable expertise or programming language:

    • Enthusiasm and curiosity for exploring scientific data.
    • The trainee should be comfortable with working in an international environment 
    • Some experience with command line computing (e.g. terminal, Unix) and a scripting language (e.g. python) is beneficial.
    • Basic knowledge about X-ray telescopes and X-ray data is desirable, but not required.

     

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