Kippenhahn Prize 2014 is awarded to two junior scientists
August 03, 2015
Since 2008, the Kippenhahn Prize is awarded for the best scientific publication written by an MPA student; it was donated by the former director of the institute, Prof. Rudolf Kippenhahn. The decision for 2014 was difficult due to the high quality of the submitted publications, so that the committee decided award the prize jointly to two young researchers: Richard D'Souza for his paper "Parametrizing the Stellar Haloes of Galaxies" and Marco Selig for his paper "D3PO - Denoising, Deconvolving, and Decomposing Photon Observations".
The galactic halo is an extended, roughly spherical component of stars, which extends beyond the main, visible component of the galaxy. As these stellar halos can be very faint, Richard used deep observations from the SDSS to stack a large number of images of individual galaxies. The stacked images of the galaxies reveal the existence of stellar halos around galaxies of all types, both elliptical and spiral, with masses ranging from that of the Small Magellanic Cloud to those of the most massive ellipticals in the centres of rich clusters. Richard led the difficult SDSS imaging analysis from start to finish and wrote up an excellent paper, which has been well received by the community.
The paper written by Marco Selig bridges from information theory to next generation astronomical imaging. It develops the D3PO algorithm, which performs several complex data analysis steps in order to process photon count data jointly and self-consistently. The results are two independent sky images, one for the diffuse flux and one for the point-like sources. D3PO has been applied to gamma ray data from the Fermi satellite, producing unique sky maps, a point source catalogue that is competitive with the best one of the Fermi collaboration, and separate maps revealing two diffuse phases of the interstellar medium. As "astro-infonaut", Marco crafted novel and versatile tools to extract signals with high fidelity from complex and noisy data sets which he then applied successfully to astronomical data.