Exploring the cool Universe with Point Process Mapping
The hidden wealth of astrophysics is still to be extracted from Herschel observations.
The matter involved in the formation of stars and planets is initially very cool, and so it radiates at long wavelengths, typically 30 μm to 1000 μm. Most of this radiation is continuum emission from dust, and the rest is mainly line emission from molecules. This is why expensive observatories like HERSCHEL were built, and why there is a major continuing effort to expand observing capabilities at these wavelengths, in terms of spatial and spectral resolution, and sky coverage, with observatories like ALMA and IRAM.
This project will analyse the huge data sets from these observatories, using the new PPMAP algorithm. As compared with the standard analysis procedures, PPMAP makes fewer assumptions (and no new ones) yet delivers approximately 1000 times more information, so it really is a game-changer. Specifically, PPMAP (i) improves the resolution, with pixels about 20 times smaller in area, (ii) it determines the temperature distribution of the emitting dust along each line of sight, and (iii) it determines variations in the properties of dust along the line of sight.
The specific objectives will be to generate large data hyper-cubes using PPMAP, and then to analyse them statistically to look for characteristic patterns that can be used to constrain the physics of the underlying sources (proto-stars, proto-planetary discs, HII regions, stellar-wind bubbles, supernova remnants, galactic nuclei and outflows, high redshift galaxies) and their interrelations. The student will learn to handle very large data sets, and to analyse them statistically.