Thesis Supervisor: Daniel Bramich

Abstract

Mathematical algorithms play an important role in all aspects of astronomical investigation and data calibration. Many algorithms are developed only to be applied to data without a full investigation of their parameter space, or a proper consideration of the relevant error models. Hence there is a large potential for investigation into improving and optimising exisiting algorithms, and the development of new algorithms all across the area of scientific research in Astronomy. There are also always opportunities for introducing algorithms from other sciences to the astronomical community via applications to research problems.

The exact project(s) a student will undertake will be down to which algorithms the student finds interesting and the potential for improvement and development of these algorithms. The general thrust of the investigation will be in the area of astronomical data reduction and calibration. CCD imaging, photometry and astrometry are particular areas of interest (e.g: star matching algorithms, template image construction, difference imaging etc.).

The nature of the work will necessarily be mathematical and would suit an astronomy student with a strong mathematical background and good programming skills.

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