Aperture photometry assumes that the background varies in a linear fashion in the aperture’s vicinity. However, in a dense star cluster the background is usually nonlinear. Therefore, one may use point spread function (PSF) photometry in order to meaningfully measure the brightnesses of the sources. In the latter approach, a single model is fitted to each object allowing one to determine, with subpixel precision, their position, amplitude, and width.

However, this becomes a non straightforward task when considering fitting multiple overlapping objects. To do so, one can not “just fit a model with hundreds parameters”. In fact, there exist several problems with this “brute force” approach, and the most critical one might be that the parameter space will have many dimensions (as many as the number of parameters, precisely), which almost certainly will make optimization algorithms to diverge or to get stuck in a local minima.

Hence, my primary task is to work on developing an algorithm to localize, fit, and perform photometry of several overlapping objects (e.g. a dense star cluster, globular clusters, etc) simultaneously.