Multi-criteria search and optimization: an application to X-ray plasma spectroscopy

X-ray spectroscopy diagnostics have been widely used as a standard technique to determine the temperature and density of astrophysical and laboratory plasmas. Traditional techniques have relied on performing an interactive search with a graphical user interface to select theoretical model parameters that best fit the data. We use a Pareto optimal genetic algorithm to drive a search of model parameters that produce high-quality simultaneous fits of spectra and spatially-resolved emissivity profiles. Preliminary results indicate that our Pareto optimal genetic algorithm is able to quickly find physically meaningful solutions.