  We present an algorithm to extract the distance list from atomic pair
distribution functions (PDFs) in a highly automated way. The algorithm is
constructed via curve fitting based on a Debye scattering equation model. Due
to the non-convex nature of the resulting optimization problem, a number of
techniques are developed to overcome various computational difficulties. A key
ingredient is a new approach to obtain a reasonable initial guess based on the
theoretical properties of the mathematical model. Tests on various
nanostructured samples show the effectiveness of the initial guess and the
accuracy and overall good performance of the extraction algorithm. This
approach could be extended to any spectrum that is approximated as a sum of
Gaussian functions.
