Applying our implementation of the parameter estimation approach, we can evaluate the behaviour of algorithm as the problem size grows. For the purposes of testing, we initially perform the parameter estimation for a simple model based on point-charges. As per Figure , the result of each local optimisation can be categorised into 1) runs that converged to an optimum and for which the T M F is unchanged upon re-evaluation (i.e., satisfies B3 in Figure ), 2) runs that did not converge to an optimum but terminated due to a slow decrease or increase in the T M F (i.e., a sub-optimal point that satisfies B4 or B5 in Figure ), and 3) runs that terminated prematurely due to a failure at some stage of the algorithm.