Another issue with the approach of XGandalf is that candidate vectors for a * , b * and c * are only optimized independently, and then a solution basis is put together from these candidate vectors. That is, in order to index correctly, the algorithm requires all three vectors of the solution to be present in the candidate vectors, which decreases the Figure : TORO Indexer algorithmic flow: The process starts with mapping the positions of Bragg spots to a set of vectors in the three-dimensional reciprocal space. This dataset is then subjected to robust optimization methods, such as least trimmed squares and residual threshold annealing, in order to identify the crystal orientation. chances of finding a solution. Moreover, joint optimization occurs only during the final refinement step. This becomes problematic, particularly in the presence of a large number of outliers, as each candidate vector for a * , b * and c * might propose a different set of outliers, leading to incompatible solutions.