FABADA goes MANTID to answer an old question: How many lines are there?

Abstract

Data fitting and model selection lie at the very heart of the scientific method, and these tasks are often tackled via the use of popular (and typically unquestioned) optimization algorithms of limited validity or flexibility, e.g., least-squares methods. To circumvent these limitations, this work introduces the implementation within the MANTID framework of robust inference methods based on the Bayesian fitting algorithm FABADA. The power of this new MANTID tool is illustrated by revisiting an overarching and recurring question in the interpretation of quasielastic neutron scattering measurements, that is, how many spectral components may (or may not) be justified by the available experimental data.