Optimal background treatment in dipolar spectroscopy

Abstract

Treatment of the background in dipolar EPR spectroscopy signals is a critical processing step for the recovery of the underlying distance distributions. Here we present new mathematical considerations that show pitfalls of background subtraction and division. In order to overcome these problems we propose an improved background treatment approach. We show, empirically, that this new method outperforms the established ones and analyze the established practice of post-correction signal truncation, as well as the influence of moderate background-fit errors, on accuracy of distance distributions.