Analytically optimized noise redistribution in pulse dipolar EPR spectroscopy

Abstract

Non-uniform data acquisition protocols are derived analytically for optimizing the measurement of nanometer distance information by pulse dipolar spectroscopy methods, such as DEER (Double Electron Electron Resonance). The random measurement noise is redistributed by non-uniform signal averaging of the signal. This optimizes accuracy and efficiency for measurement of the first four non-central moments of the distribution of distances within pairs of spin labels attached to nanostructures. With these protocols, the mean distance can typically be measured with the same accuracy in half the time or with 40% higher accuracy in the same time. Different signal averaging schemes are optimal for each of the first four moments, but the optimal scheme for the first moment works well for all moments and for measurement of the entire distance distribution of distances in the sample. These protocols were tested in silico using three approaches to analysis of DEER data: the Tikhonov regularization, model-based fitting, and Mellin transform approaches. The non-uniform acquisition protocols produced significantly better results from each of the analysis protocols.