Global analysis of complex PELDOR time traces.

Pulsed electron-electron double resonance (PELDOR, alternatively called DEER for double electron-electron resonance) pulse sequences allow for the detection of echo decay curves that are modulated by dipole-dipole-coupling frequencies of interacting electron spins. With increasing distance between them, the echo decay needs to be monitored over a progressively extended time period. However, since the echo intensity typically falls off exponentially with increasing time, this might be problematic with respect to the minimum signal-to-noise ratio required for a sound data analysis. In this contribution we present the new PELDOR analysis tool GloPel (Global analysis of PELDOR data), an open-source Python-based application, that allows to extract improved-quality distance distributions from PELDOR data for which no ideal signal-to-noise ratio can be achieved for a very long observation window. By using Tikhonov regularization, GloPel allows for the simultaneous analysis of two time traces acquired for a sample in two different observation time windows, thus taking advantage of both, the typically high signal-to-noise ratio of the time trace acquired at early times of the echo decay, and the best possible background function fitted for the decay at later times, which is in most cases superimposed with considerable noise. In this way, short distances are not overseen in the higher noise of the longer time traces while long distances are not artificially shortened by limiting the observation time window of the experiment. Following our suggested data acquisition procedure, a significant reduction of the measurement time may also be achieved.