Thin electrodes of magnetic tunnel junctions can show superparamagnetism at surprisingly low temperature. We analysed their thermally induced switching for varying temperature, magnetic and electric field. Although the dwell times follow an Arrhenius law, they are orders of magnitude too small compared to a model of single domain activation. Including entropic effects removes this inconsistency and leads to a magnetic activation volume much smaller than that of the electrode. Comparing data for varying barrier thickness then allows to separate the impact of Zeman energy, spin-transfer-torque and voltage induced anisotropy change on the dwell times. Based on these results, we demonstrate a tuning of the switching rates by combining magnetic and electric fields, which opens a path for their application in noisy neural networks.
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