  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.
