A binary stochastic neuron (BSN) or a probabilistic bit (p-bit) randomly fluctuates between digitized “0” and “1” with a controllable functionality of time-averaged value. Such an unconventional bit is the most essential building block for the recently proposed stochastic neural networks and probabilistic computing. Here, we experimentally implement a magnetic tunnel junction (MTJ) for BSN, with relaxation times on the order of tens of milliseconds that can be modulated by a current-induced spin-transfer torque. The NIST Statistical Test Suite (800-22a) is used to verify true random number generation by the BSN-MTJ device. Our results suggest the possibility of using the artificial BSN MTJ device in neuromorphic applications as well as in a recently proposed probabilistic computing.

We present detailed investigations of the magnetic properties of Pt/CoFeB/MgO layers as studied using the angle-resolved spin-torque ferromagnetic resonance method. Although the measurements provide reasonable magnetic parameters, we obtain an unusual value in the interfacial spin transparency if spin-pumping is assumed to be the dominant source for enhancing magnetic damping ( αeff) in the nanometer thickness regime. However, the thickness dependence of the Landé g-factor ( geff) for CoFeB indicates that the interfacial spin–orbit coupling plays a role in determining αeff. In addition, the azimuthal asymmetry in the magnetic system may not be related to the possibility of generating unconventional spin polarization. The results in this work are expected to aid in understanding various magnetic properties and current-induced spin-torques in a heavy-metal/ferromagnet bilayer.