Reinforcement Learning Approach for Sub-Critical Current SOT-MRAM Switching

2021 
We present the use of reinforcement learning for the discovery of pulse sequences for optimal switching of spin-orbit torque magnetoresistive memory devices. A neural network trained on fixed material parameters is able to switch a memory cell for a wide range of material parameter variations as well as for sub-critical current values. Micromagnetic simulations are used to prove the reliability of the trained neural network.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    9
    References
    0
    Citations
    NaN
    KQI
    []