Compensated Ferrimagnet Based Artificial Synapse and Neuron for Ultrafast Neuromorphic Computing

Abstract

Abstract Spintronic devices are considered a possible solution for the hardware implementation of artificial synapses and neurons, as a result of their non‐volatility, high scalability, complementary metal‐oxide‐semiconductor transistor compatibility, and low power consumption. As compared to ferromagnets, ferrimagnet‐based spintronics exhibits equivalently fascinating properties that have been witnessed in ultrafast spin dynamics, together with efficient electrical or optical manipulation. Their applications in neuromorphic computing, however, have still not been revealed, which motivates the present experimental study. Here, by using compensated ferrimagnets containing Co 0.80 Gd 0.20 with perpendicular magnetic anisotropy, it is demonstrated that the behavior of spin‐orbit torque switching in compensated ferrimagnets could be used to mimic biological synapses and neurons. In particular, by using the anomalous Hall effect and magneto‐optical Kerr effect imaging measurements, the ultrafast stimulation of artificial synapses and neurons is illustrated, with a time scale down to 10 ns. Using experimentally derived device parameters, a three‐layer fully connected neural network for handwritten digits recognition is further simulated, based on which, an accuracy of more than 93% could be achieved. The results identify compensated ferrimagnets as an intriguing candidate for the ultrafast neuromorphic spintronics.