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Topologically stable magnetic skyrmion has a much lower depinning currentdensity that may be useful for memory as well as neuromorphic computing.However, skyrmion-based devices suffer from the Magnus force originating fromthe skyrmion Hall effect, which may result in unwanted skyrmion annihilation ifthe magnitude of the driving current gets too large. A design of an artificialneuron and a synapse using a synthetic antiferromagnetically coupled bilayerdevice, which nullifies the Magnus force, is demonstrated in this work. Theleak term in the artificial leaky integrate-and-fire neuron is achieved byengineering the uniaxial anisotropy profile of the neuronal device. Thesynaptic device has a similar structure as the neuronal device but has aconstant uniaxial anisotropy. The synaptic device also has a linear andsymmetric weight update, which is a highly desirable trait of an artificialsynapse. Neuronal and synaptic devices based on magnetic domain-wall (DW)motion are also studied and compared to skyrmionic devices. Our simulationresults show the energy required to perform such operation in DW orskyrmion-based devices is on the order of a few fJ.

Design of Spintronics-based Neuronal and Synaptic Devices for Spiking Neural Network Circuits