Related papers: Biskyrmion-based artificial neuron with refractory…
Neuromorphic computing using spike-based learning has broad prospects in reducing computing power. Memristive neurons composed with two locally active memristors have been used to mimic the dynamical behaviors of biological neurons. In this…
Skyrmions and antiskyrmions are nanoscale swirling textures of magnetic moments formed by chiral interactions between atomic spins in magnetic non-centrosymmetric materials and multilayer films with broken inversion symmetry. These…
In this work we compute the torque field present in a ferromagnet in contact with a metallic nanowire when a skyrmion is present. If the nanowire is narrow enough the current is carried by a single conduction band. In this regime the…
Antiferromagnets are promising materials for future spintronic applications due to their unique properties including zero stray fields, robustness versus external magnetic fields and ultrafast dynamics, which have attracted extensive…
Skyrmion is a topologically protected spin texture excited in magnetic thin films. The radii of skyrmions are typically 10-100 nm. Because of the size, the skyrmion is expected to be a candidate for memory and novel-device usages. To…
Magnetic skyrmions are promising candidates as information carriers in spintronic devices. The transport of individual skyrmions in a fast and controlled way is a key issue in this field. Here we introduce a novel platform for accelerating,…
Acting as artificial synapses, two-terminal memristive devices are considered fundamental building blocks for the realization of artificial neural networks. Organized into large arrays with a top-down approach, memristive devices in…
Spiking Neural Networks (SNNs) offer a promising energy-efficient alternative to Artificial Neural Networks (ANNs) by utilizing sparse and asynchronous processing through discrete spike-based computation. However, the performance of deep…
Memristors have been suggested as neuromorphic computing elements. Spike-time dependent plasticity and the Hodgkin-Huxley model of the neuron have both been modelled effectively by memristor theory. The d.c. response of the memristor is a…
The spiking activity of neocortical neurons exhibits a striking level of variability, even when these networks are driven by identical stimuli. The approximately Poisson firing of neurons has led to the hypothesis that these neural networks…
Magnetic skyrmions hold promise for spintronic devices. To explore the dynamical properties of skyrmions in devices, a nanoscale method to image spin textures in response to a stimulus is essential. Here, we apply a technique for operando…
Magnetic skyrmions are topological magnetic textures that hold great promise as nanoscale bits of information in memory and logic devices. Although room-temperature ferromagnetic skyrmions and their current-induced manipulation have been…
The physical mechanisms underlying current-driven skyrmion motion include the spin-transfer torque exerted by a spin-polarized horizontal electric current and the spin-orbit torque exerted by a perpendicular spin current. Each mechanism…
Magnetic skyrmions are of considerable interest for low-power memory and logic devices because of high speed at low current and high stability due to topological protection. We propose a skyrmion field-effect transistor based on a…
Magnetic skyrmions are topologically protected states that are very promising for the design of the next generation of ultralow-power electronic devices. In this letter, we propose a magnetic tunnel junction based spin-transfer torque diode…
Spiking neural network (SNN) is interesting due to its strong bio-plausibility and high energy efficiency. However, its performance is falling far behind conventional deep neural networks (DNNs). In this paper, considering a general class…
Neuromorphic computing uses brain-inspired principles to design circuits that can perform computational tasks with superior power efficiency to conventional computers. Approaches that use traditional electronic devices to create artificial…
Magnetic Skyrmions and multiferroics are the most interesting objects in nanostructure science that have great potential in future spin-electronic technology. The study of multiferroic Skyrmions has attracted much interest in recent years.…
Heterogeneous systems with analog CMOS circuits integrated with nanoscale memristive devices enable efficient deployment of neural networks on neuromorphic hardware. CMOS Neuron with low footprint can emulate slow temporal dynamics by…
Biological image processing is performed by complex neural networks composed of thousands of neurons interconnected via thousands of synapses, some of which are excitatory and others inhibitory. Spiking neural models are distinguished from…