相关论文: Shape-based Magnetic Domain Wall Drift for an Arti…

Current induced domain wall (DW) motion in perpendicularly magnetized nanostripes in the presence of spin orbit torques is studied. We show using micromagnetic simulations that the direction of the current induced DW motion and the…

Spiking Neural Networks (SNNs) have emerged as energy-efficient alternatives to traditional artificial neural networks, leveraging asynchronous and biologically inspired neuron dynamics. Among existing neuron models, the Leaky…

We report the results of micromagnetic simulations of domain wall (DW) nucleation and pinning/depinning processes in ferromagnetic planar structure consisting of nanowire (NW) with perpendicular anisotropy and special V-shaped nanoparticle…

In artificial neural networks, neurons are usually implemented with highly dissipative CMOS-based operational amplifiers. A more energy-efficient implementation is a 'spin-neuron' realized with a magneto-tunneling junction (MTJ) that is…

We present an array of leaky integrate-and-fire (LIF) neuron circuits designed for the second-generation BrainScaleS mixed-signal 65-nm CMOS neuromorphic hardware. The neuronal array is embedded in the analog network core of a scaled-down…

Spiking neural networks (SNNs) aim to simulate real neural networks in the human brain with biologically plausible neurons. The leaky integrate-and-fire (LIF) neuron is one of the most widely studied SNN architectures. However, it has the…

The fundamental limits currently faced by traditional computing devices necessitate the exploration of new ways to store, compute and transmit information. Here, we propose a three-dimensional (3D) magnetic interconnector that exploits…

A domain wall (DW) in a nanowire can propagate under a longitudinal magnetic field by emitting spin waves (SWs). We numerically investigated the properties of SWs emitted by the DW motion, such as frequency and wavenumber, and their…

We investigate the magnetic domain wall (DW) dynamics in uniaxial/biaxial nanowires under a thermal gradient (TG). The findings reveal that the DW propagates toward the hotter region in both nanowires. The main physics of such observations…

In this work, we examine fundamental elements of spiking neural networks (SNNs) as well as how to tune them. Concretely, we focus on two different foundational neuronal units utilized in SNNs -- the leaky integrate-and-fire (LIF) and the…

An energy-efficient voltage controlled domain wall device for implementing an artificial neuron and synapse is analyzed using micromagnetic modeling in the presence of room temperature thermal noise. By controlling the domain wall motion…

We show that in a magnetic nanowire with double magnetic domain walls, quantum interference results in spin-split quasistationary states localized mainly between the domain walls. Spin-flip-assisted transmission through the domain structure…

Sliding ferroelectricity in bilayer van der Waals materials exhibits ultrafast switching speed and fatigue resistance during the polarization switching, offering an avenue for the design of memories and neuromorphic devices. The unique…

We present a biophysical approach for the coupling of neural network activity as resulting from proper dipole currents of cortical pyramidal neurons to the electric field in extracellular fluid. Starting from a reduced threecompartment…

Leaky-integrate-and-fire (LIF) is studied as a non-linear operator that maps an integrable signal $f$ to a sequence $\eta_f$ of discrete events, the spikes. In the case without any Dirac pulses in the input, it makes no difference whether…

Spintronic artificial neurons are intriguing building blocks for energy efficient Neuromorphic Computing (NC). Nevertheless, most contemporary implementations rely on symmetry breaking external in plane magnetic fields (H_X) for neuron…

Using neuromorphic computing for robotics applications has gained much attention in recent year due to the remarkable ability of Spiking Neural Networks (SNNs) for high-precision yet low memory and compute complexity inference when…

The Spiking Neural Network (SNN) has drawn increasing attention for its energy-efficient, event-driven processing and biological plausibility. To train SNNs via backpropagation, surrogate gradients are used to approximate the…

In the last decade, two revolutionary concepts in nano magnetism emerged from research for storage technologies and advanced information processing. The first suggests the use of magnetic domain walls (DWs) in ferromagnetic nanowires to…

Manipulation of magnetic domain walls via a helicity-independent laser pulse has recently been experimentally demonstrated and various physical mechanisms leading to domain wall dynamics have been discussed. Spin-dependent superdiffusive…