Related papers: Ultra-fast spin Hall nano-oscillator based microwa…
Spin torque nano-oscillators (STNOs) hold encouraging promise for nanoscale microwave generators, modulators, and new types of intelligent computing. The nonlinearity, describing the current-induced tunability of oscillating frequency, is a…
Noise spectroscopy elucidates the fundamental noise sources in spin systems, thereby serving as an essential tool toward developing spin qubits with long coherence times for quantum information processing, communication, and sensing. But…
Swept laser interferometry is an extremely powerful solution embedded in several recent technologies such as absolute distance measurement, light detection and ranging, optical frequency domain reflectometry, optical coherence tomography,…
Oscillator neural networks (ONN) are a promising hardware option for artificial intelligence. With an abundance of theoretical treatments of ONNs, few experimental implementations exist to date. In contrast to prior publications of only…
We propose a radical advance in Magnetic Resonance Imaging. MRI remains slow because it requires successive applications of magnetic field gradients to encode for spatial location. Parallel MRI accelerates imaging by permitting…
Spiking neural networks (SNNs) have gained attention in recent years due to their ability to handle sparse and event-based data better than regular artificial neural networks (ANNs). Since the structure of SNNs is less suited for typically…
Spiking neural networks (SNNs) recently gained momentum due to their low-power multiplication-free computing and the closer resemblance of biological processes in the nervous system of humans. However, SNNs require very long spike trains…
Spiking neural networks (SNNs) that enable low-power design on edge devices have recently attracted significant research. However, the temporal characteristic of SNNs causes high latency, high bandwidth and high energy consumption for the…
In this work, we have proposed a revolutionary neuromorphic computing methodology to implement All-Skyrmion Spiking Neural Network (AS-SNN). Such proposed methodology is based on our finding that skyrmion is a topological stable spin…
Spiking Neural Networks (SNNs) have garnered attention over recent years due to their increased energy efficiency and advantages in terms of operational complexity compared to traditional Artificial Neural Networks (ANNs). Two important…
One recent breakthrough in the field of magnonics is the experimental realization of reconfigurable spin-wave nanochannels formed by magnetic domain wall with a width of $10-100$ nm [Wagner \emph{et al}., Nat. Nano. \textbf{11}, 432…
Spiking neural networks (SNNs) can be used in low-power and embedded systems (such as emerging neuromorphic chips) due to their event-based nature. Also, they have the advantage of low computation cost in contrast to conventional artificial…
The ability to generate, detect, and control coherent terahertz (THz) spin currents with femtosecond temporal and nanoscale spatial resolution has significant ramifications. The diffraction limit of concentrated THz radiation, which has a…
Spiking neural network (SNN) is interesting both theoretically and practically because of its strong bio-inspiration nature and potentially outstanding energy efficiency. Unfortunately, its development has fallen far behind the conventional…
The spin dynamics of stripes in high-temperature superconductors and related compounds is studied in the framework of a spin-wave theory for a simple spin-only model. The magnon dispersion relation and the magnetic structure factor are…
We report on the design and first tests of a device allowing for measurement of ultracold neutrons polarisation by means of the simultaneous analysis of the two spin components. The device was developed in the framework of the neutron…
Radio Frequency (RF) sensing holds the potential for enabling pervasive monitoring applications. However, modern sensing algorithms imply complex operations, which clash with the energy-constrained nature of edge sensing devices. This calls…
We propose here a high-frequency spin-Hall nano-oscillator based on a simple magnetic texture, such as a domain wall, located in an antiferromagnet with easy-axis anisotropy type. We show that the spin current, polarized along the…
Spiking neural networks (SNNs) have closer dynamics to the brain than current deep neural networks. Their low power consumption and sample efficiency make these networks interesting. Recently, several deep convolutional spiking neural…
Highly luminescent ZnO:Na nanocrystals of size ~2 nm were synthesized using a improved sol-lyophilization process. The surface analysis such as survey scan, core-level and valence band spectra of ZnO:Na nanocrystals were studied using x-ray…