Related papers: An all-magnonic neuron with tunable fading memory
In this work, we introduce an optoelectronic spiking artificial neuron capable of operating at ultrafast rates ($\approx$ 100 ps/optical spike) and with low energy consumption ($<$ pJ/spike). The proposed system combines an excitable…
The field of magnonics, which utilizes propagating spin waves for nano-scale transmission and processing of information, has been significantly advanced by the advent of the spin-orbit torque. The latter phenomenon can allow one to overcome…
Spiking neural network offers the most bio-realistic approach to mimic the parallelism and compactness of the human brain. A spiking neuron is the central component of an SNN which generates information-encoded spikes. We present a…
Ferromagnetic \nmg has unique magnetoelastic properties. These are investigated by detailed computational studies of the phonon dispersion curves for the non-modulated cubic \Ltw and tetragonal structures. For the \Ltw\ structure, a…
The capability of magnons to hybridize and strongly couple with diverse excitations offers a promising avenue for realizing and controlling emergent properties that hold significant potential for applications in devices, circuits, and…
A broadband quantum echo effect in a three level $\varLambda$-type system interacting with two laser fields is investigated theoretically. Inspired by the emerging field of nuclear quantum optics which typically deals with very narrow…
For scalable quantum communication and networks, a key step is to realize a quantum repeater node that can efficiently connect different segments of atom-photon entanglement using quantum memories. We report a compact and hardware-efficient…
Neuromorphic engineering makes use of mixed-signal analog and digital circuits to directly emulate the computational principles of biological brains. Such electronic systems offer a high degree of adaptability, robustness, and energy…
Transcranial static magnetic stimulation is a novel noninvasive method of reduction of the cortical excitability in certain neurological diseases that, unlike ordinary transcranial magnetic stimulation, makes use of static magnetic fields…
In the framework of magnonics all-optical femtosecond laser experiments are used to study spin waves and their relaxation paths. Magnonic crystal structures based on antidots allow the control over the spin-wave modes. In these…
Mirror neurons are a class of neurons that activate both when an individual observes an action and when they perform the same action. This mechanism reveals a fundamental interplay between action understanding and embodied execution,…
Nonlinear dynamics of spiking neural networks has recently attracted much interest as an approach to understand possible information processing in the brain and apply it to artificial intelligence. Since information can be processed by…
Nonlinear metasurfaces are multifunctional photonic elements that generate and control light, enabling multiple proof-of-principle applications, such as in nonlinear holography, beam shaping, and nanoscale sources of entangled photon pairs.…
Multiferroics offer an elegant means to implement voltage-control and on the fly reconfigurability in microscopic, nanoscaled systems based on ferromagnetic materials. These properties are particularly interesting for the field of…
The recent progress of artificial intelligence (AI) has boosted the computational possibilities in fields where standard computers are not able to perform. The AI paradigm is to emulate human intelligence and therefore breaks the familiar…
Benefiting from the event-driven and sparse spiking characteristics of the brain, spiking neural networks (SNNs) are becoming an energy-efficient alternative to artificial neural networks (ANNs). However, the performance gap between SNNs…
Multistable mechanical metamaterials enable programmable transitions between discrete stable states through propagating kink transition waves (TWs). Yet controlling these kinks typically requires local actuation or high-energy deformation,…
Magnonics, which employs spin-waves to transmit and process information, is a promising venue for low-power data processing. One of the major challenges is the local control of the spin-wave propagation path. Here, we introduce the concept…
Magnons are the quanta of collective spin excitations in magnetically-ordered systems and manipulation of magnons for computing and information processing has witnessed the development of ``magnonics". A magnon corresponds to an excitation…
We propose a computational model of neuron, called firing cell (FC), properties of which cover such phenomena as attenuation of receptors for external stimuli, delay and decay of postsynaptic potentials, modification of internal weights due…