Related papers: Benchmarking Inverse Rashba-Edelstein Magnetoelect…
We simulated the remagnetization dynamics of the ultra-dense and ultra-thin magnetic dot array system with dipole-dipole and exchange coupling interactions. Within the proposed 2D XY superlattice model, the square dots are modeled by the…
Intelligent biological systems are characterized by their embodiment in a complex environment and the intimate interplay between their nervous systems and the nonlinear mechanical properties of their bodies. This coordination, in which the…
The MagnetoEncephaloGraphy (MEG) has gained great interest in neurorehabilitation training due to its high temporal resolution. The challenge is to localize the active regions of the brain in a fast and accurate way. In this paper we use an…
Non-magnetic materials without inversion symmetry typically exhibit strong Rashba spin-orbit coupling (SOC), enabling the well-known Rashba Edelstein effect where an external electrical current induces transverse spin polarisation. In this…
Neuromorphic architectures, which incorporate parallel and in-memory processing, are crucial for accelerating artificial neural network (ANN) computations. This work presents a novel memristor-based multi-layer neural network (memristive…
Recent years have seen an increasing interest in the development of artificial intelligence circuits and systems for edge computing applications. In-memory computing mixed-signal neuromorphic architectures provide promising ultra-low-power…
We explore a case example of networks of classical electronic oscillators evolving towards the solution of complex optimization problems. We show that when driven into subharmonic response, a network of such nonlinear electrical resonators…
We derive the eigenenergies and eigenstates of electrons in a quantum wire subjected to an external magnetic field. These are calculated in the presence of spin orbit interactions arising from the Rashba (structural inversion asymmetry) and…
Stochastic spiking neural networks based on nanoelectronic spin devices can be a possible pathway to achieving "brainlike" compact and energy-effcient cognitive intelligence. The computational model attempt to exploit the intrinsic device…
As numerical simulations grow in size and complexity, they become increasingly resource-intensive in terms of time and energy. While specialized hardware accelerators often provide order-of-magnitude gains and are state of the art in other…
The Edelstein effect occurring in systems with broken inversion symmetry generates a spin polarization when an electric field is applied, which is most advantageous in spintronics applications. Unfortunately, it became apparent that this…
Designing two-dimensional (2D) Rashba semiconductors, exploring the underlying mechanism of Rashba effect, and further proposing efficient and controllable approaches are crucial for the development of spintronics. On the basis of…
This note is meant to invite the reader to consider interaction nets, a relatively recently discovered model of computation, as a possible alternative for cellular automata which are often employed as the basis for digital physics. Defined…
Deep Neural Networks (DNN) have achieved human level performance in many image analytics tasks but DNNs are mostly deployed to GPU platforms that consume a considerable amount of power. Brain-inspired spiking neuromorphic chips consume low…
Neuromorphic systems that employ advanced synaptic learning rules, such as the three-factor learning rule, require synaptic devices of increased complexity. Herein, a novel neoHebbian artificial synapse utilizing ReRAM devices has been…
Therapeutic intervention in neurological disorders still relies heavily on pharmacological solutions, while the treatment of patients with drug resistance remains an open challenge. This is particularly true for patients with epilepsy, 30%…
The spin Edelstein effect has proven to be a promising phenomenon to generate spin polarization from a charge current in systems without inversion symmetry. In recent years, a current-induced orbital magnetization, called orbital Edelstein…
The memristance of a memristor depends on the amount of charge flowing through it and when current stops flowing through it, it remembers the state. Thus, memristors are extremely suited for implementation of memory units. Memristors find…
Bio-inspired computing has focused on neuron and synapses with great success. However, the connections between these, the dendrites, also play an important role. In this paper, we investigate the motivation for replicating dendritic…
Rashba effect describes how electrons moving in an electric field experience a momentum dependent magnetic field that couples to the electron angular momentum (spin). This physical phenomenon permits the generation of spin polarization from…