Related papers: Spintronic virtual neural network by a voltage con…
Using a nonequilibrium Monte Carlo method suitable to nanomagnetism, we investigate representative systems of interacting sub-10nm grained nanomagnets with large uniaxial anisotropy. Various magnetization memory and aging effects are found…
Ferromagnetic shape memory alloys (MSMAs), such as Ni-Mn-Ga single crystals, can exhibit the shape memory effect due to an applied magnetic field at room temperature. Under a variable magnetic field and a constant bias stress loading, MSMAs…
Recurrent neural networks are used in virtual analog modeling applications to digitally replicate the sound of analog hardware audio processors. The controls of hardware devices can be used as a conditioning input to these networks. A…
Multiple neuromorphic applications require the tuning of two or more devices to a common signal. Various types of neuromorphic computation can be realized using spintronic oscillators, where the DC current induces magnetization precession,…
We suggest a novel approach for wide-field imaging of the neural network dynamics of brain slices that uses highly sensitivity magnetometry based on nitrogen-vacancy (NV) centers in diamond. In-vitro recordings in brain slices is a proven…
We demonstrate that transport spectroscopy of single molecular magnets shows signatures of quantum tunneling at low temperatures. We find current and noise oscillations as function of bias voltage due to a weak violation of spin selection…
We demonstrate field and current controlled magnetodynamics in nanocontact spin-torque nano-oscillators (STNOs) based on orthogonal magnetic tunnel junctions (MTJs). We systematically analyze the microwave properties (frequency $f$,…
Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and…
A current research trend in neurocomputing involves the design of novel artificial neural networks incorporating the concept of time into their operating model. In this paper, a novel architecture that employs stigmergy is proposed.…
Algorithms for associative memory typically rely on a network of many connected units. The prototypical example is the Hopfield model, whose generalizations to the quantum realm are mainly based on open quantum Ising models. We propose a…
Artificial intelligence based on artificial neural networks, which are originally inspired by the biological architectures of human brain, has mostly been realized using software but executed on conventional von Neumann computers, where the…
Antiferromagnetic materials have a vanishingly small net magnetization, which generates weak dipolar fields and makes them robust against external magnetic perturbation and rapid magnetization dynamics, as dictated by the geometric mean of…
The current study uses a novel method of multilevel neurons and high order synchronization effects described by a family of special metrics, for pattern recognition in an oscillatory neural network (ONN). The output oscillator (neuron) of…
Electrical-controllable antiferromagnet tunnel junction is a key goal in spintronics, holding immense promise for ultra-dense and ultra-stable antiferromagnetic memory with high processing speed for modern information technology. Here, we…
We propose an analog implementation of the transcendental activation function leveraging two spin-orbit torque magnetoresistive random-access memory (SOT-MRAM) devices and a CMOS inverter. The proposed analog neuron circuit consumes 1.8-27x…
Highly efficient information processing in brain is based on processing and memory components called synapses, whose output is dependent on the history of the signals passed through them. Here we have developed an artificial synapse with…
We investigate a new method to augment recurrent neural networks with extra memory without increasing the number of network parameters. The system has an associative memory based on complex-valued vectors and is closely related to…
Brain-inspired non-Boolean computing offers intrinsic error tolerance and parallelism, but its practical deployment is limited by the lack of compact, energy-efficient spiking hardware compatible with large-scale integration. Mott…
Perpendicular magnetic anisotropy (PMA) plays a critical role in the development of spintronics, thereby demanding new strategies to control PMA. Here we demonstrate a conceptually new type of interface induced PMA that is controlled by…
Demonstration of ultra-low energy switching mechanisms is an imperative for continued improvements in computing devices. Ferroelectric (FE) and multiferroic (MF) orders and their manipulation promises an ideal combination of state variables…