Related papers: Skyrmion-Magnetic Tunnel Junction Synapse with Mix…
In crossbar array structures, which serves as an "In-Memory" compute engine for Artificial Intelligence hardware, write sneak path problem causes undesired switching of devices that degrades network accuracy. While custom crossbar…
Spintronic devices have recently attracted a lot of attention in the field of unconventional computing due to their non-volatility for short and long term memory, non-linear fast response and relatively small footprint. Here we report how…
Real-time tracking of high-speed objects in cognitive tasks is challenging in the present artificial intelligence techniques because the data processing and computation are time-consuming resulting in impeditive time delays. A…
Magnetic skyrmions are particle-like chiral spin textures found in a magnetic film with out-of-planeanisotropy and are considered to be potential candidates as information carriers in next generationdata storage devices. Despite intense…
Neuromorphic computing aims to develop energy-efficient devices that mimic biological synapses. One promising approach involves memristive devices that can dynamically adjust their electrical resistance in response to stimuli, similar to…
Traditional computation based on von Neumann architecture is limited by the time and energy consumption due to data transfer between the storage and the processing units. The von Neumann architecture is also inefficient in solving…
Skyrmions and antiskyrmions are nanoscale swirling textures of magnetic moments formed by chiral interactions between atomic spins in magnetic non-centrosymmetric materials and multilayer films with broken inversion symmetry. These…
Spin-torque memristors were proposed in 2009, which could provide fast, low-power and infinite memristive behavior for large-density non-volatile memory and neuromorphic computing. However, the strict requirements of combining high…
Skyrmion qubits are a new highly promising logic element for quantum information processing. However, their scalability to multiple interacting qubits remains challenging. We propose a hybrid quantum setup with skyrmion qubits strongly…
The desire to empower resource-limited edge devices with computer vision (CV) must overcome the high energy consumption of collecting and processing vast sensory data. To address the challenge, this work proposes an energy-efficient…
Replicating the computational functionalities and performances of the brain remains one of the biggest challenges for the future of information and communication technologies. Such an ambitious goal requires research efforts from the…
We demonstrate that thermally stable perpendicular magnetic tunnel junctions (pMTJs), widely used in spin-transfer torque magnetic random-access memory, can be actuated with nanosecond pulses to exhibit tunable stochastic behavior. This…
There is growing interest in exploring nanomagnetic devices as potential replacements for electronic devices (e.g. transistors) in digital switching circuits and systems. A special class of nanomagnetic devices are switched with…
The ever-increasing amount of data from ubiquitous smart devices fosters data-centric and cognitive algorithms. Traditional digital computer systems have separate logic and memory units, resulting in a huge delay and energy cost for…
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…
Learning and memory in the brain are implemented by complex, time-varying changes in neural circuitry. The computational rules according to which synaptic weights change over time are the subject of much research, and are not precisely…
Significant scientific and technological progress in the field of spintronics is based on trilayer magnetic tunnel junction devices which principally rely on the physics of single barrier tunneling. While technologically relevant devices…
Magnetic skyrmions are topologically nontrivial particles with a potential application as information elements in future spintronic device architectures. While they are commonly portrayed as two dimensional objects, in reality magnetic…
Straintronic magneto-tunneling junction (s-MTJ) switches, whose resistances are controlled with voltage-generated strain in the magnetostrictive free layer of the MTJ, are extremely energy-efficient switches that would dissipate a few aJ of…
Brain-inspired learning in physical hardware has enormous potential to learn fast at minimal energy expenditure. One of the characteristics of biological learning systems is their ability to learn in the presence of various noise sources.…